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+

OpenPipelines.bio v0.9.0

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+

MAJOR CHANGES

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  • Update component documentation to v0.9.0 release.
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MINOR CHANGES

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  • Update to Viash actions 0.4.0.
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OpenPipelines.bio v0.8.0

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MAJOR CHANGES

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  • Update component documentation to v0.8.0 release.

    • +

  • Use git submodule to access openpipeline repo

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  • Propose new website structure

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  • Update author page

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+

OpenPipelines.bio v0.7.2

+

First versioned release of the website.

+ + +
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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/index.html b/pr-preview/pr-51/components/index.html new file mode 100644 index 00000000..4b887696 --- /dev/null +++ b/pr-preview/pr-51/components/index.html @@ -0,0 +1,2744 @@ + + + + + + + + + + +OpenPipelines - Components + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Components

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+ +
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+ An overview of the workflows and modules in OpenPipelines +
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Workflows

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+Name + +Namespace + +Description +
+Workflows + +  + + +
+BD Rhapsody + +Ingestion + +A generic pipeline for running BD Rhapsody WTA or Targeted mapping, with support for AbSeq, VDJ and/or SMK. +
+Bbknn leiden + +Multiomics/integration + +Run bbknn followed by leiden clustering and run umap on the result. +
+Cell Ranger mapping + +Ingestion + +A pipeline for running Cell Ranger mapping. +
+Cell Ranger multi + +Ingestion + +A pipeline for running Cell Ranger multi. +
+Cell Ranger post-processing + +Ingestion + +Post-processing Cell Ranger datasets. +
+Conversion + +Ingestion + +A pipeline to convert different file formats to .h5mu. +
+Demux + +Ingestion + +A generic pipeline for running bcl2fastq, bcl-convert or Cell Ranger mkfastq. +
+Full pipeline + +Multiomics + +A pipeline to analyse multiple multiomics samples. +
+Harmony leiden + +Integration/common + +Run harmony integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+Harmony leiden + +Multiomics/integration + +Run harmony integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+Initialize integration + +Integration/initialize integration + +Run calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP. +
+Initialize integration + +Multiomics/integration + +Run calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP. +
+Integration + +Multiomics + +A pipeline for demultiplexing multimodal multi-sample RNA transcriptomics data. +
+Leiden scvi + +Multiomics/integration + +Run scvi integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+Make reference + +Ingestion + +Build a transcriptomics reference into one of many formats +
+Multisample + +Multiomics + +This workflow serves as an entrypoint into the ‘full_pipeline’ in order to re-run the multisample processing and the integration setup. +
+Prot multisample + +Multiomics + +Processing unimodal multi-sample ADT data. +
+Prot singlesample + +Multiomics + +Processing unimodal single-sample CITE-seq data. +
+Rna multisample + +Multiomics + +Processing unimodal multi-sample RNA transcriptomics data. +
+Rna singlesample + +Multiomics + +Processing unimodal single-sample RNA transcriptomics data. +
+Scanorama leiden + +Integration/scanorama leiden + +Run scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+Scanorama leiden + +Multiomics/integration + +Run scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+Scvi + +Integration/scvi + +Run scvi integration followed by neighbour calculations and run umap on the result. +
+Totalvi leiden + +Multiomics/integration + +Run totalVI integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+
+No matching items +
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+

Modules

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+Name + +Namespace + +Description +
+Modules + +  + + +
+Add id + +Metadata + +Add id of .obs. +
+BD Rhapsody + +Mapping + +A wrapper for the BD Rhapsody Analysis CWL v1.10.1 pipeline +
+Bbknn + +Neighbors + +BBKNN network generation +
+Bcl convert + +Demux + +Convert bcl files to fastq files using bcl-convert. +
+Bcl2fastq + +Demux + +Convert bcl files to fastq files using bcl2fastq +
+Build bdrhap reference + +Reference + +Compile a reference into a STAR index compatible with the BD Rhapsody pipeline. +
+Build cellranger reference + +Reference + +Build a Cell Ranger-compatible reference folder from user-supplied genome FASTA and gene GTF files. +
+Calculate qc metrics + +Qc + +Add basic quality control metrics to an .h5mu file. +
+Cellbender remove background + +Correction + +Eliminating technical artifacts from high-throughput single-cell RNA sequencing data. +
+Cellbender remove background v0 2 + +Correction + +Eliminating technical artifacts from high-throughput single-cell RNA sequencing data. +
+Cellranger count + +Mapping + +Align fastq files using Cell Ranger count. +
+Cellranger count split + +Mapping + +Split 10x Cell Ranger output directory into separate output fields. +
+Cellranger mkfastq + +Demux + +Demultiplex raw sequencing data +
+Cellranger multi + +Mapping + +Align fastq files using Cell Ranger multi. +
+Cellxgene census + +Query + +Query CellxGene Census or user-specified TileDBSoma object, and eventually fetch cell and gene metadata or/and expression counts. +
+Clr + +Transform + +Perform CLR normalization on CITE-seq data (Stoeckius et al., 2017) +
+Compress h5mu + +Compression + +Compress a MuData file. +
+Concat + +Dataflow + +Concatenates several uni-modal samples in .h5mu files into a single file +
+Delete layer + +Transform + +Delete an anndata layer from one or more modalities +
+Do filter + +Filter + +Remove observations and variables based on specified .obs and .var columns +
+Download file + +Download + +Download a file +
+Fastqc + +Qc + +Fastqc component, please see https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. +
+Filter 10xh5 + +Process 10xh5 + +Filter a 10x h5 dataset +
+Filter with counts + +Filter + +Filter scRNA-seq data based on the primary QC metrics. +
+Filter with hvg + +Filter + +Annotate highly variable genes [Satija15] [Zheng17] [Stuart19]. +
+Filter with scrublet + +Filter + +Doublet detection using the Scrublet method (Wolock, Lopez and Klein, 2019). +
+Find neighbors + +Neighbors + +Compute a neighborhood graph of observations [McInnes18]. +
+From 10xh5 to h5mu + +Convert + +Converts a 10x h5 into an h5mu file +
+From 10xmtx to h5mu + +Convert + +Converts a 10x mtx into an h5mu file +
+From bd to 10x molecular barcode tags + +Convert + +Convert the molecular barcode sequence SAM tag from BD format (MA) to 10X format (UB) +
+From bdrhap to h5mu + +Convert + +Convert the output of a BD Rhapsody WTA pipeline to a MuData h5 file +
+From cellranger multi to h5mu + +Convert + +Converts the output from cellranger multi to a single .h5mu file. +
+From h5ad to h5mu + +Convert + +Converts a single layer h5ad file into a single MuData object +
+From h5mu to h5ad + +Convert + +Converts a h5mu file into a h5ad file +
+Harmonypy + +Integrate + +Performs Harmony integration based as described in https://github.com/immunogenomics/harmony. +
+Htseq count + +Mapping + +Quantify gene expression for subsequent testing for differential expression. +
+Htseq count to h5mu + +Mapping + +Convert the htseq table to a h5mu +
+Join csv + +Metadata + +Join a csv containing metadata to the .obs or .var field of a mudata file. +
+Join uns to obs + +Metadata + +Join a data frame of length 1 (1 row index value) in .uns containing metadata to the .obs of a mudata file. +
+Knn + +Labels transfer + +Performs label transfer from reference to query using KNN classifier +
+Leiden + +Cluster + +Cluster cells using the Leiden algorithm [Traag18] implemented in the Scanpy framework [Wolf18]. +
+Lianapy + +Interpret + +Performs LIANA integration based as described in https://github.com/saezlab/liana-py +
+Log1p + +Transform + +Logarithmize the data matrix. +
+Make params + +Files + +Looks for files in a directory and turn it in a params file. +
+Make reference + +Reference + +Preprocess and build a transcriptome reference. +
+Merge + +Dataflow + +Combine one or more single-modality .h5mu files together into one .h5mu file +
+Mermaid + +Report + +Generates a network from mermaid code +
+Move obsm to obs + +Metadata + +Move a matrix from .obsm to .obs. +
+Multi star + +Mapping + +Align fastq files using STAR. +
+Multi star to h5mu + +Mapping + +Convert the output of multi_star to a h5mu +
+Multiqc + +Qc + +MultiQC aggregates results from bioinformatics analyses across many samples into a single report. +
+Normalize total + +Transform + +Normalize counts per cell. +
+Pca + +Dimred + +Computes PCA coordinates, loadings and variance decomposition. +
+Popv + +Annotate + +Performs popular major vote cell typing on single cell sequence data using multiple algorithms. +
+Publish + +Transfer + +Publish an artifact and optionally rename with parameters +
+Regress out + +Transform + +Regress out (mostly) unwanted sources of variation. +
+Remove modality + +Filter + +Remove a modality from a .h5mu file +
+Samtools sort + +Mapping + +Sort and (optionally) index alignments. +
+Scale + +Transform + +Scale data to unit variance and zero mean +
+Scanorama + +Integrate + +Use Scanorama to integrate different experiments +
+Scarches + +Integrate + +Performs reference mapping with scArches +
+Scvelo + +Velocity + +ID: scvelo
+Namespace: velocity +
+Scvi + +Integrate + +Performs scvi integration as done in the human lung cell atlas https://github.com/LungCellAtlas/HLCA +
+Split modalities + +Dataflow + +Split the modalities from a single .h5mu multimodal sample into seperate .h5mu files. +
+Star align + +Mapping + +Align fastq files using STAR. +
+Star align v273a + +Mapping + +Align fastq files using STAR. +
+Star build reference + +Mapping + +Create a reference for STAR from a set of fasta files. +
+Subset h5mu + +Filter + +Create a subset of a mudata file by selecting the first number of observations +
+Sync test resources + +Download + +Synchronise the test resources from s3://openpipelines-data to resources_test +
+Totalvi + +Integrate + +Performs mapping to the reference by totalvi model: https://docs.scvi-tools.org/en/stable/tutorials/notebooks/scarches_scvi_tools.html#Reference-mapping-with-TOTALVI +
+Umap + +Dimred + +UMAP (Uniform Manifold Approximation and Projection) is a manifold learning technique suitable for visualizing high-dimensional data. +
+Velocyto + +Velocity + +Runs the velocity analysis on a BAM file, outputting a loom file. +
+Velocyto to h5mu + +Convert + +Convert a velocyto loom file to a h5mu file. +
+Xgboost + +Labels transfer + +Performs label transfer from reference to query using XGBoost classifier +
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+No matching items +
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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/annotate/popv.html b/pr-preview/pr-51/components/modules/annotate/popv.html new file mode 100644 index 00000000..79672cd0 --- /dev/null +++ b/pr-preview/pr-51/components/modules/annotate/popv.html @@ -0,0 +1,1758 @@ + + + + + + + + + + +OpenPipelines - Popv + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+

Popv

+
+ +
+
+ Performs popular major vote cell typing on single cell sequence data using multiple algorithms. +
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+ + +
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+

Info

+

ID: popv
+Namespace: annotate

+
+ +

Note that this is a one-shot version of PopV.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/annotate/popv/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# input_layer: "foo"
+# input_obs_batch: "foo"
+# input_var_subset: "foo"
+# input_obs_label: "foo"
+unknown_celltype_label: "unknown"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Arguments
+methods: # please fill in - example: ["knn_on_scvi", "scanvi"]
+
+# Reference
+reference: # please fill in - example: "TS_Bladder_filtered.h5ad"
+# reference_layer: "foo"
+reference_obs_label: "cell_ontology_class"
+reference_obs_batch: "donor_assay"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/annotate/popv/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+

Arguments related to the input (aka query) dataset.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu file.file, required, example: "input.h5mu"
--modalityWhich modality to process.string, default: "rna"
--input_layerWhich layer to use. If no value is provided, the counts are assumed to be in the .X slot. Otherwise, count data is expected to be in .layers[input_layer].string
--input_obs_batchKey in obs field of input adata for batch information. If no value is provided, batch label is assumed to be unknown.string
--input_var_subsetSubset the input object with this column.string
--input_obs_labelKey in obs field of input adata for label information. This is only used for training scANVI. Unlabelled cells should be set to "unknown_celltype_label".string
--unknown_celltype_labelIf input_obs_label is specified, cells with this value will be treated as unknown and will be predicted by the model.string, default: "unknown"
+
+
+

Reference

+

Arguments related to the reference dataset.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--referenceUser-provided reference tissue. The data that will be used as reference to call cell types.file, required, example: "TS_Bladder_filtered.h5ad"
--reference_layerWhich layer to use. If no value is provided, the counts are assumed to be in the .X slot. Otherwise, count data is expected to be in .layers[reference_layer].string
--reference_obs_labelKey in obs field of reference AnnData with cell-type information.string, default: "cell_ontology_class"
--reference_obs_batchKey in obs field of input adata for batch information.string, default: "donor_assay"
+
+
+

Outputs

+

Output arguments.

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionstring, example: "gzip"
+
+
+

Arguments

+

Other arguments.

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--methodsMethods to call cell types. By default, runs to knn_on_scvi and scanvi.string, required, example: "knn_on_scvi", example: "scanvi"
+
+
+
+

Authors

+
    +

  • Matthias Beyens (author)

    • +

  • Robrecht Cannoodt (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/cluster/leiden.html b/pr-preview/pr-51/components/modules/cluster/leiden.html new file mode 100644 index 00000000..0a96faba --- /dev/null +++ b/pr-preview/pr-51/components/modules/cluster/leiden.html @@ -0,0 +1,1652 @@ + + + + + + + + + + +OpenPipelines - Leiden + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Leiden

+
+ +
+
+ Cluster cells using the Leiden algorithm [Traag18] implemented in the Scanpy framework [Wolf18]. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: leiden
+Namespace: cluster

+
+ +

Leiden is an improved version of the Louvain algorithm [Blondel08]. It has been proposed for single-cell analysis by [Levine15]. This requires having ran neighbors/find_neighbors or neighbors/bbknn first.

+

Blondel08: Blondel et al. (2008), Fast unfolding of communities in large networks, J. Stat. Mech.
+Levine15: Levine et al. (2015), Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis, Cell.
+Traag18: Traag et al. (2018), From Louvain to Leiden: guaranteeing well-connected communities arXiv.
+Wolf18: Wolf et al. (2018), Scanpy: large-scale single-cell gene expression data analysis, Genome Biology.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/cluster/leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+obsp_connectivities: "connectivities"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+obsm_name: "leiden"
+resolution: [1]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/cluster/leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput file.file, required, example: "input.h5mu"
--modalitystring, default: "rna"
--obsp_connectivitiesIn which .obsp slot the neighbor connectivities can be found.string, default: "connectivities"
--outputOutput file.file, required, example: "output.h5mu"
--output_compressionstring, example: "gzip"
--obsm_nameName of the .obsm key under which to add the cluster labels. The name of the columns in the matrix will correspond to the resolutions.string, default: "leiden"
--resolutionA parameter value controlling the coarseness of the clustering. Higher values lead to more clusters. Multiple values will result in clustering being performed multiple times.double, default: 1
+
+
+
+

Authors

+
    +
  • Dries De Maeyer (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/compression/compress_h5mu.html b/pr-preview/pr-51/components/modules/compression/compress_h5mu.html new file mode 100644 index 00000000..b6d5f7a4 --- /dev/null +++ b/pr-preview/pr-51/components/modules/compression/compress_h5mu.html @@ -0,0 +1,1623 @@ + + + + + + + + + + +OpenPipelines - Compress h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Compress h5mu

+
+ +
+
+ Compress a MuData file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: compress_h5mu
+Namespace: compression

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/compression/compress_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "sample_path"
+# output: "$id.$key.output.output"
+compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/compression/compress_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to the input .h5mu.file, required, example: "sample_path"
--outputlocation of output file.file, required
--compressionCompression type.string, default: "gzip"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/from_10xh5_to_h5mu.html b/pr-preview/pr-51/components/modules/convert/from_10xh5_to_h5mu.html new file mode 100644 index 00000000..c9b8d904 --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/from_10xh5_to_h5mu.html @@ -0,0 +1,1689 @@ + + + + + + + + + + +OpenPipelines - From 10xh5 to h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

From 10xh5 to h5mu

+
+ +
+
+ Converts a 10x h5 into an h5mu file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: from_10xh5_to_h5mu
+Namespace: convert

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/from_10xh5_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "raw_feature_bc_matrix.h5"
+# input_metrics_summary: "metrics_cellranger.h5"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+uns_metrics: "metrics_cellranger"
+
+# Arguments
+# min_genes: 100
+# min_counts: 1000
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/from_10xh5_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputA 10x h5 file as generated by Cell Ranger.file, required, example: "raw_feature_bc_matrix.h5"
--input_metrics_summaryA metrics summary csv file as generated by Cell Ranger.file, example: "metrics_cellranger.h5"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionstring, example: "gzip"
--uns_metricsName of the .uns slot under which to QC metrics (if any).string, default: "metrics_cellranger"
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--min_genesMinimum number of counts required for a cell to pass filtering.integer, example: 100
--min_countsMinimum number of genes expressed required for a cell to pass filtering.integer, example: 1000
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/from_10xmtx_to_h5mu.html b/pr-preview/pr-51/components/modules/convert/from_10xmtx_to_h5mu.html new file mode 100644 index 00000000..03fba7b8 --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/from_10xmtx_to_h5mu.html @@ -0,0 +1,1623 @@ + + + + + + + + + + +OpenPipelines - From 10xmtx to h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

From 10xmtx to h5mu

+
+ +
+
+ Converts a 10x mtx into an h5mu file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: from_10xmtx_to_h5mu
+Namespace: convert

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/from_10xmtx_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input_dir_containing_gz_files"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/from_10xmtx_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput mtx folderfile, required, example: "input_dir_containing_gz_files"
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionstring, example: "gzip"
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html b/pr-preview/pr-51/components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html new file mode 100644 index 00000000..ace767c2 --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html @@ -0,0 +1,1629 @@ + + + + + + + + + + +OpenPipelines - From bd to 10x molecular barcode tags + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

From bd to 10x molecular barcode tags

+
+ +
+
+ Convert the molecular barcode sequence SAM tag from BD format (MA) to 10X format (UB) +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: from_bd_to_10x_molecular_barcode_tags
+Namespace: convert

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/from_bd_to_10x_molecular_barcode_tags/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.bam"
+# output: "$id.$key.output.sam"
+bam: false
+# threads: 123
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/from_bd_to_10x_molecular_barcode_tags/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput SAM or BAM file.file, required, example: "input.bam"
--outputOutput alignment file.file, example: "output.sam"
--bamOutput a BAM file.boolean_true
--threadsNumber of threadsinteger
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/from_bdrhap_to_h5mu.html b/pr-preview/pr-51/components/modules/convert/from_bdrhap_to_h5mu.html new file mode 100644 index 00000000..855d308f --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/from_bdrhap_to_h5mu.html @@ -0,0 +1,1650 @@ + + + + + + + + + + +OpenPipelines - From bdrhap to h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

From bdrhap to h5mu

+
+ +
+
+ Convert the output of a BD Rhapsody WTA pipeline to a MuData h5 file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: from_bdrhap_to_h5mu
+Namespace: convert

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/from_bdrhap_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "my_id"
+input: # please fill in - example: "input_dir/"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/from_bdrhap_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idA sample ID.string, required, example: "my_id"
--inputThe output of a BD Rhapsody workflow.file, required, example: "input_dir"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionstring, example: "gzip"
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/from_cellranger_multi_to_h5mu.html b/pr-preview/pr-51/components/modules/convert/from_cellranger_multi_to_h5mu.html new file mode 100644 index 00000000..11358287 --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/from_cellranger_multi_to_h5mu.html @@ -0,0 +1,1632 @@ + + + + + + + + + + +OpenPipelines - From cellranger multi to h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

From cellranger multi to h5mu

+
+ +
+
+ Converts the output from cellranger multi to a single .h5mu file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: from_cellranger_multi_to_h5mu
+Namespace: convert

+
+ +

By default, will map the following library type names to modality names: - Gene Expression: rna - Peaks: atac - Antibody Capture: prot - VDJ: vdj - VDJ-T: vdj_t - VDJ-B: vdj_b - CRISPR Guide Capture: crispr - Multiplexing Capture: hashing

+

Other library types have their whitepace removed and dashes replaced by underscores to generate the modality name.

+

Currently does not allow parsing the output from cell barcode demultiplexing.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/from_cellranger_multi_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input_dir_containing_modalities"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+uns_metrics: "metrics_cellranger"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/from_cellranger_multi_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput folder. Must contain the output from a cellranger multi run.file, required, example: "input_dir_containing_modalities"
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionstring, example: "gzip"
--uns_metricsName of the .uns slot under which to QC metrics (if any).string, default: "metrics_cellranger"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/from_h5ad_to_h5mu.html b/pr-preview/pr-51/components/modules/convert/from_h5ad_to_h5mu.html new file mode 100644 index 00000000..33808506 --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/from_h5ad_to_h5mu.html @@ -0,0 +1,1629 @@ + + + + + + + + + + +OpenPipelines - From h5ad to h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

From h5ad to h5mu

+
+ +
+
+ Converts a single layer h5ad file into a single MuData object +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: from_h5ad_to_h5mu
+Namespace: convert

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/from_h5ad_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: ["input.h5ad"]
+modality: ["rna"]
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/from_h5ad_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5ad filesfile, required, default: "input.h5ad"
--modalitystring, default: "rna"
--outputOutput MuData file.file, default: "output.h5mu"
--output_compressionstring, example: "gzip"
+
+
+
+

Authors

+
    +
  • Dries De Maeyer (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/from_h5mu_to_h5ad.html b/pr-preview/pr-51/components/modules/convert/from_h5mu_to_h5ad.html new file mode 100644 index 00000000..8be9ed7f --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/from_h5mu_to_h5ad.html @@ -0,0 +1,1629 @@ + + + + + + + + + + +OpenPipelines - From h5mu to h5ad + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

From h5mu to h5ad

+
+ +
+
+ Converts a h5mu file into a h5ad file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: from_h5mu_to_h5ad
+Namespace: convert

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/from_h5mu_to_h5ad/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# output: "$id.$key.output.h5ad"
+output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/from_h5mu_to_h5ad/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput MuData filefile, required, default: "input.h5mu"
--modalitystring, default: "rna"
--outputOutput AnnData file.file, default: "output.h5ad"
--output_compressionThe compression format to be used on the final h5ad object.string, default: "gzip"
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/convert/velocyto_to_h5mu.html b/pr-preview/pr-51/components/modules/convert/velocyto_to_h5mu.html new file mode 100644 index 00000000..93f2261c --- /dev/null +++ b/pr-preview/pr-51/components/modules/convert/velocyto_to_h5mu.html @@ -0,0 +1,1677 @@ + + + + + + + + + + +OpenPipelines - Velocyto to h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Velocyto to h5mu

+
+ +
+
+ Convert a velocyto loom file to a h5mu file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: velocyto_to_h5mu
+Namespace: convert

+
+ +

If an input h5mu file is also provided, the velocity h5ad object will get added to that h5mu instead.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/convert/velocyto_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input_loom: # please fill in - example: "input.loom"
+# input_h5mu: "input.h5mu"
+modality: "rna_velocity"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+layer_spliced: "velo_spliced"
+layer_unspliced: "velo_unspliced"
+layer_ambiguous: "velo_ambiguous"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/convert/velocyto_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--input_loomPath to the input loom file.file, required, example: "input.loom"
--input_h5muIf a MuData file is provided,file, example: "input.h5mu"
--modalityThe name of the modality to operate on.string, default: "rna_velocity"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputPath to the output MuData file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--layer_splicedOutput layer for the spliced reads.string, default: "velo_spliced"
--layer_unsplicedOutput layer for the unspliced reads.string, default: "velo_unspliced"
--layer_ambiguousOutput layer for the ambiguous reads.string, default: "velo_ambiguous"
+
+
+
+

Authors

+
    +

  • Dries Schaumont (maintainer, author)

    • +

  • Robrecht Cannoodt (author)

    • +

  • Angela Oliveira Pisco (contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/correction/cellbender_remove_background.html b/pr-preview/pr-51/components/modules/correction/cellbender_remove_background.html new file mode 100644 index 00000000..21905ca3 --- /dev/null +++ b/pr-preview/pr-51/components/modules/correction/cellbender_remove_background.html @@ -0,0 +1,1893 @@ + + + + + + + + + + +OpenPipelines - Cellbender remove background + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cellbender remove background

+
+ +
+
+ Eliminating technical artifacts from high-throughput single-cell RNA sequencing data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellbender_remove_background
+Namespace: correction

+
+ +

This module removes counts due to ambient RNA molecules and random barcode swapping from (raw) UMI-based scRNA-seq count matrices. At the moment, only the count matrices produced by the CellRanger count pipeline is supported. Support for additional tools and protocols will be added in the future. A quick start tutorial can be found here.

+

Fleming et al. 2022, bioRxiv.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/correction/cellbender_remove_background/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+layer_output: "cellbender_corrected"
+obs_background_fraction: "cellbender_background_fraction"
+obs_cell_probability: "cellbender_cell_probability"
+obs_cell_size: "cellbender_cell_size"
+obs_droplet_efficiency: "cellbender_droplet_efficiency"
+obs_latent_scale: "cellbender_latent_scale"
+var_ambient_expression: "cellbender_ambient_expression"
+obsm_gene_expression_encoding: "cellbender_gene_expression_encoding"
+
+# Arguments
+expected_cells_from_qc: false
+# expected_cells: 1000
+# total_droplets_included: 25000
+# force_cell_umi_prior: 123
+# force_empty_umi_prior: 123
+model: "full"
+epochs: 150
+low_count_threshold: 5
+z_dim: 64
+z_layers: [512]
+training_fraction: 0.9
+empty_drop_training_fraction: 0.2
+# ignore_features: [123]
+fpr: [0.01]
+# exclude_feature_types: ["foo"]
+projected_ambient_count_threshold: 0.1
+learning_rate: 1.0E-4
+# final_elbo_fail_fraction: 123.0
+# epoch_elbo_fail_fraction: 123.0
+num_training_tries: 1
+learning_rate_retry_mult: 0.2
+posterior_batch_size: 128
+# posterior_regulation: "foo"
+# alpha: 123.0
+# q: 123.0
+estimator: "mckp"
+estimator_multiple_cpu: false
+# constant_learning_rate: true
+debug: false
+cuda: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/correction/cellbender_remove_background/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu file. Data file on which to run tool. Data must be un-filtered: it should include empty droplets.file, required, example: "input.h5mu"
--modalityList of modalities to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputFull count matrix as an h5mu file, with background RNA removed. This file contains all the original droplet barcodes.file, required, example: "output.h5mu"
--output_compressionstring, example: "gzip"
--layer_outputOutput layerstring, default: "cellbender_corrected"
--obs_background_fractionstring, default: "cellbender_background_fraction"
--obs_cell_probabilitystring, default: "cellbender_cell_probability"
--obs_cell_sizestring, default: "cellbender_cell_size"
--obs_droplet_efficiencystring, default: "cellbender_droplet_efficiency"
--obs_latent_scalestring, default: "cellbender_latent_scale"
--var_ambient_expressionstring, default: "cellbender_ambient_expression"
--obsm_gene_expression_encodingstring, default: "cellbender_gene_expression_encoding"
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--expected_cells_from_qcWill use the Cell Ranger QC to determine the estimated number of cellsboolean, default: FALSE
--expected_cellsNumber of cells expected in the dataset (a rough estimate within a factor of 2 is sufficient).integer, example: 1000
--total_droplets_includedThe number of droplets from the rank-ordered UMI plot that will have their cell probabilities inferred as an output. Include the droplets which might contain cells. Droplets beyond TOTAL_DROPLETS_INCLUDED should be ‘surely empty’ droplets.integer, example: 25000
--force_cell_umi_priorIgnore CellBender’s heuristic prior estimation, and use this prior for UMI counts in cells.integer
--force_empty_umi_priorIgnore CellBender’s heuristic prior estimation, and use this prior for UMI counts in empty droplets.integer
--modelWhich model is being used for count data. * ‘naive’ subtracts the estimated ambient profile. * ‘simple’ does not model either ambient RNA or random barcode swapping (for debugging purposes – not recommended). * ‘ambient’ assumes background RNA is incorporated into droplets. * ‘swapping’ assumes background RNA comes from random barcode swapping (via PCR chimeras). * ‘full’ uses a combined ambient and swapping model.string, default: "full"
--epochsNumber of epochs to train.integer, default: 150
--low_count_thresholdDroplets with UMI counts below this number are completely excluded from the analysis. This can help identify the correct prior for empty droplet counts in the rare case where empty counts are extremely high (over 200).integer, default: 5
--z_dimDimension of latent variable z.integer, default: 64
--z_layersDimension of hidden layers in the encoder for z.integer, default: 512
--training_fractionTraining detail: the fraction of the data used for training. The rest is never seen by the inference algorithm. Speeds up learning.double, default: 0.9
--empty_drop_training_fractionTraining detail: the fraction of the training data each epoch that is drawn (randomly sampled) from surely empty droplets.double, default: 0.2
--ignore_featuresInteger indices of features to ignore entirely. In the output count matrix, the counts for these features will be unchanged.integer
--fprTarget ‘delta’ false positive rate in [0, 1). Use 0 for a cohort of samples which will be jointly analyzed for differential expression. A false positive is a true signal count that is erroneously removed. More background removal is accompanied by more signal removal at high values of FPR. You can specify multiple values, which will create multiple output files.double, default: 0.01
--exclude_feature_typesFeature types to ignore during the analysis. These features will be left unchanged in the output file.string
--projected_ambient_count_thresholdControls how many features are included in the analysis, which can lead to a large speedup. If a feature is expected to have less than PROJECTED_AMBIENT_COUNT_THRESHOLD counts total in all cells (summed), then that gene is excluded, and it will be unchanged in the output count matrix. For example, PROJECTED_AMBIENT_COUNT_THRESHOLD = 0 will include all features which have even a single count in any empty droplet.double, default: 0.1
--learning_rateTraining detail: lower learning rate for inference. A OneCycle learning rate schedule is used, where the upper learning rate is ten times this value. (For this value, probably do not exceed 1e-3).double, default: 1e-04
--final_elbo_fail_fractionTraining is considered to have failed if (best_test_ELBO - final_test_ELBO)/(best_test_ELBO - initial_test_ELBO) > FINAL_ELBO_FAIL_FRACTION. Training will automatically re-run if –num-training-tries > 1. By default, will not fail training based on final_training_ELBO.double
--epoch_elbo_fail_fractionTraining is considered to have failed if (previous_epoch_test_ELBO - current_epoch_test_ELBO)/(previous_epoch_test_ELBO - initial_train_ELBO) > EPOCH_ELBO_FAIL_FRACTION. Training will automatically re-run if –num-training-tries > 1. By default, will not fail training based on epoch_training_ELBO.double
--num_training_triesNumber of times to attempt to train the model. At each subsequent attempt, the learning rate is multiplied by LEARNING_RATE_RETRY_MULT.integer, default: 1
--learning_rate_retry_multLearning rate is multiplied by this amount each time a new training attempt is made. (This parameter is only used if training fails based on EPOCH_ELBO_FAIL_FRACTION or FINAL_ELBO_FAIL_FRACTION and NUM_TRAINING_TRIES is > 1.)double, default: 0.2
--posterior_batch_sizeTraining detail: size of batches when creating the posterior. Reduce this to avoid running out of GPU memory creating the posterior (will be slower).integer, default: 128
--posterior_regulationPosterior regularization method. (For experts: not required for normal usage, see documentation). * PRq is approximate quantile-targeting. * PRmu is approximate mean-targeting aggregated over genes (behavior of v0.2.0). * PRmu_gene is approximate mean-targeting per gene.string
--alphaTunable parameter alpha for the PRq posterior regularization method (not normally used: see documentation).double
--qTunable parameter q for the CDF threshold estimation method (not normally used: see documentation).double
--estimatorOutput denoised count estimation method. (For experts: not required for normal usage, see documentation).string, default: "mckp"
--estimator_multiple_cpuIncluding the flag –estimator-multiple-cpu will use more than one CPU to compute the MCKP output count estimator in parallel (does nothing for other estimators).boolean_true
--constant_learning_rateIncluding the flag –constant-learning-rate will use the ClippedAdam optimizer instead of the OneCycleLR learning rate schedule, which is the default. Learning is faster with the OneCycleLR schedule. However, training can easily be continued from a checkpoint for more epochs than the initial command specified when using ClippedAdam. On the other hand, if using the OneCycleLR schedule with 150 epochs specified, it is not possible to pick up from that final checkpoint and continue training until 250 epochs.boolean
--debugIncluding the flag –debug will log extra messages useful for debugging.boolean_true
--cudaIncluding the flag –cuda will run the inference on a GPU.boolean_true
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/correction/cellbender_remove_background_v0_2.html b/pr-preview/pr-51/components/modules/correction/cellbender_remove_background_v0_2.html new file mode 100644 index 00000000..2d507bf9 --- /dev/null +++ b/pr-preview/pr-51/components/modules/correction/cellbender_remove_background_v0_2.html @@ -0,0 +1,1785 @@ + + + + + + + + + + +OpenPipelines - Cellbender remove background v0 2 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cellbender remove background v0 2

+
+ +
+
+ Eliminating technical artifacts from high-throughput single-cell RNA sequencing data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellbender_remove_background_v0_2
+Namespace: correction

+
+ +

This module removes counts due to ambient RNA molecules and random barcode swapping from (raw) UMI-based scRNA-seq count matrices. At the moment, only the count matrices produced by the CellRanger count pipeline is supported. Support for additional tools and protocols will be added in the future. A quick start tutorial can be found here.

+

Fleming et al. 2022, bioRxiv.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/correction/cellbender_remove_background_v0_2/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+layer_output: "corrected"
+obs_latent_rt_efficiency: "latent_rt_efficiency"
+obs_latent_cell_probability: "latent_cell_probability"
+obs_latent_scale: "latent_scale"
+var_ambient_expression: "ambient_expression"
+obsm_latent_gene_encoding: "cellbender_latent_gene_encoding"
+
+# Arguments
+# expected_cells: 1000
+# total_droplets_included: 25000
+expected_cells_from_qc: true
+model: "full"
+epochs: 150
+low_count_threshold: 15
+z_dim: 100
+z_layers: [500]
+training_fraction: 0.9
+empty_drop_training_fraction: 0.5
+fpr: [0.01]
+exclude_antibody_capture: false
+# learning_rate: 1.0E-4
+cuda: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/correction/cellbender_remove_background_v0_2/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu file.file, required, example: "input.h5mu"
--modalityList of modalities to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputFull count matrix as an h5mu file, with background RNA removed. This file contains all the original droplet barcodes.file, required, example: "output.h5mu"
--output_compressionstring, example: "gzip"
--layer_outputOutput layerstring, default: "corrected"
--obs_latent_rt_efficiencystring, default: "latent_rt_efficiency"
--obs_latent_cell_probabilitystring, default: "latent_cell_probability"
--obs_latent_scalestring, default: "latent_scale"
--var_ambient_expressionstring, default: "ambient_expression"
--obsm_latent_gene_encodingstring, default: "cellbender_latent_gene_encoding"
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--expected_cellsNumber of cells expected in the dataset (a rough estimate within a factor of 2 is sufficient).integer, example: 1000
--total_droplets_includedThe number of droplets from the rank-ordered UMI plot that will be analyzed. The largest ‘total_droplets’ droplets will have their cell probabilities inferred as an output.integer, example: 25000
--expected_cells_from_qcWill use the Cell Ranger QC to determine the estimated number of cellsboolean, default: TRUE
--modelWhich model is being used for count data. ‘simple’ does not model either ambient RNA or random barcode swapping (for debugging purposes – not recommended). ‘ambient’ assumes background RNA is incorporated into droplets. ‘swapping’ assumes background RNA comes from random barcode swapping. ‘full’ uses a combined ambient and swapping model.string, default: "full"
--epochsNumber of epochs to train.integer, default: 150
--low_count_thresholdDroplets with UMI counts below this number are completely excluded from the analysis. This can help identify the correct prior for empty droplet counts in the rare case where empty counts are extremely high (over 200).integer, default: 15
--z_dimDimension of latent variable z.integer, default: 100
--z_layersDimension of hidden layers in the encoder for z.integer, default: 500
--training_fractionTraining detail: the fraction of the data used for training. The rest is never seen by the inference algorithm. Speeds up learning.double, default: 0.9
--empty_drop_training_fractionTraining detail: the fraction of the training data each epoch that is drawn (randomly sampled) from surely empty droplets.double, default: 0.5
--fprTarget false positive rate in (0, 1). A false positive is a true signal count that is erroneously removed. More background removal is accompanied by more signal removal at high values of FPR. You can specify multiple values, which will create multiple output files.double, default: 0.01
--exclude_antibody_captureIncluding the flag –exclude-antibody-capture will cause remove-background to operate on gene counts only, ignoring other features.boolean_true
--learning_rateTraining detail: lower learning rate for inference. A OneCycle learning rate schedule is used, where the upper learning rate is ten times this value. (For this value, probably do not exceed 1e-3).double, example: 1e-04
--cudaIncluding the flag –cuda will run the inference on a GPU.boolean_true
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/dataflow/concat.html b/pr-preview/pr-51/components/modules/dataflow/concat.html new file mode 100644 index 00000000..a81bec69 --- /dev/null +++ b/pr-preview/pr-51/components/modules/dataflow/concat.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Concat + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Concat

+
+ +
+
+ Concatenates several uni-modal samples in .h5mu files into a single file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: concat
+Namespace: dataflow

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/dataflow/concat/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: ["sample_paths"]
+# input_id: ["foo"]
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+obs_sample_name: "sample_id"
+other_axis_mode: "move"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/dataflow/concat/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPaths to the different samples to be concatenated.file, required, example: "sample_paths"
--input_idNames of the different samples that have to be concatenated. Must be specified when using ‘–mode move’. In this case, the ids will be used for the columns names of the dataframes registring the conflicts. If specified, must be of same length as --input.string
--outputfile, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--obs_sample_nameName of the .obs key under which to add the sample names.string, default: "sample_id"
--other_axis_modeHow to handle the merging of other axis (var, obs, …). - None: keep no data - same: only keep elements of the matrices which are the same in each of the samples - unique: only keep elements for which there is only 1 possible value (1 value that can occur in multiple samples) - first: keep the annotation from the first sample - only: keep elements that show up in only one of the objects (1 unique element in only 1 sample) - move: identical to ‘same’, but moving the conflicting values to .varm or .obsmstring, default: "move"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/dataflow/merge.html b/pr-preview/pr-51/components/modules/dataflow/merge.html new file mode 100644 index 00000000..c983a365 --- /dev/null +++ b/pr-preview/pr-51/components/modules/dataflow/merge.html @@ -0,0 +1,1623 @@ + + + + + + + + + + +OpenPipelines - Merge + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Merge

+
+ +
+
+ Combine one or more single-modality .h5mu files together into one .h5mu file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: merge
+Namespace: dataflow

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/dataflow/merge/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: ["sample_paths"]
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/dataflow/merge/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPaths to the single-modality .h5mu files that need to be combinedfile, required, default: "sample_paths"
--outputPath to the output file.file, default: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/dataflow/split_modalities.html b/pr-preview/pr-51/components/modules/dataflow/split_modalities.html new file mode 100644 index 00000000..9f53c767 --- /dev/null +++ b/pr-preview/pr-51/components/modules/dataflow/split_modalities.html @@ -0,0 +1,1636 @@ + + + + + + + + + + +OpenPipelines - Split modalities + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Split modalities

+
+ +
+
+ Split the modalities from a single .h5mu multimodal sample into seperate .h5mu files. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: split_modalities
+Namespace: dataflow

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/dataflow/split_modalities/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "sample_path"
+# output: "$id.$key.output.output"
+# output_compression: "gzip"
+# output_types: "$id.$key.output_types.csv"
+compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/dataflow/split_modalities/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to a single .h5mu file.file, required, default: "sample_path"
--outputOutput directory containing multiple h5mu files.file, required, example: "/path/to/output"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--output_typesA csv containing the base filename and modality type per output file.file, required, example: "types.csv"
--compressionThe compression format to be used on the final h5mu object.string, default: "gzip"
+
+
+
+

Authors

+
    +

  • Dries Schaumont (maintainer)

    • +

  • Robrecht Cannoodt (contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/demux/bcl2fastq.html b/pr-preview/pr-51/components/modules/demux/bcl2fastq.html new file mode 100644 index 00000000..2b952e08 --- /dev/null +++ b/pr-preview/pr-51/components/modules/demux/bcl2fastq.html @@ -0,0 +1,1635 @@ + + + + + + + + + + +OpenPipelines - Bcl2fastq + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Bcl2fastq

+
+ +
+
+ Convert bcl files to fastq files using bcl2fastq +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: bcl2fastq
+Namespace: demux

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/demux/bcl2fastq/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "bcl_dir"
+sample_sheet: # please fill in - example: "SampleSheet.csv"
+# output: "$id.$key.output.output"
+# reports: "$id.$key.reports.reports"
+ignore_missing: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/demux/bcl2fastq/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput run directoryfile, required, example: "bcl_dir"
--sample_sheetPointer to the sample sheetfile, required, example: "SampleSheet.csv"
--outputOutput directory containig fastq filesfile, required, example: "fastq_dir"
--reportsReports directoryfile, example: "reports_dir"
--ignore_missingboolean_true
+
+
+
+

Authors

+
    +
  • Toni Verbeiren (author, maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/demux/bcl_convert.html b/pr-preview/pr-51/components/modules/demux/bcl_convert.html new file mode 100644 index 00000000..cf6e17f6 --- /dev/null +++ b/pr-preview/pr-51/components/modules/demux/bcl_convert.html @@ -0,0 +1,1637 @@ + + + + + + + + + + +OpenPipelines - Bcl convert + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Bcl convert

+
+ +
+
+ Convert bcl files to fastq files using bcl-convert. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: bcl_convert
+Namespace: demux

+
+ +

Information about upgrading from bcl2fastq via https://emea.support.illumina.com/bulletins/2020/10/upgrading-from-bcl2fastq-to-bcl-convert.html and https://support.illumina.com/sequencing/sequencing_software/bcl-convert/compatibility.html

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/demux/bcl_convert/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "bcl_dir"
+sample_sheet: # please fill in - example: "bcl_dir"
+# output: "$id.$key.output.output"
+# reports: "$id.$key.reports.reports"
+test_mode: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/demux/bcl_convert/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput run directoryfile, required, example: "bcl_dir"
--sample_sheetPointer to the sample sheetfile, required, example: "bcl_dir"
--outputOutput directory containig fastq filesfile, required, example: "fastq_dir"
--reportsReports directoryfile, example: "reports_dir"
--test_modeShould bcl-convert be run in test mode (using –first-tile-only)?boolean, default: FALSE
+
+
+
+

Authors

+
    +

  • Toni Verbeiren (author, maintainer)

    • +

  • Marijke Van Moerbeke (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/demux/cellranger_mkfastq.html b/pr-preview/pr-51/components/modules/demux/cellranger_mkfastq.html new file mode 100644 index 00000000..1b31bb75 --- /dev/null +++ b/pr-preview/pr-51/components/modules/demux/cellranger_mkfastq.html @@ -0,0 +1,1631 @@ + + + + + + + + + + +OpenPipelines - Cellranger mkfastq + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cellranger mkfastq

+
+ +
+
+ Demultiplex raw sequencing data +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellranger_mkfastq
+Namespace: demux

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/demux/cellranger_mkfastq/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "/path/to/bcl"
+sample_sheet: # please fill in - example: "SampleSheet.csv"
+# output: "$id.$key.output.output"
+# reports: "$id.$key.reports.reports"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/demux/cellranger_mkfastq/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to the (untarred) BCL files. Expects ‘RunParameters.xml’ at ‘./’.file, required, example: "/path/to/bcl"
--sample_sheetThe path to the sample sheet.file, required, example: "SampleSheet.csv"
--outputThe folder to store the demux resultsfile, required, default: "fastqs", example: "/path/to/output"
--reportsReports directoryfile, example: "reports_dir"
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Samuel D’Souza (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/dimred/pca.html b/pr-preview/pr-51/components/modules/dimred/pca.html new file mode 100644 index 00000000..4ef3e583 --- /dev/null +++ b/pr-preview/pr-51/components/modules/dimred/pca.html @@ -0,0 +1,1672 @@ + + + + + + + + + + +OpenPipelines - Pca + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Pca

+
+ +
+
+ Computes PCA coordinates, loadings and variance decomposition. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: pca
+Namespace: dimred

+
+ +

Uses the implementation of scikit-learn [Pedregosa11]

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/dimred/pca/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# layer: "foo"
+# var_input: "filter_with_hvg"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+obsm_output: "X_pca"
+varm_output: "pca_loadings"
+uns_output: "pca_variance"
+# num_components: 25
+overwrite: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/dimred/pca/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--layerUse specified layer for expression values instead of the .X object from the modality.string
--var_inputColumn name in .var matrix that will be used to select which genes to run the PCA on.string, example: "filter_with_hvg"
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--obsm_outputIn which .obsm slot to store the resulting embedding.string, default: "X_pca"
--varm_outputIn which .varm slot to store the resulting loadings matrix.string, default: "pca_loadings"
--uns_outputIn which .uns slot to store the resulting variance objects.string, default: "pca_variance"
--num_componentsNumber of principal components to compute. Defaults to 50, or 1 - minimum dimension size of selected representation.integer, example: 25
--overwriteAllow overwriting .obsm, .varm and .uns slots.boolean_true
+
+
+
+

Authors

+
    +
  • Dries De Maeyer (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/dimred/umap.html b/pr-preview/pr-51/components/modules/dimred/umap.html new file mode 100644 index 00000000..db5ec53d --- /dev/null +++ b/pr-preview/pr-51/components/modules/dimred/umap.html @@ -0,0 +1,1732 @@ + + + + + + + + + + +OpenPipelines - Umap + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Umap

+
+ +
+
+ UMAP (Uniform Manifold Approximation and Projection) is a manifold learning technique suitable for visualizing high-dimensional data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: umap
+Namespace: dimred

+
+ +

Besides tending to be faster than tSNE, it optimizes the embedding such that it best reflects the topology of the data, which we represent throughout Scanpy using a neighborhood graph. tSNE, by contrast, optimizes the distribution of nearest-neighbor distances in the embedding such that these best match the distribution of distances in the high-dimensional space. We use the implementation of umap-learn [McInnes18]. For a few comparisons of UMAP with tSNE, see this preprint

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/dimred/umap/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+uns_neighbors: "neighbors"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+obsm_output: "umap"
+
+# Arguments
+min_dist: 0.5
+spread: 1.0
+num_components: 2
+# max_iter: 123
+alpha: 1.0
+gamma: 1.0
+negative_sample_rate: 5
+init_pos: "spectral"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/dimred/umap/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--uns_neighborsThe .uns neighbors slot as output by the find_neighbors component.string, default: "neighbors"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--obsm_outputThe pre/postfix under which to store the UMAP results.string, default: "umap"
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--min_distThe effective minimum distance between embedded points. Smaller values will result in a more clustered/clumped embedding where nearby points on the manifold are drawn closer together, while larger values will result on a more even dispersal of points. The value should be set relative to the spread value, which determines the scale at which embedded points will be spread out.double, default: 0.5
--spreadThe effective scale of embedded points. In combination with min_dist this determines how clustered/clumped the embedded points are.double, default: 1
--num_componentsThe number of dimensions of the embedding.integer, default: 2
--max_iterThe number of iterations (epochs) of the optimization. Called n_epochs in the original UMAP. Default is set to 500 if neighbors[‘connectivities’].shape[0] <= 10000, else 200.integer
--alphaThe initial learning rate for the embedding optimization.double, default: 1
--gammaWeighting applied to negative samples in low dimensional embedding optimization. Values higher than one will result in greater weight being given to negative samples.double, default: 1
--negative_sample_rateThe number of negative edge/1-simplex samples to use per positive edge/1-simplex sample in optimizing the low dimensional embedding.integer, default: 5
--init_posHow to initialize the low dimensional embedding. Called init in the original UMAP. Options are: * Any key from .obsm * 'paga': positions from paga() * 'spectral': use a spectral embedding of the graph * 'random': assign initial embedding positions at random.string, default: "spectral"
+
+
+
+

Authors

+
    +
  • Dries De Maeyer (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/download/download_file.html b/pr-preview/pr-51/components/modules/download/download_file.html new file mode 100644 index 00000000..ed5759f6 --- /dev/null +++ b/pr-preview/pr-51/components/modules/download/download_file.html @@ -0,0 +1,1623 @@ + + + + + + + + + + +OpenPipelines - Download file + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Download file

+
+ +
+
+ Download a file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: download_file
+Namespace: download

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/download/download_file/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "https://cf.10xgenomics.com/samples/cell-exp/3.0.0/pbmc_1k_protein_v3/pbmc_1k_protein_v3_raw_feature_bc_matrix.h5"
+# output: "$id.$key.output.h5"
+verbose: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/download/download_file/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputURL to a file to download.string, required, example: "https://cf.10xgenomics.com/samples/cell-exp/3.0.0/pbmc_1k_protein_v3/pbmc_1k_protein_v3_raw_feature_bc_matrix.h5"
--outputPath where to store output.file, required, example: "pbmc_1k_protein_v3_raw_feature_bc_matrix.h5"
--verboseIncrease verbosityboolean_true
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/download/sync_test_resources.html b/pr-preview/pr-51/components/modules/download/sync_test_resources.html new file mode 100644 index 00000000..59c103ec --- /dev/null +++ b/pr-preview/pr-51/components/modules/download/sync_test_resources.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Sync test resources + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Sync test resources

+
+ +
+
+ Synchronise the test resources from s3://openpipelines-data to resources_test +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: sync_test_resources
+Namespace: download

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/download/sync_test_resources/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: "s3://openpipelines-data"
+# output: "$id.$key.output.output"
+quiet: false
+dryrun: false
+delete: false
+# exclude: ["foo"]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/download/sync_test_resources/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to the S3 bucket to sync from.string, default: "s3://openpipelines-data"
--outputPath to the test resource directory.file, default: "resources_test"
--quietDisplays the operations that would be performed using the specified command without actually running them.boolean_true
--dryrunDoes not display the operations performed from the specified command.boolean_true
--deleteFiles that exist in the destination but not in the source are deleted during sync.boolean_true
--excludeExclude all files or objects from the command that matches the specified pattern.string
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/files/make_params.html b/pr-preview/pr-51/components/modules/files/make_params.html new file mode 100644 index 00000000..e1cb2f77 --- /dev/null +++ b/pr-preview/pr-51/components/modules/files/make_params.html @@ -0,0 +1,1654 @@ + + + + + + + + + + +OpenPipelines - Make params + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Make params

+
+ +
+
+ Looks for files in a directory and turn it in a params file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: make_params
+Namespace: files

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/files/make_params/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+base_dir: # please fill in - example: "/path/to/dir"
+pattern: # please fill in - example: "*.fastq.gz"
+n_dirname_drop: 0
+n_basename_id: 0
+id_name: "id"
+path_name: "path"
+# group_name: "param_list"
+# output: "$id.$key.output.yaml"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/files/make_params/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--base_dirBase directory to search recursivelyfile, required, example: "/path/to/dir"
--patternAn optional regular expression. Only file names which match the regular expression will be matched.string, required, example: "*.fastq.gz"
--n_dirname_dropFor every matched file, the parent directory will be traversed N times.integer, default: 0
--n_basename_idThe unique identifiers will consist of at least N dirnames.integer, default: 0
--id_nameThe name for storing the identifier field in the yaml.string, default: "id"
--path_nameThe name for storing the path field in the yaml.string, default: "path"
--group_nameTop level name for the group of entries.string, example: "param_list"
--outputOutput YAML file.file, required, example: "params.yaml"
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (maintainer, author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/filter/do_filter.html b/pr-preview/pr-51/components/modules/filter/do_filter.html new file mode 100644 index 00000000..27ed3dd1 --- /dev/null +++ b/pr-preview/pr-51/components/modules/filter/do_filter.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Do filter + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Do filter

+
+ +
+
+ Remove observations and variables based on specified .obs and .var columns +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: do_filter
+Namespace: filter

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/filter/do_filter/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# obs_filter: ["filter_with_x"]
+# var_filter: ["filter_with_x"]
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/filter/do_filter/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--obs_filterWhich .obs columns to use to filter the observations by.string, example: "filter_with_x"
--var_filterWhich .var columns to use to filter the observations by.string, example: "filter_with_x"
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer, contributor)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/filter/filter_with_counts.html b/pr-preview/pr-51/components/modules/filter/filter_with_counts.html new file mode 100644 index 00000000..a9a3f05c --- /dev/null +++ b/pr-preview/pr-51/components/modules/filter/filter_with_counts.html @@ -0,0 +1,1757 @@ + + + + + + + + + + +OpenPipelines - Filter with counts + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Filter with counts

+
+ +
+
+ Filter scRNA-seq data based on the primary QC metrics. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: filter_with_counts
+Namespace: filter

+
+ +

This is based on both the UMI counts, the gene counts and the mitochondrial genes (genes starting with mt/MT)

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/filter/filter_with_counts/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# layer: "raw_counts"
+# var_gene_names: "gene_symbol"
+mitochondrial_gene_regex: "^[mM][tT]-"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+do_subset: false
+obs_name_filter: "filter_with_counts"
+var_name_filter: "filter_with_counts"
+# var_name_mitochondrial_genes: "foo"
+
+# Arguments
+# min_counts: 200
+# max_counts: 5000000
+# min_genes_per_cell: 200
+# max_genes_per_cell: 1500000
+# min_cells_per_gene: 3
+# min_fraction_mito: 0
+# max_fraction_mito: 0.2
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/filter/filter_with_counts/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--layerstring, example: "raw_counts"
--var_gene_names.var column name to be used to detect mitochondrial genes instead of .var_names (default if not set). Gene names matching with the regex value from –mitochondrial_gene_regex will be identified as a mitochondrial gene.string, example: "gene_symbol"
--mitochondrial_gene_regexRegex string that identifies mitochondrial genes from –var_gene_names. By default will detect human and mouse mitochondrial genes from a gene symbol.string, default: "^[mM][tT]-"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--do_subsetWhether to subset before storing the output.boolean_true
--obs_name_filterIn which .obs slot to store a boolean array corresponding to which observations should be removed.string, default: "filter_with_counts"
--var_name_filterIn which .var slot to store a boolean array corresponding to which variables should be removed.string, default: "filter_with_counts"
--var_name_mitochondrial_genesIn which .var slot to store a boolean array corresponding the mitochondrial genes. Will only be used if –min_fraction_mito or –max_fraction_mito are specified.string
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--min_countsMinimum number of counts captured per cell.integer, example: 200
--max_countsMaximum number of counts captured per cell.integer, example: 5000000
--min_genes_per_cellMinimum of non-zero values per cell.integer, example: 200
--max_genes_per_cellMaximum of non-zero values per cell.integer, example: 1500000
--min_cells_per_geneMinimum of non-zero values per gene.integer, example: 3
--min_fraction_mitoMinimum fraction of UMIs that are mitochondrial.double, example: 0
--max_fraction_mitoMaximum fraction of UMIs that are mitochondrial.double, example: 0.2
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (author)

    • +

  • Robrecht Cannoodt (maintainer, author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/filter/filter_with_hvg.html b/pr-preview/pr-51/components/modules/filter/filter_with_hvg.html new file mode 100644 index 00000000..b960c3d3 --- /dev/null +++ b/pr-preview/pr-51/components/modules/filter/filter_with_hvg.html @@ -0,0 +1,1712 @@ + + + + + + + + + + +OpenPipelines - Filter with hvg + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Filter with hvg

+
+ +
+
+ Annotate highly variable genes [Satija15] [Zheng17] [Stuart19]. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: filter_with_hvg
+Namespace: filter

+
+ +

Expects logarithmized data, except when flavor=‘seurat_v3’ in which count data is expected.

+

Depending on flavor, this reproduces the R-implementations of Seurat [Satija15], Cell Ranger [Zheng17], and Seurat v3 [Stuart19].

+

For the dispersion-based methods ([Satija15] and [Zheng17]), the normalized dispersion is obtained by scaling with the mean and standard deviation of the dispersions for genes falling into a given bin for mean expression of genes. This means that for each bin of mean expression, highly variable genes are selected.

+

For [Stuart19], a normalized variance for each gene is computed. First, the data are standardized (i.e., z-score normalization per feature) with a regularized standard deviation. Next, the normalized variance is computed as the variance of each gene after the transformation. Genes are ranked by the normalized variance.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/filter/filter_with_hvg/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# layer: "foo"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+var_name_filter: "filter_with_hvg"
+varm_name: "hvg"
+do_subset: false
+flavor: "seurat"
+# n_top_genes: 123
+min_mean: 0.0125
+max_mean: 3
+min_disp: 0.5
+# max_disp: 123.0
+span: 0.3
+n_bins: 20
+# obs_batch_key: "foo"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/filter/filter_with_hvg/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--layeruse adata.layers[layer] for expression values instead of adata.X.string
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--var_name_filterIn which .var slot to store a boolean array corresponding to which observations should be filtered out.string, default: "filter_with_hvg"
--varm_nameIn which .varm slot to store additional metadata.string, default: "hvg"
--do_subsetWhether to subset before storing the output.boolean_true
--flavorChoose the flavor for identifying highly variable genes. For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_genes.string, default: "seurat"
--n_top_genesNumber of highly-variable genes to keep. Mandatory if flavor=‘seurat_v3’.integer
--min_meanIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’.double, default: 0.0125
--max_meanIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’.double, default: 3
--min_dispIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’.double, default: 0.5
--max_dispIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’. Default is +inf.double
--spanThe fraction of the data (cells) used when estimating the variance in the loess model fit if flavor=‘seurat_v3’.double, default: 0.3
--n_binsNumber of bins for binning the mean gene expression. Normalization is done with respect to each bin. If just a single gene falls into a bin, the normalized dispersion is artificially set to 1.integer, default: 20
--obs_batch_keyIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method. For all flavors, genes are first sorted by how many batches they are a HVG. For dispersion-based flavors ties are broken by normalized dispersion. If flavor = ‘seurat_v3’, ties are broken by the median (across batches) rank based on within-batch normalized variance.string
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (contributor)

    • +

  • Robrecht Cannoodt (maintainer, contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/filter/filter_with_scrublet.html b/pr-preview/pr-51/components/modules/filter/filter_with_scrublet.html new file mode 100644 index 00000000..913056dd --- /dev/null +++ b/pr-preview/pr-51/components/modules/filter/filter_with_scrublet.html @@ -0,0 +1,1687 @@ + + + + + + + + + + +OpenPipelines - Filter with scrublet + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Filter with scrublet

+
+ +
+
+ Doublet detection using the Scrublet method (Wolock, Lopez and Klein, 2019). +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: filter_with_scrublet
+Namespace: filter

+
+ +

The method tests for potential doublets by using the expression profiles of cells to generate synthetic potential doubles which are tested against cells. The method returns a “doublet score” on which it calls for potential doublets.

+

For the source code please visit https://github.com/AllonKleinLab/scrublet.

+

For 10x we expect the doublet rates to be: Multiplet Rate (%) - # of Cells Loaded - # of Cells Recovered ~0.4% ~800 ~500 ~0.8% ~1,600 ~1,000 ~1.6% ~3,200 ~2,000 ~2.3% ~4,800 ~3,000 ~3.1% ~6,400 ~4,000 ~3.9% ~8,000 ~5,000 ~4.6% ~9,600 ~6,000 ~5.4% ~11,200 ~7,000 ~6.1% ~12,800 ~8,000 ~6.9% ~14,400 ~9,000 ~7.6% ~16,000 ~10,000

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/filter/filter_with_scrublet/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+obs_name_filter: "filter_with_scrublet"
+do_subset: false
+obs_name_doublet_score: "scrublet_doublet_score"
+min_counts: 2
+min_cells: 3
+min_gene_variablity_percent: 85
+num_pca_components: 30
+distance_metric: "euclidean"
+allow_automatic_threshold_detection_fail: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/filter/filter_with_scrublet/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--obs_name_filterIn which .obs slot to store a boolean array corresponding to which observations should be filtered out.string, default: "filter_with_scrublet"
--do_subsetWhether to subset before storing the output.boolean_true
--obs_name_doublet_scoreName of the doublet scores column in the obs slot of the returned object.string, default: "scrublet_doublet_score"
--min_countsThe number of minimal UMI counts per cell that have to be present for initial cell detection.integer, default: 2
--min_cellsThe number of cells in which UMIs for a gene were detected.integer, default: 3
--min_gene_variablity_percentUsed for gene filtering prior to PCA. Keep the most highly variable genes (in the top min_gene_variability_pctl percentile), as measured by the v-statistic [Klein et al., Cell 2015].double, default: 85
--num_pca_componentsNumber of principal components to use during PCA dimensionality reduction.integer, default: 30
--distance_metricThe distance metric used for computing similarities.string, default: "euclidean"
--allow_automatic_threshold_detection_failWhen scrublet fails to automatically determine the double score threshold, allow the component to continue and set the output columns to NA.boolean_true
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (contributor)

    • +

  • Robrecht Cannoodt (maintainer, contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/filter/remove_modality.html b/pr-preview/pr-51/components/modules/filter/remove_modality.html new file mode 100644 index 00000000..f73148e1 --- /dev/null +++ b/pr-preview/pr-51/components/modules/filter/remove_modality.html @@ -0,0 +1,1629 @@ + + + + + + + + + + +OpenPipelines - Remove modality + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Remove modality

+
+ +
+
+ Remove a modality from a .h5mu file +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: remove_modality
+Namespace: filter

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/filter/remove_modality/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: # please fill in - example: ["foo"]
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/filter/remove_modality/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, required
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/filter/subset_h5mu.html b/pr-preview/pr-51/components/modules/filter/subset_h5mu.html new file mode 100644 index 00000000..11af00e4 --- /dev/null +++ b/pr-preview/pr-51/components/modules/filter/subset_h5mu.html @@ -0,0 +1,1635 @@ + + + + + + + + + + +OpenPipelines - Subset h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Subset h5mu

+
+ +
+
+ Create a subset of a mudata file by selecting the first number of observations +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: subset_h5mu
+Namespace: filter

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/filter/subset_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+# number_of_observations: 5
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/filter/subset_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--number_of_observationsNumber of observations to be selected from the h5mu file.integer, example: 5
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/index.html b/pr-preview/pr-51/components/modules/index.html new file mode 100644 index 00000000..14ecc03a --- /dev/null +++ b/pr-preview/pr-51/components/modules/index.html @@ -0,0 +1,1482 @@ + + + + + + + + + +OpenPipelines - Modules + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Modules

+
+ + + +
+ + + + +
+ + +
+ + + + +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/integrate/harmonypy.html b/pr-preview/pr-51/components/modules/integrate/harmonypy.html new file mode 100644 index 00000000..7d1f3f7c --- /dev/null +++ b/pr-preview/pr-51/components/modules/integrate/harmonypy.html @@ -0,0 +1,1655 @@ + + + + + + + + + + +OpenPipelines - Harmonypy + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Harmonypy

+
+ +
+
+ Performs Harmony integration based as described in https://github.com/immunogenomics/harmony. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: harmonypy
+Namespace: integrate

+
+ +

Based on an implementation in python from https://github.com/slowkow/harmonypy

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/integrate/harmonypy/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "path/to/file"
+# output: "$id.$key.output.output"
+# output_compression: "gzip"
+modality: "rna"
+obsm_input: "X_pca"
+obsm_output: "X_pca_integrated"
+theta: [2]
+obs_covariates: # please fill in - example: ["batch", "sample"]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/integrate/harmonypy/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required
--outputOutput h5mu file.file, required
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--modalitystring, default: "rna"
--obsm_inputWhich .obsm slot to use as a starting PCA embedding.string, default: "X_pca"
--obsm_outputIn which .obsm slot to store the resulting integrated embedding.string, default: "X_pca_integrated"
--thetaDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.double, default: 2
--obs_covariatesThe .obs field(s) that define the covariate(s) to regress out.string, required, example: "batch", example: "sample"
+
+
+
+

Authors

+
    +

  • Dries Schaumont (maintainer)

    • +

  • Robrecht Cannoodt (contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/integrate/scanorama.html b/pr-preview/pr-51/components/modules/integrate/scanorama.html new file mode 100644 index 00000000..5783470b --- /dev/null +++ b/pr-preview/pr-51/components/modules/integrate/scanorama.html @@ -0,0 +1,1678 @@ + + + + + + + + + + +OpenPipelines - Scanorama + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scanorama

+
+ +
+
+ Use Scanorama to integrate different experiments +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scanorama
+Namespace: integrate

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/integrate/scanorama/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "path/to/file"
+modality: "rna"
+# output: "$id.$key.output.h5ad"
+# output_compression: "gzip"
+obs_batch: "batch"
+obsm_input: "X_pca"
+obsm_output: "X_scanorama"
+knn: 20
+batch_size: 5000
+sigma: 15
+approx: true
+alpha: 0.1
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/integrate/scanorama/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required
--modalitystring, default: "rna"
--outputOutput .h5mu filefile, required, default: "output.h5ad"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--obs_batchColumn name discriminating between your batches.string, default: "batch"
--obsm_inputBasis obsm slot to run scanorama on.string, default: "X_pca"
--obsm_outputThe name of the field in adata.obsm where the integrated embeddings will be stored after running this function. Defaults to X_scanorama.string, default: "X_scanorama"
--knnNumber of nearest neighbors to use for matching.integer, default: 20
--batch_sizeThe batch size used in the alignment vector computation. Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory.integer, default: 5000
--sigmaCorrection smoothing parameter on Gaussian kernel.double, default: 15
--approxUse approximate nearest neighbors with Python annoy; greatly speeds up matching runtime.boolean, default: TRUE
--alphaAlignment score minimum cutoffdouble, default: 0.1
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (author)

    • +

  • Dries Schaumont (maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/integrate/scarches.html b/pr-preview/pr-51/components/modules/integrate/scarches.html new file mode 100644 index 00000000..0ad6cf84 --- /dev/null +++ b/pr-preview/pr-51/components/modules/integrate/scarches.html @@ -0,0 +1,1764 @@ + + + + + + + + + + +OpenPipelines - Scarches + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scarches

+
+ +
+
+ Performs reference mapping with scArches +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scarches
+Namespace: integrate

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/integrate/scarches/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "path/to/file"
+modality: "rna"
+reference: # please fill in - example: "path/to/file"
+dataset_name: "test_dataset"
+
+# Outputs
+# output: "$id.$key.output.output"
+# output_compression: "gzip"
+# model_output: "$id.$key.model_output.model_output"
+obsm_output: "X_integrated_scanvi"
+
+# Early stopping arguments
+# early_stopping: true
+early_stopping_monitor: "elbo_validation"
+early_stopping_patience: 45
+early_stopping_min_delta: 0.0
+
+# Learning parameters
+max_epochs: # please fill in - example: 123
+reduce_lr_on_plateau: true
+lr_factor: 0.6
+lr_patience: 30
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/integrate/scarches/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu file to use as a queryfile, required
--modalitystring, default: "rna"
--referencePath to the directory with reference model or a web link. For HLCA use https://zenodo.org/record/6337966/files/HLCA_reference_model.zipfile, required
--dataset_nameName of query dataset to use as a batch name. If not set, name of the input file is usedstring, default: "test_dataset"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--model_outputOutput directory for modelfile, default: "model"
--obsm_outputIn which .obsm slot to store the resulting integrated embedding.string, default: "X_integrated_scanvi"
+
+
+

Early stopping arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--early_stoppingWhether to perform early stopping with respect to the validation set.boolean
--early_stopping_monitorMetric logged during validation set epoch.string, default: "elbo_validation"
--early_stopping_patienceNumber of validation epochs with no improvement after which training will be stopped.integer, default: 45
--early_stopping_min_deltaMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.double, default: 0
+
+
+

Learning parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--max_epochsNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.integer, required
--reduce_lr_on_plateauWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.boolean, default: TRUE
--lr_factorFactor to reduce learning rate.double, default: 0.6
--lr_patienceNumber of epochs with no improvement after which learning rate will be reduced.double, default: 30
+
+
+
+

Authors

+
    +
  • Vladimir Shitov
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/integrate/scvi.html b/pr-preview/pr-51/components/modules/integrate/scvi.html new file mode 100644 index 00000000..f8fb0076 --- /dev/null +++ b/pr-preview/pr-51/components/modules/integrate/scvi.html @@ -0,0 +1,1937 @@ + + + + + + + + + + +OpenPipelines - Scvi + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scvi

+
+ +
+
+ Performs scvi integration as done in the human lung cell atlas https://github.com/LungCellAtlas/HLCA +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scvi
+Namespace: integrate

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/integrate/scvi/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "path/to/file"
+modality: "rna"
+# input_layer: "foo"
+obs_batch: "sample_id"
+# var_input: "foo"
+# obs_labels: "foo"
+# obs_size_factor: "foo"
+# obs_categorical_covariate: ["foo"]
+# obs_continuous_covariate: ["foo"]
+
+# Outputs
+# output: "$id.$key.output.output"
+# model_output: "$id.$key.model_output.model_output"
+# output_compression: "gzip"
+obsm_output: "X_scvi_integrated"
+
+# SCVI options
+n_hidden_nodes: 128
+n_dimensions_latent_space: 30
+n_hidden_layers: 2
+dropout_rate: 0.1
+dispersion: "gene"
+gene_likelihood: "nb"
+
+# Variational auto-encoder model options
+use_layer_normalization: "both"
+use_batch_normalization: "none"
+encode_covariates: true
+deeply_inject_covariates: false
+use_observed_lib_size: false
+
+# Early stopping arguments
+# early_stopping: true
+early_stopping_monitor: "elbo_validation"
+early_stopping_patience: 45
+early_stopping_min_delta: 0.0
+
+# Learning parameters
+# max_epochs: 123
+reduce_lr_on_plateau: true
+lr_factor: 0.6
+lr_patience: 30
+
+# Data validition
+n_obs_min_count: 0
+n_var_min_count: 0
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/integrate/scvi/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required
--modalitystring, default: "rna"
--input_layerInput layer to use. If None, X is usedstring
--obs_batchColumn name discriminating between your batches.string, default: "sample_id"
--var_input.var column containing highly variable genes. By default, do not subset genes.string
--obs_labelsKey in adata.obs for label information. Categories will automatically be converted into integer categories and saved to adata.obs[’_scvi_labels’]. If None, assigns the same label to all the data.string
--obs_size_factorKey in adata.obs for size factor information. Instead of using library size as a size factor, the provided size factor column will be used as offset in the mean of the likelihood. Assumed to be on linear scale.string
--obs_categorical_covariateKeys in adata.obs that correspond to categorical data. These covariates can be added in addition to the batch covariate and are also treated as nuisance factors (i.e., the model tries to minimize their effects on the latent space). Thus, these should not be used for biologically-relevant factors that you do not want to correct for.string
--obs_continuous_covariateKeys in adata.obs that correspond to continuous data. These covariates can be added in addition to the batch covariate and are also treated as nuisance factors (i.e., the model tries to minimize their effects on the latent space). Thus, these should not be used for biologically-relevant factors that you do not want to correct for.string
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required
--model_outputFolder where the state of the trained model will be saved to.file
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--obsm_outputIn which .obsm slot to store the resulting integrated embedding.string, default: "X_scvi_integrated"
+
+
+

SCVI options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--n_hidden_nodesNumber of nodes per hidden layer.integer, default: 128
--n_dimensions_latent_spaceDimensionality of the latent space.integer, default: 30
--n_hidden_layersNumber of hidden layers used for encoder and decoder neural-networks.integer, default: 2
--dropout_rateDropout rate for the neural networks.double, default: 0.1
--dispersionSet the behavior for the dispersion for negative binomial distributions: - gene: dispersion parameter of negative binomial is constant per gene across cells - gene-batch: dispersion can differ between different batches - gene-label: dispersion can differ between different labels - gene-cell: dispersion can differ for every gene in every cellstring, default: "gene"
--gene_likelihoodModel used to generate the expression data from a count-based likelihood distribution. - nb: Negative binomial distribution - zinb: Zero-inflated negative binomial distribution - poisson: Poisson distributionstring, default: "nb"
+
+
+

Variational auto-encoder model options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--use_layer_normalizationNeural networks for which to enable layer normalization.string, default: "both"
--use_batch_normalizationNeural networks for which to enable batch normalization.string, default: "none"
--encode_covariatesWhether to concatenate covariates to expression in encoderboolean_false
--deeply_inject_covariatesWhether to concatenate covariates into output of hidden layers in encoder/decoder. This option only applies when n_layers > 1. The covariates are concatenated to the input of subsequent hidden layers.boolean_true
--use_observed_lib_sizeUse observed library size for RNA as scaling factor in mean of conditional distribution.boolean_true
+
+
+

Early stopping arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--early_stoppingWhether to perform early stopping with respect to the validation set.boolean
--early_stopping_monitorMetric logged during validation set epoch.string, default: "elbo_validation"
--early_stopping_patienceNumber of validation epochs with no improvement after which training will be stopped.integer, default: 45
--early_stopping_min_deltaMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.double, default: 0
+
+
+

Learning parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--max_epochsNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.integer
--reduce_lr_on_plateauWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.boolean, default: TRUE
--lr_factorFactor to reduce learning rate.double, default: 0.6
--lr_patienceNumber of epochs with no improvement after which learning rate will be reduced.double, default: 30
+
+
+

Data validition

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--n_obs_min_countMinimum number of cells threshold ensuring that every obs_batch category has sufficient observations (cells) for model training.integer, default: 0
--n_var_min_countMinimum number of genes threshold ensuring that every var_input filter has sufficient observations (genes) for model training.integer, default: 0
+
+
+
+

Authors

+
    +

  • Malte D. Luecken (author)

    • +

  • Dries Schaumont (maintainer)

    • +

  • Matthias Beyens (contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/integrate/totalvi.html b/pr-preview/pr-51/components/modules/integrate/totalvi.html new file mode 100644 index 00000000..9c557206 --- /dev/null +++ b/pr-preview/pr-51/components/modules/integrate/totalvi.html @@ -0,0 +1,1761 @@ + + + + + + + + + + +OpenPipelines - Totalvi + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Totalvi

+
+ +
+
+ Performs mapping to the reference by totalvi model: https://docs.scvi-tools.org/en/stable/tutorials/notebooks/scarches_scvi_tools.html#Reference-mapping-with-TOTALVI +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: totalvi
+Namespace: integrate

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/integrate/totalvi/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "path/to/file"
+reference: # please fill in - example: "path/to/file"
+force_retrain: false
+query_modality: "rna"
+# query_proteins_modality: "foo"
+reference_modality: "rna"
+reference_proteins_modality: "prot"
+# input_layer: "foo"
+obs_batch: "sample_id"
+# var_input: "foo"
+
+# Outputs
+# output: "$id.$key.output.output"
+obsm_output: "X_integrated_totalvi"
+obsm_normalized_rna_output: "X_totalvi_normalized_rna"
+obsm_normalized_protein_output: "X_totalvi_normalized_protein"
+# reference_model_path: "$id.$key.reference_model_path.reference_model_path"
+# query_model_path: "$id.$key.query_model_path.query_model_path"
+
+# Learning parameters
+max_epochs: 400
+max_query_epochs: 200
+weight_decay: 0.0
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/integrate/totalvi/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu file with query data to integrate with reference.file, required
--referenceInput h5mu file with reference data to train the TOTALVI model.file, required
--force_retrainIf true, retrain the model and save it to reference_model_pathboolean_true
--query_modalitystring, default: "rna"
--query_proteins_modalityName of the modality in the input (query) h5mu file containing protein datastring
--reference_modalitystring, default: "rna"
--reference_proteins_modalityName of the modality containing proteins in the referencestring, default: "prot"
--input_layerInput layer to use. If None, X is usedstring
--obs_batchColumn name discriminating between your batches.string, default: "sample_id"
--var_input.var column containing highly variable genes. By default, do not subset genes.string
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required
--obsm_outputIn which .obsm slot to store the resulting integrated embedding.string, default: "X_integrated_totalvi"
--obsm_normalized_rna_outputIn which .obsm slot to store the normalized RNA from TOTALVI.string, default: "X_totalvi_normalized_rna"
--obsm_normalized_protein_outputIn which .obsm slot to store the normalized protein data from TOTALVI.string, default: "X_totalvi_normalized_protein"
--reference_model_pathDirectory with the reference model. If not exists, trained model will be saved therefile, default: "totalvi_model_reference"
--query_model_pathDirectory, where the query model will be savedfile, default: "totalvi_model_query"
+
+
+

Learning parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--max_epochsNumber of passes through the datasetinteger, default: 400
--max_query_epochsNumber of passes through the dataset, when fine-tuning model for queryinteger, default: 200
--weight_decayWeight decay, when fine-tuning model for querydouble, default: 0
+
+
+
+

Authors

+
    +
  • Vladimir Shitov
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/interpret/lianapy.html b/pr-preview/pr-51/components/modules/interpret/lianapy.html new file mode 100644 index 00000000..e285c2d8 --- /dev/null +++ b/pr-preview/pr-51/components/modules/interpret/lianapy.html @@ -0,0 +1,1684 @@ + + + + + + + + + + +OpenPipelines - Lianapy + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Lianapy

+
+ +
+
+ Performs LIANA integration based as described in https://github.com/saezlab/liana-py +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: lianapy
+Namespace: interpret

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/interpret/lianapy/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "path/to/file"
+# output: "$id.$key.output.output"
+output_compression: "gzip"
+modality: "rna"
+# layer: "foo"
+groupby: "bulk_labels"
+resource_name: "consensus"
+gene_symbol: "gene_symbol"
+expr_prop: 0.1
+min_cells: 5
+aggregate_method: "rra"
+return_all_lrs: false
+n_perms: 100
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/interpret/lianapy/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required
--outputOutput h5mu file.file, required
--output_compressionstring, default: "gzip"
--modalitystring, default: "rna"
--layerLayer in anndata.AnnData.layers to use. If None, use mudata.mod[modality].X.string
--groupbyThe key of the observations grouping to consider.string, default: "bulk_labels"
--resource_nameName of the resource to be loaded and use for ligand-receptor inference.string, default: "consensus"
--gene_symbolColumn name in var DataFrame in which gene symbol are stored.string, default: "gene_symbol"
--expr_propMinimum expression proportion for the ligands/receptors (and their subunits) in the corresponding cell identities. Set to ‘0’, to return unfiltered results.double, default: 0.1
--min_cellsMinimum cells per cell identity (‘groupby’) to be considered for downstream analysis.integer, default: 5
--aggregate_methodMethod aggregation approach, one of [‘mean’, ‘rra’], where ‘mean’ represents the mean rank, while ‘rra’ is the RobustRankAggregate (Kolde et al., 2014) of the interactions.string, default: "rra"
--return_all_lrsBool whether to return all LRs, or only those that surpass the ‘expr_prop’ threshold. Those interactions that do not pass the ‘expr_prop’ threshold will be assigned to the worst score of the ones that do. ‘False’ by default.boolean, default: FALSE
--n_permsNumber of permutations for the permutation test. Note that this is relevant only for permutation-based methods - e.g. ’CellPhoneDBinteger, default: 100
+
+
+
+

Authors

+
    +

  • Mauro Saporita (author)

    • +

  • Povilas Gibas (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/labels_transfer/knn.html b/pr-preview/pr-51/components/modules/labels_transfer/knn.html new file mode 100644 index 00000000..5e24aa66 --- /dev/null +++ b/pr-preview/pr-51/components/modules/labels_transfer/knn.html @@ -0,0 +1,1718 @@ + + + + + + + + + + +OpenPipelines - Knn + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Knn

+
+ +
+
+ Performs label transfer from reference to query using KNN classifier +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: knn
+Namespace: labels_transfer

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/labels_transfer/knn/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Learning parameters
+n_neighbors: # please fill in - example: 123
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/labels_transfer/knn/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input dataset (query) arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputThe query data to transfer the labels to. Should be a .h5mu file.file, required
--modalityWhich modality to use.string, default: "rna"
--input_obsm_featuresThe .obsm key of the embedding to use for the classifier’s inference. If not provided, the .X slot will be used instead. Make sure that embedding was obtained in the same way as the reference embedding (e.g. by the same model or preprocessing).string, example: "X_integrated_scanvi"
+
+
+

Reference dataset arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--referenceThe reference data to train classifiers on.file, example: "https:/zenodo.org/record/6337966/files/HLCA_emb_and_metadata.h5ad"
--reference_obsm_featuresThe .obsm key of the embedding to use for the classifier’s training. Make sure that embedding was obtained in the same way as the query embedding (e.g. by the same model or preprocessing).string, required, default: "X_integrated_scanvi"
--reference_obs_targetsThe .obs key of the target labels to tranfer.string, default: "ann_level_1", default: "ann_level_2", default: "ann_level_3", default: "ann_level_4", default: "ann_level_5", default: "ann_finest_level"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputThe query data in .h5mu format with predicted labels transfered from the reference.file, required
--output_obs_predictionsIn which .obs slots to store the predicted information. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the "_pred" suffix.string
--output_obs_uncertaintyIn which .obs slots to store the uncertainty of the predictions. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the "_uncertainty" suffix.string
--output_uns_parametersThe .uns key to store additional information about the parameters used for the label transfer.string, default: "labels_transfer"
+
+
+

Learning parameters

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--n_neighborsNumber of nearest neighbors to use for classificationinteger, required
+
+
+
+

Authors

+
    +
  • Vladimir Shitov (author)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/labels_transfer/xgboost.html b/pr-preview/pr-51/components/modules/labels_transfer/xgboost.html new file mode 100644 index 00000000..fd65bd95 --- /dev/null +++ b/pr-preview/pr-51/components/modules/labels_transfer/xgboost.html @@ -0,0 +1,1835 @@ + + + + + + + + + + +OpenPipelines - Xgboost + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Xgboost

+
+ +
+
+ Performs label transfer from reference to query using XGBoost classifier +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: xgboost
+Namespace: labels_transfer

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/labels_transfer/xgboost/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Execution arguments
+force_retrain: false
+use_gpu: false
+verbosity: 1
+# model_output: "$id.$key.model_output.model_output"
+
+# Learning parameters
+learning_rate: 0.3
+min_split_loss: 0
+max_depth: 6
+min_child_weight: 1
+max_delta_step: 0
+subsample: 1
+sampling_method: "uniform"
+colsample_bytree: 1
+colsample_bylevel: 1
+colsample_bynode: 1
+reg_lambda: 1
+reg_alpha: 0
+scale_pos_weight: 1
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/labels_transfer/xgboost/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input dataset (query) arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputThe query data to transfer the labels to. Should be a .h5mu file.file, required
--modalityWhich modality to use.string, default: "rna"
--input_obsm_featuresThe .obsm key of the embedding to use for the classifier’s inference. If not provided, the .X slot will be used instead. Make sure that embedding was obtained in the same way as the reference embedding (e.g. by the same model or preprocessing).string, example: "X_integrated_scanvi"
+
+
+

Reference dataset arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--referenceThe reference data to train classifiers on.file, example: "https:/zenodo.org/record/6337966/files/HLCA_emb_and_metadata.h5ad"
--reference_obsm_featuresThe .obsm key of the embedding to use for the classifier’s training. Make sure that embedding was obtained in the same way as the query embedding (e.g. by the same model or preprocessing).string, required, default: "X_integrated_scanvi"
--reference_obs_targetsThe .obs key of the target labels to tranfer.string, default: "ann_level_1", default: "ann_level_2", default: "ann_level_3", default: "ann_level_4", default: "ann_level_5", default: "ann_finest_level"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputThe query data in .h5mu format with predicted labels transfered from the reference.file, required
--output_obs_predictionsIn which .obs slots to store the predicted information. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the "_pred" suffix.string
--output_obs_uncertaintyIn which .obs slots to store the uncertainty of the predictions. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the "_uncertainty" suffix.string
--output_uns_parametersThe .uns key to store additional information about the parameters used for the label transfer.string, default: "labels_transfer"
+
+
+

Execution arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--force_retrainRetrain models on the reference even if model_output directory already has trained classifiers. WARNING! It will rewrite existing classifiers for targets in the model_output directory!boolean_true
--use_gpuUse GPU during models training and inference (recommended).boolean, default: FALSE
--verbosityThe verbosity level for evaluation of the classifier from the range [0,2]integer, default: 1
--model_outputOutput directory for modelfile, default: "model"
+
+
+

Learning parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--learning_rateStep size shrinkage used in update to prevents overfitting. Range: [0,1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 0.3
--min_split_lossMinimum loss reduction required to make a further partition on a leaf node of the tree. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 0
--max_depthMaximum depth of a tree. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referenceinteger, default: 6
--min_child_weightMinimum sum of instance weight (hessian) needed in a child. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referenceinteger, default: 1
--max_delta_stepMaximum delta step we allow each leaf output to be. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 0
--subsampleSubsample ratio of the training instances. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 1
--sampling_methodThe method to use to sample the training instances. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencestring, default: "uniform"
--colsample_bytreeFraction of columns to be subsampled. Range (0, 1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 1
--colsample_bylevelSubsample ratio of columns for each level. Range (0, 1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 1
--colsample_bynodeSubsample ratio of columns for each node (split). Range (0, 1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 1
--reg_lambdaL2 regularization term on weights. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 1
--reg_alphaL1 regularization term on weights. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 0
--scale_pos_weightControl the balance of positive and negative weights, useful for unbalanced classes. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the referencedouble, default: 1
+
+
+
+

Authors

+
    +
  • Vladimir Shitov (author)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/bd_rhapsody.html b/pr-preview/pr-51/components/modules/mapping/bd_rhapsody.html new file mode 100644 index 00000000..6cfcc37b --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/bd_rhapsody.html @@ -0,0 +1,1852 @@ + + + + + + + + + + +OpenPipelines - BD Rhapsody + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

BD Rhapsody

+
+ +
+
+ A wrapper for the BD Rhapsody Analysis CWL v1.10.1 pipeline +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: bd_rhapsody
+Namespace: mapping

+
+ +

A wrapper for the BD Rhapsody Analysis CWL v1.10.1 pipeline.

+

The CWL pipeline file is obtained by cloning ‘https://bitbucket.org/CRSwDev/cwl/src/master/’ and removing all objects with class ‘DockerRequirement’ from the YML.

+

This pipeline can be used for a targeted analysis (with --mode targeted) or for a whole transcriptome analysis (with --mode wta).

+
    +
  • If mode is "targeted", then either the --reference or --abseq_reference parameters must be defined.
    • +
  • If mode is "wta", then --reference and --transcriptome_annotation must be defined, --abseq_reference and --supplemental_reference is optional.
    • +
+

The reference_genome and transcriptome_annotation files can be generated with the make_reference pipeline. Alternatively, BD also provides standard references which can be downloaded from these locations:

+
    +
  • Human: http://bd-rhapsody-public.s3-website-us-east-1.amazonaws.com/Rhapsody-WTA/GRCh38-PhiX-gencodev29/
    • +
  • Mouse: http://bd-rhapsody-public.s3-website-us-east-1.amazonaws.com/Rhapsody-WTA/GRCm38-PhiX-gencodevM19/
    • +
+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/bd_rhapsody/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+mode: # please fill in - example: "wta"
+input: # please fill in - example: ["input.fastq.gz"]
+reference: # please fill in - example: ["reference_genome.tar.gz|reference.fasta"]
+# transcriptome_annotation: "transcriptome.gtf"
+# abseq_reference: ["abseq_reference.fasta"]
+# supplemental_reference: ["supplemental_reference.fasta"]
+sample_prefix: "sample"
+
+# Outputs
+# output: "$id.$key.output.output"
+
+# Putative cell calling settings
+# putative_cell_call: "mRNA"
+# exact_cell_count: 10000
+disable_putative_calling: false
+
+# Subsample arguments
+# subsample: 0.01
+# subsample_seed: 3445
+
+# Multiplex arguments
+# sample_tags_version: "human"
+# tag_names: ["4-mySample", "9-myOtherSample", "6-alsoThisSample"]
+
+# VDJ arguments
+# vdj_version: "human"
+
+# CWL-runner arguments
+parallel: true
+timestamps: false
+dryrun: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/bd_rhapsody/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--modeWhether to run a whole transcriptome analysis (WTA) or a targeted analysis.string, required, example: "wta"
--inputPath to your read files in the FASTQ.GZ format. You may specify as many R1/R2 read pairs as you want.file, required, example: "input.fastq.gz"
--referenceRefence to map to. For --mode wta, this is the path to STAR index as a tar.gz file. For --mode targeted, this is the path to mRNA reference file for pre-designed, supplemental, or custom panel, in FASTA formatfile, required, example: "reference_genome.tar.gz&#124;reference.fasta"
--transcriptome_annotationPath to GTF annotation file (only for --mode wta).file, example: "transcriptome.gtf"
--abseq_referencePath to the AbSeq reference file in FASTA format. Only needed if BD AbSeq Ab-Oligos are used.file, example: "abseq_reference.fasta"
--supplemental_referencePath to the supplemental reference file in FASTA format. Only needed if there are additional transgene sequences used in the experiment (only for --mode wta).file, example: "supplemental_reference.fasta"
--sample_prefixSpecify a run name to use as the output file base name. Use only letters, numbers, or hyphens. Do not use special characters or spaces.string, default: "sample"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput folder. Output still needs to be processed further.file, required, example: "output_dir"
+
+
+

Putative cell calling settings

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--putative_cell_callSpecify the dataset to be used for putative cell calling. For putative cell calling using an AbSeq dataset, please provide an AbSeq_Reference fasta file above.string, example: "mRNA"
--exact_cell_countExact cell count - Set a specific number (>=1) of cells as putative, based on those with the highest error-corrected read countinteger, example: 10000
--disable_putative_callingDisable Refined Putative Cell Calling - Determine putative cells using only the basic algorithm (minimum second derivative along the cumulative reads curve). The refined algorithm attempts to remove false positives and recover false negatives, but may not be ideal for certain complex mixtures of cell types. Does not apply if Exact Cell Count is set.boolean_true
+
+
+

Subsample arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--subsampleA number >1 or fraction (0 < n < 1) to indicate the number or percentage of reads to subsample.double, example: 0.01
--subsample_seedA seed for replicating a previous subsampled run.integer, example: 3445
+
+
+

Multiplex arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--sample_tags_versionSpecify if multiplexed run.string, example: "human"
--tag_namesTag_Names (optional) - Specify the tag number followed by ‘-’ and the desired sample name to appear in Sample_Tag_Metrics.csv. Do not use the special characters: &, (), [], {}, <>, ?, |string, example: "4-mySample", example: "9-myOtherSample", example: "6-alsoThisSample"
+
+
+

VDJ arguments

+ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--vdj_versionSpecify if VDJ run.string, example: "human"
+
+
+

CWL-runner arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--parallelRun jobs in parallel.boolean, default: TRUE
--timestampsAdd timestamps to the errors, warnings, and notifications.boolean_true
--dryrunIf true, the output directory will only contain the CWL input files, but the pipeline itself will not be executed.boolean_true
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/cellranger_count.html b/pr-preview/pr-51/components/modules/mapping/cellranger_count.html new file mode 100644 index 00000000..ec10d289 --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/cellranger_count.html @@ -0,0 +1,1697 @@ + + + + + + + + + + +OpenPipelines - Cellranger count + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cellranger count

+
+ +
+
+ Align fastq files using Cell Ranger count. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellranger_count
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/cellranger_count/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: ["sample_S1_L001_R1_001.fastq.gz", "sample_S1_L001_R2_001.fastq.gz"]
+reference: # please fill in - example: "reference.tar.gz"
+
+# Outputs
+# output: "$id.$key.output.output"
+
+# Arguments
+# expect_cells: 3000
+chemistry: "auto"
+secondary_analysis: false
+generate_bam: true
+include_introns: true
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/cellranger_count/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputThe fastq.gz files to align. Can also be a single directory containing fastq.gz files.file, required, example: "sample_S1_L001_R1_001.fastq.gz", example: "sample_S1_L001_R2_001.fastq.gz"
--referenceThe path to Cell Ranger reference tar.gz file. Can also be a directory.file, required, example: "reference.tar.gz"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputThe folder to store the alignment results.file, required, example: "/path/to/output"
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--expect_cellsExpected number of recovered cells, used as input to cell calling algorithm.integer, example: 3000
--chemistryAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.string, default: "auto"
--secondary_analysisWhether or not to run the secondary analysis e.g. clustering.boolean, default: FALSE
--generate_bamWhether to generate a BAM file.boolean, default: TRUE
--include_intronsInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)boolean, default: TRUE
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Samuel D’Souza (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/cellranger_count_split.html b/pr-preview/pr-51/components/modules/mapping/cellranger_count_split.html new file mode 100644 index 00000000..34524c2e --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/cellranger_count_split.html @@ -0,0 +1,1649 @@ + + + + + + + + + + +OpenPipelines - Cellranger count split + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cellranger count split

+
+ +
+
+ Split 10x Cell Ranger output directory into separate output fields. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellranger_count_split
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/cellranger_count_split/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input_dir"
+# filtered_h5: "$id.$key.filtered_h5.h5"
+# metrics_summary: "$id.$key.metrics_summary.csv"
+# molecule_info: "$id.$key.molecule_info.h5"
+# bam: "$id.$key.bam.bam"
+# bai: "$id.$key.bai.bai"
+# raw_h5: "$id.$key.raw_h5.h5"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/cellranger_count_split/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputOutput directory from a Cell Ranger count run.file, required, example: "input_dir"
--filtered_h5file, example: "filtered_feature_bc_matrix.h5"
--metrics_summaryfile, example: "metrics_summary.csv"
--molecule_infofile, example: "molecule_info.h5"
--bamfile, example: "possorted_genome_bam.bam"
--baifile, example: "possorted_genome_bam.bam.bai"
--raw_h5file, example: "raw_feature_bc_matrix.h5"
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Samuel D’Souza (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/cellranger_multi.html b/pr-preview/pr-51/components/modules/mapping/cellranger_multi.html new file mode 100644 index 00000000..a8df1c48 --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/cellranger_multi.html @@ -0,0 +1,1828 @@ + + + + + + + + + + +OpenPipelines - Cellranger multi + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cellranger multi

+
+ +
+
+ Align fastq files using Cell Ranger multi. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellranger_multi
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/cellranger_multi/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Outputs
+# output: "$id.$key.output.output"
+
+# Input files
+input: # please fill in - example: ["mysample_S1_L001_R1_001.fastq.gz", "mysample_S1_L001_R2_001.fastq.gz"]
+gex_reference: # please fill in - example: "reference_genome.tar.gz"
+# vdj_reference: "reference_vdj.tar.gz"
+# vdj_inner_enrichment_primers: "enrichment_primers.txt"
+# feature_reference: "feature_reference.csv"
+
+# Library arguments
+library_id: # please fill in - example: ["mysample1"]
+library_type: # please fill in - example: ["Gene Expression"]
+# library_subsample: ["0.5"]
+# library_lanes: ["1-4"]
+
+# Gene expression arguments
+# gex_expect_cells: 3000
+gex_chemistry: "auto"
+gex_secondary_analysis: false
+gex_generate_bam: false
+gex_include_introns: true
+
+# Cell multiplexing parameters
+# cell_multiplex_sample_id: "foo"
+# cell_multiplex_oligo_ids: "foo"
+# cell_multiplex_description: "foo"
+
+# Executor arguments
+dryrun: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/cellranger_multi/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input files

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputThe FASTQ files to be analyzed. FASTQ files should conform to the naming conventions of bcl2fastq and mkfastq: [Sample Name]_S[Sample Index]_L00[Lane Number]_[Read Type]_001.fastq.gzfile, required, example: "mysample_S1_L001_R1_001.fastq.gz", example: "mysample_S1_L001_R2_001.fastq.gz"
--gex_referenceGenome refence index built by Cell Ranger mkref.file, required, example: "reference_genome.tar.gz"
--vdj_referenceVDJ refence index built by Cell Ranger mkref.file, example: "reference_vdj.tar.gz"
--vdj_inner_enrichment_primersV(D)J Immune Profiling libraries: if inner enrichment primers other than those provided in the 10x Genomics kits are used, they need to be specified here as a text file with one primer per line.file, example: "enrichment_primers.txt"
--feature_referencePath to the Feature reference CSV file, declaring Feature Barcode constructs and associated barcodes. Required only for Antibody Capture or CRISPR Guide Capture libraries. See https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/feature-bc-analysis#feature-ref for more information.file, example: "feature_reference.csv"
+
+
+

Library arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--library_idThe Illumina sample name to analyze. This must exactly match the ‘Sample Name’ part of the FASTQ files specified in the --input argument.string, required, example: "mysample1"
--library_typeThe underlying feature type of the library. Possible values: “Gene Expression”, “VDJ”, “VDJ-T”, “VDJ-B”, “Antibody Capture”, “CRISPR Guide Capture”, “Multiplexing Capture”string, required, example: "Gene Expression"
--library_subsampleOptional. The rate at which reads from the provided FASTQ files are sampled. Must be strictly greater than 0 and less than or equal to 1.string, example: "0.5"
--library_lanesLanes associated with this sample. Defaults to using all lanes.string, example: "1-4"
+
+
+

Gene expression arguments

+

Arguments relevant to the analysis of gene expression data.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--gex_expect_cellsExpected number of recovered cells, used as input to cell calling algorithm.integer, example: 3000
--gex_chemistryAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.string, default: "auto"
--gex_secondary_analysisWhether or not to run the secondary analysis e.g. clustering.boolean, default: FALSE
--gex_generate_bamWhether to generate a BAM file.boolean, default: FALSE
--gex_include_intronsInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)boolean, default: TRUE
+
+
+

Cell multiplexing parameters

+

Arguments related to cell multiplexing.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--cell_multiplex_sample_idA name to identify a multiplexed sample. Must be alphanumeric with hyphens and/or underscores, and less than 64 characters. Required for Cell Multiplexing libraries.string
--cell_multiplex_oligo_idsThe Cell Multiplexing oligo IDs used to multiplex this sample. If multiple CMOs were used for a sample, separate IDs with a pipe (e.g., CMO301|CMO302). Required for Cell Multiplexing libraries.string
--cell_multiplex_descriptionA description for the sample.string
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputThe folder to store the alignment results.file, required, example: "/path/to/output"
+
+
+

Executor arguments

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--dryrunIf true, the output directory will only contain the CWL input files, but the pipeline itself will not be executed.boolean_true
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Dries De Maeyer (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/htseq_count.html b/pr-preview/pr-51/components/modules/mapping/htseq_count.html new file mode 100644 index 00000000..19fddba8 --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/htseq_count.html @@ -0,0 +1,1758 @@ + + + + + + + + + + +OpenPipelines - Htseq count + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Htseq count

+
+ +
+
+ Quantify gene expression for subsequent testing for differential expression. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: htseq_count
+Namespace: mapping

+
+ +

This script takes one or more alignment files in SAM/BAM format and a feature file in GFF format and calculates for each feature the number of reads mapping to it.

+

See http://htseq.readthedocs.io/en/master/count.html for details.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/htseq_count/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+order: "name"
+stranded: "yes"
+minimum_alignment_quality: 10
+# type: "exon"
+# id_attribute: ["gene_id"]
+# additional_attributes: ["gene_name"]
+add_chromosome_info: false
+mode: "union"
+non_unique: "none"
+# secondary_alignments: "foo"
+# supplementary_alignments: "foo"
+counts_output_sparse: false
+
+# Input
+input: # please fill in - example: ["mysample1.BAM", "mysample2.BAM"]
+reference: # please fill in - example: "reference.gtf"
+
+# Output
+# output: "$id.$key.output.tsv"
+# output_delimiter: "   "
+# output_sam: ["$id.$key.output_sam_*.BAM"]
+# output_sam_format: "foo"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/htseq_count/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to the SAM/BAM files containing the mapped reads.file, required, example: "mysample1.BAM", example: "mysample2.BAM"
--referencePath to the GTF file containing the features.file, required, example: "reference.gtf"
+
+
+

Output

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputFilename to output the counts to.file, required, example: "htseq-count.tsv"
--output_delimiterColumn delimiter in output.string, example: " "
--output_samWrite out all SAM alignment records into SAM/BAM files (one per input file needed), annotating each line with its feature assignment (as an optional field with tag ‘XF’). See the -p option to use BAM instead of SAM.file, example: "mysample1_out.BAM", example: "mysample2_out.BAM"
--output_sam_formatFormat to use with the –output_sam argument.string
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--orderSorting order of . Paired-end sequencing data must be sorted either by position or by read name, and the sorting order must be specified. Ignored for single-end data.string, default: "name"
--strandedWhether the data is from a strand-specific assay. ‘reverse’ means ‘yes’ with reversed strand interpretation.string, default: "yes"
--minimum_alignment_qualitySkip all reads with MAPQ alignment quality lower than the given minimum value. MAPQ is the 5th column of a SAM/BAM file and its usage depends on the software used to map the reads.integer, default: 10
--typeFeature type (3rd column in GTF file) to be used, all features of other type are ignored (default, suitable for Ensembl GTF files: exon)string, example: "exon"
--id_attributeGTF attribute to be used as feature ID (default, suitable for Ensembl GTF files: gene_id). All feature of the right type (see -t option) within the same GTF attribute will be added together. The typical way of using this option is to count all exonic reads from each gene and add the exons but other uses are possible as well. You can call this option multiple times: in that case, the combination of all attributes separated by colons (:) will be used as a unique identifier, e.g. for exons you might use -i gene_id -i exon_number.string, example: "gene_id"
--additional_attributesAdditional feature attributes (suitable for Ensembl GTF files: gene_name). Use multiple times for more than one additional attribute. These attributes are only used as annotations in the output, while the determination of how the counts are added together is done based on option -i.string, example: "gene_name"
--add_chromosome_infoStore information about the chromosome of each feature as an additional attribute (e.g. colunm in the TSV output file).boolean_true
--modeMode to handle reads overlapping more than one feature.string, default: "union"
--non_uniqueWhether and how to score reads that are not uniquely aligned or ambiguously assigned to features.string, default: "none"
--secondary_alignmentsWhether to score secondary alignments (0x100 flag).string
--supplementary_alignmentsWhether to score supplementary alignments (0x800 flag).string
--counts_output_sparseStore the counts as a sparse matrix (mtx, h5ad, loom).boolean_true
+
+
+
+

Authors

+
    +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Angela Oliveira Pisco (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/htseq_count_to_h5mu.html b/pr-preview/pr-51/components/modules/mapping/htseq_count_to_h5mu.html new file mode 100644 index 00000000..766e28b1 --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/htseq_count_to_h5mu.html @@ -0,0 +1,1657 @@ + + + + + + + + + + +OpenPipelines - Htseq count to h5mu + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Htseq count to h5mu

+
+ +
+
+ Convert the htseq table to a h5mu +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: htseq_count_to_h5mu
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/htseq_count_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Input
+input_id: # please fill in - example: ["foo"]
+input_counts: # please fill in - example: ["counts.tsv"]
+reference: # please fill in - example: "gencode_v41_star"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/htseq_count_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--input_idThe obs index for the countsstring, required, example: "foo"
--input_countsThe counts as a TSV file as output by HTSeq.file, required, example: "counts.tsv"
--referenceThe GTF file.file, required, example: "gencode_v41_star"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Angela Oliveira Pisco (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/multi_star.html b/pr-preview/pr-51/components/modules/mapping/multi_star.html new file mode 100644 index 00000000..0dd705c7 --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/multi_star.html @@ -0,0 +1,3064 @@ + + + + + + + + + + +OpenPipelines - Multi star + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Multi star

+
+ +
+
+ Align fastq files using STAR. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: multi_star
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/multi_star/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Input/Output
+input_id: # please fill in - example: ["mysample", "mysample"]
+input_r1: # please fill in - example: ["mysample_S1_L001_R1_001.fastq.gz", "mysample_S1_L002_R1_001.fastq.gz"]
+# input_r2: ["mysample_S1_L001_R2_001.fastq.gz", "mysample_S1_L002_R2_001.fastq.gz"]
+reference_index: # please fill in - example: "/path/to/reference"
+reference_gtf: # please fill in - example: "genes.gtf"
+# output: "$id.$key.output.output"
+
+# Processing arguments
+run_htseq_count: true
+run_multiqc: true
+min_success_rate: 0.5
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/multi_star/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input/Output

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--input_idThe ID of the sample being processed. This vector should have the same length as the --input_r1 argument.string, required, example: "mysample", example: "mysample"
--input_r1Paths to the sequences to be mapped. If using Illumina paired-end reads, only the R1 files should be passed.file, required, example: "mysample_S1_L001_R1_001.fastq.gz", example: "mysample_S1_L002_R1_001.fastq.gz"
--input_r2Paths to the sequences to be mapped. If using Illumina paired-end reads, only the R2 files should be passed.file, example: "mysample_S1_L001_R2_001.fastq.gz", example: "mysample_S1_L002_R2_001.fastq.gz"
--reference_indexPath to the reference built by star_build_reference. Corresponds to the –genomeDir argument in the STAR command.file, required, example: "/path/to/reference"
--reference_gtfPath to the gtf reference file.file, required, example: "genes.gtf"
--outputPath to output directory. Corresponds to the –outFileNamePrefix argument in the STAR command.file, required, example: "/path/to/foo"
+
+
+

Processing arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--run_htseq_countWhether or not to also run htseq-count after STAR.boolean, default: TRUE
--run_multiqcWhether or not to also run MultiQC at the end.boolean, default: TRUE
--min_success_rateFail when the success rate is below this threshold.double, default: 0.5
+
+
+

Run Parameters

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--runRNGseedrandom number generator seed.integer, example: 777
+
+
+

Genome Parameters

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--genomeFastaFilespath(s) to the fasta files with the genome sequences, separated by spaces. These files should be plain text FASTA files, they cannot be zipped. Required for the genome generation (–runMode genomeGenerate). Can also be used in the mapping (–runMode alignReads) to add extra (new) sequences to the genome (e.g. spike-ins).file
+
+
+

Splice Junctions Database

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--sjdbFileChrStartEndpath to the files with genomic coordinates (chr start end strand) for the splice junction introns. Multiple files can be supplied and will be concatenated.string
--sjdbGTFfilepath to the GTF file with annotationsfile
--sjdbGTFchrPrefixprefix for chromosome names in a GTF file (e.g. ‘chr’ for using ENSMEBL annotations with UCSC genomes)string
--sjdbGTFfeatureExonfeature type in GTF file to be used as exons for building transcriptsstring, example: "exon"
--sjdbGTFtagExonParentTranscriptGTF attribute name for parent transcript ID (default “transcript_id” works for GTF files)string, example: "transcript_id"
--sjdbGTFtagExonParentGeneGTF attribute name for parent gene ID (default “gene_id” works for GTF files)string, example: "gene_id"
--sjdbGTFtagExonParentGeneNameGTF attribute name for parent gene namestring, example: "gene_name"
--sjdbGTFtagExonParentGeneTypeGTF attribute name for parent gene typestring, example: "gene_type", example: "gene_biotype"
--sjdbOverhanglength of the donor/acceptor sequence on each side of the junctions, ideally = (mate_length - 1)integer, example: 100
--sjdbScoreextra alignment score for alignments that cross database junctionsinteger, example: 2
--sjdbInsertSavewhich files to save when sjdb junctions are inserted on the fly at the mapping step - Basic … only small junction / transcript files - All … all files including big Genome, SA and SAindex - this will create a complete genome directorystring, example: "Basic"
+
+
+

Variation parameters

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--varVCFfilepath to the VCF file that contains variation data. The 10th column should contain the genotype information, e.g. 0/1string
+
+
+

Read Parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--readFilesTypeformat of input read files - Fastx … FASTA or FASTQ - SAM SE … SAM or BAM single-end reads; for BAM use –readFilesCommand samtools view - SAM PE … SAM or BAM paired-end reads; for BAM use –readFilesCommand samtools viewstring, example: "Fastx"
--readFilesSAMattrKeepfor –readFilesType SAM SE/PE, which SAM tags to keep in the output BAM, e.g.: –readFilesSAMtagsKeep RG PL - All … keep all tags - None … do not keep any tagsstring, example: "All"
--readFilesManifestpath to the “manifest” file with the names of read files. The manifest file should contain 3 tab-separated columns: paired-end reads: read1_file_name \(tab\) read2_file_name \(tab\) read_group_line. single-end reads: read1_file_name \(tab\) - \(tab\) read_group_line. Spaces, but not tabs are allowed in file names. If read_group_line does not start with ID:, it can only contain one ID field, and ID: will be added to it. If read_group_line starts with ID:, it can contain several fields separated by \(tab\), and all fields will be be copied verbatim into SAM @RG header line.file
--readFilesPrefixprefix for the read files names, i.e. it will be added in front of the strings in –readFilesInstring
--readFilesCommandcommand line to execute for each of the input file. This command should generate FASTA or FASTQ text and send it to stdout For example: zcat - to uncompress .gz files, bzcat - to uncompress .bz2 files, etc.string
--readMapNumbernumber of reads to map from the beginning of the file -1: map all readsinteger, example: -1
--readMatesLengthsInEqual/NotEqual - lengths of names,sequences,qualities for both mates are the same / not the same. NotEqual is safe in all situations.string, example: "NotEqual"
--readNameSeparatorcharacter(s) separating the part of the read names that will be trimmed in output (read name after space is always trimmed)string, example: "/"
--readQualityScoreBasenumber to be subtracted from the ASCII code to get Phred quality scoreinteger, example: 33
+
+
+

Read Clipping

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--clipAdapterTypeadapter clipping type - Hamming … adapter clipping based on Hamming distance, with the number of mismatches controlled by –clip5pAdapterMMp - CellRanger4 … 5p and 3p adapter clipping similar to CellRanger4. Utilizes Opal package by Martin Sosic: https://github.com/Martinsos/opal - None … no adapter clipping, all other clip* parameters are disregardedstring, example: "Hamming"
--clip3pNbasesnumber(s) of bases to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates.integer, example: 0
--clip3pAdapterSeqadapter sequences to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates. - polyA … polyA sequence with the length equal to read lengthstring
--clip3pAdapterMMpmax proportion of mismatches for 3p adapter clipping for each mate. If one value is given, it will be assumed the same for both mates.double, example: 0.1
--clip3pAfterAdapterNbasesnumber of bases to clip from 3p of each mate after the adapter clipping. If one value is given, it will be assumed the same for both mates.integer, example: 0
--clip5pNbasesnumber(s) of bases to clip from 5p of each mate. If one value is given, it will be assumed the same for both mates.integer, example: 0
+
+
+

Limits

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--limitGenomeGenerateRAMmaximum available RAM (bytes) for genome generationlong, example: NA
--limitIObufferSizemax available buffers size (bytes) for input/output, per threadlong, example: 30000000, example: 50000000
--limitOutSAMoneReadBytesmax size of the SAM record (bytes) for one read. Recommended value: >(2(LengthMate1+LengthMate2+100)outFilterMultimapNmaxlong, example: 100000
--limitOutSJoneReadmax number of junctions for one read (including all multi-mappers)integer, example: 1000
--limitOutSJcollapsedmax number of collapsed junctionsinteger, example: 1000000
--limitBAMsortRAMmaximum available RAM (bytes) for sorting BAM. If =0, it will be set to the genome index size. 0 value can only be used with –genomeLoad NoSharedMemory option.long, example: 0
--limitSjdbInsertNsjmaximum number of junctions to be inserted to the genome on the fly at the mapping stage, including those from annotations and those detected in the 1st step of the 2-pass runinteger, example: 1000000
--limitNreadsSoftsoft limit on the number of readsinteger, example: -1
+
+
+

Output: general

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outTmpKeepwhether to keep the temporary files after STAR runs is finished - None … remove all temporary files - All … keep all filesstring
--outStdwhich output will be directed to stdout (standard out) - Log … log messages - SAM … alignments in SAM format (which normally are output to Aligned.out.sam file), normal standard output will go into Log.std.out - BAM_Unsorted … alignments in BAM format, unsorted. Requires –outSAMtype BAM Unsorted - BAM_SortedByCoordinate … alignments in BAM format, sorted by coordinate. Requires –outSAMtype BAM SortedByCoordinate - BAM_Quant … alignments to transcriptome in BAM format, unsorted. Requires –quantMode TranscriptomeSAMstring, example: "Log"
--outReadsUnmappedoutput of unmapped and partially mapped (i.e. mapped only one mate of a paired end read) reads in separate file(s). - None … no output - Fastx … output in separate fasta/fastq files, Unmapped.out.mate1/2string
--outQSconversionAddadd this number to the quality score (e.g. to convert from Illumina to Sanger, use -31)integer, example: 0
--outMultimapperOrderorder of multimapping alignments in the output files - Old_2.4 … quasi-random order used before 2.5.0 - Random … random order of alignments for each multi-mapper. Read mates (pairs) are always adjacent, all alignment for each read stay together. This option will become default in the future releases.string, example: "Old_2.4"
+
+
+

Output: SAM and BAM

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outSAMmodemode of SAM output - None … no SAM output - Full … full SAM output - NoQS … full SAM but without quality scoresstring, example: "Full"
--outSAMstrandFieldCufflinks-like strand field flag - None … not used - intronMotif … strand derived from the intron motif. This option changes the output alignments: reads with inconsistent and/or non-canonical introns are filtered out.string
--outSAMattributesa string of desired SAM attributes, in the order desired for the output SAM. Tags can be listed in any combination/order. Presets: - None … no attributes - Standard … NH HI AS nM - All … NH HI AS nM NM MD jM jI MC ch Alignment: - NH … number of loci the reads maps to: =1 for unique mappers, >1 for multimappers. Standard SAM tag. - HI … multiple alignment index, starts with –outSAMattrIHstart (=1 by default). Standard SAM tag. - AS … local alignment score, +1/-1 for matches/mismateches, score* penalties for indels and gaps. For PE reads, total score for two mates. Stadnard SAM tag. - nM … number of mismatches. For PE reads, sum over two mates. - NM … edit distance to the reference (number of mismatched + inserted + deleted bases) for each mate. Standard SAM tag. - MD … string encoding mismatched and deleted reference bases (see standard SAM specifications). Standard SAM tag. - jM … intron motifs for all junctions (i.e. N in CIGAR): 0: non-canonical; 1: GT/AG, 2: CT/AC, 3: GC/AG, 4: CT/GC, 5: AT/AC, 6: GT/AT. If splice junctions database is used, and a junction is annotated, 20 is added to its motif value. - jI … start and end of introns for all junctions (1-based). - XS … alignment strand according to –outSAMstrandField. - MC … mate’s CIGAR string. Standard SAM tag. - ch … marks all segment of all chimeric alingments for –chimOutType WithinBAM output. - cN … number of bases clipped from the read ends: 5’ and 3’ Variation: - vA … variant allele - vG … genomic coordinate of the variant overlapped by the read. - vW … 1 - alignment passes WASP filtering; 2,3,4,5,6,7 - alignment does not pass WASP filtering. Requires –waspOutputMode SAMtag. STARsolo: - CR CY UR UY … sequences and quality scores of cell barcodes and UMIs for the solo* demultiplexing. - GX GN … gene ID and gene name for unique-gene reads. - gx gn … gene IDs and gene names for unique- and multi-gene reads. - CB UB … error-corrected cell barcodes and UMIs for solo* demultiplexing. Requires –outSAMtype BAM SortedByCoordinate. - sM … assessment of CB and UMI. - sS … sequence of the entire barcode (CB,UMI,adapter). - sQ … quality of the entire barcode. ***Unsupported/undocumented: - ha … haplotype (1/2) when mapping to the diploid genome. Requires genome generated with –genomeTransformType Diploid . - rB … alignment block read/genomic coordinates. - vR … read coordinate of the variant.string, example: "Standard"
--outSAMattrIHstartstart value for the IH attribute. 0 may be required by some downstream software, such as Cufflinks or StringTie.integer, example: 1
--outSAMunmappedoutput of unmapped reads in the SAM format 1st word: - None … no output - Within … output unmapped reads within the main SAM file (i.e. Aligned.out.sam) 2nd word: - KeepPairs … record unmapped mate for each alignment, and, in case of unsorted output, keep it adjacent to its mapped mate. Only affects multi-mapping reads.string
--outSAMordertype of sorting for the SAM output Paired: one mate after the other for all paired alignments PairedKeepInputOrder: one mate after the other for all paired alignments, the order is kept the same as in the input FASTQ filesstring, example: "Paired"
--outSAMprimaryFlagwhich alignments are considered primary - all others will be marked with 0x100 bit in the FLAG - OneBestScore … only one alignment with the best score is primary - AllBestScore … all alignments with the best score are primarystring, example: "OneBestScore"
--outSAMreadIDread ID record type - Standard … first word (until space) from the FASTx read ID line, removing /1,/2 from the end - Number … read number (index) in the FASTx filestring, example: "Standard"
--outSAMmapqUnique0 to 255: the MAPQ value for unique mappersinteger, example: 255
--outSAMflagOR0 to 65535: sam FLAG will be bitwise OR’d with this value, i.e. FLAG=FLAG | outSAMflagOR. This is applied after all flags have been set by STAR, and after outSAMflagAND. Can be used to set specific bits that are not set otherwise.integer, example: 0
--outSAMflagAND0 to 65535: sam FLAG will be bitwise AND’d with this value, i.e. FLAG=FLAG & outSAMflagOR. This is applied after all flags have been set by STAR, but before outSAMflagOR. Can be used to unset specific bits that are not set otherwise.integer, example: 65535
--outSAMattrRGlineSAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”. xxx will be added as RG tag to each output alignment. Any spaces in the tag values have to be double quoted. Comma separated RG lines correspons to different (comma separated) input files in –readFilesIn. Commas have to be surrounded by spaces, e.g. –outSAMattrRGline ID:xxx , ID:zzz “DS:z z” , ID:yyy DS:yyyystring
--outSAMheaderHD@HD (header) line of the SAM headerstring
--outSAMheaderPGextra @PG (software) line of the SAM header (in addition to STAR)string
--outSAMheaderCommentFilepath to the file with @CO (comment) lines of the SAM headerstring
--outSAMfilterfilter the output into main SAM/BAM files - KeepOnlyAddedReferences … only keep the reads for which all alignments are to the extra reference sequences added with –genomeFastaFiles at the mapping stage. - KeepAllAddedReferences … keep all alignments to the extra reference sequences added with –genomeFastaFiles at the mapping stage.string
--outSAMmultNmaxmax number of multiple alignments for a read that will be output to the SAM/BAM files. Note that if this value is not equal to -1, the top scoring alignment will be output first - -1 … all alignments (up to –outFilterMultimapNmax) will be outputinteger, example: -1
--outSAMtlencalculation method for the TLEN field in the SAM/BAM files - 1 … leftmost base of the (+)strand mate to rightmost base of the (-)mate. (+)sign for the (+)strand mate - 2 … leftmost base of any mate to rightmost base of any mate. (+)sign for the mate with the leftmost base. This is different from 1 for overlapping mates with protruding endsinteger, example: 1
--outBAMcompression-1 to 10 BAM compression level, -1=default compression (6?), 0=no compression, 10=maximum compressioninteger, example: 1
--outBAMsortingThreadN>=0: number of threads for BAM sorting. 0 will default to min(6,–runThreadN).integer, example: 0
--outBAMsortingBinsN>0: number of genome bins for coordinate-sortinginteger, example: 50
+
+
+

BAM processing

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--bamRemoveDuplicatesTypemark duplicates in the BAM file, for now only works with (i) sorted BAM fed with inputBAMfile, and (ii) for paired-end alignments only - - … no duplicate removal/marking - UniqueIdentical … mark all multimappers, and duplicate unique mappers. The coordinates, FLAG, CIGAR must be identical - UniqueIdenticalNotMulti … mark duplicate unique mappers but not multimappers.string
--bamRemoveDuplicatesMate2basesNnumber of bases from the 5’ of mate 2 to use in collapsing (e.g. for RAMPAGE)integer, example: 0
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Output Wiggle

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NameDescriptionAttributes
--outWigTypetype of signal output, e.g. “bedGraph” OR “bedGraph read1_5p”. Requires sorted BAM: –outSAMtype BAM SortedByCoordinate . 1st word: - None … no signal output - bedGraph … bedGraph format - wiggle … wiggle format 2nd word: - read1_5p … signal from only 5’ of the 1st read, useful for CAGE/RAMPAGE etc - read2 … signal from only 2nd readstring
--outWigStrandstrandedness of wiggle/bedGraph output - Stranded … separate strands, str1 and str2 - Unstranded … collapsed strandsstring, example: "Stranded"
--outWigReferencesPrefixprefix matching reference names to include in the output wiggle file, e.g. “chr”, default “-” - include all referencesstring
--outWigNormtype of normalization for the signal - RPM … reads per million of mapped reads - None … no normalization, “raw” countsstring, example: "RPM"
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Output Filtering

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NameDescriptionAttributes
--outFilterTypetype of filtering - Normal … standard filtering using only current alignment - BySJout … keep only those reads that contain junctions that passed filtering into SJ.out.tabstring, example: "Normal"
--outFilterMultimapScoreRangethe score range below the maximum score for multimapping alignmentsinteger, example: 1
--outFilterMultimapNmaxmaximum number of loci the read is allowed to map to. Alignments (all of them) will be output only if the read maps to no more loci than this value. Otherwise no alignments will be output, and the read will be counted as “mapped to too many loci” in the Log.final.out .integer, example: 10
--outFilterMismatchNmaxalignment will be output only if it has no more mismatches than this value.integer, example: 10
--outFilterMismatchNoverLmaxalignment will be output only if its ratio of mismatches to mapped length is less than or equal to this value.double, example: 0.3
--outFilterMismatchNoverReadLmaxalignment will be output only if its ratio of mismatches to read length is less than or equal to this value.double, example: 1
--outFilterScoreMinalignment will be output only if its score is higher than or equal to this value.integer, example: 0
--outFilterScoreMinOverLreadsame as outFilterScoreMin, but normalized to read length (sum of mates’ lengths for paired-end reads)double, example: 0.66
--outFilterMatchNminalignment will be output only if the number of matched bases is higher than or equal to this value.integer, example: 0
--outFilterMatchNminOverLreadsam as outFilterMatchNmin, but normalized to the read length (sum of mates’ lengths for paired-end reads).double, example: 0.66
--outFilterIntronMotifsfilter alignment using their motifs - None … no filtering - RemoveNoncanonical … filter out alignments that contain non-canonical junctions - RemoveNoncanonicalUnannotated … filter out alignments that contain non-canonical unannotated junctions when using annotated splice junctions database. The annotated non-canonical junctions will be kept.string
--outFilterIntronStrandsfilter alignments - RemoveInconsistentStrands … remove alignments that have junctions with inconsistent strands - None … no filteringstring, example: "RemoveInconsistentStrands"
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Output splice junctions (SJ.out.tab)

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NameDescriptionAttributes
--outSJtypetype of splice junction output - Standard … standard SJ.out.tab output - None … no splice junction outputstring, example: "Standard"
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Output Filtering: Splice Junctions

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NameDescriptionAttributes
--outSJfilterReadswhich reads to consider for collapsed splice junctions output - All … all reads, unique- and multi-mappers - Unique … uniquely mapping reads onlystring, example: "All"
--outSJfilterOverhangMinminimum overhang length for splice junctions on both sides for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif does not apply to annotated junctionsinteger, example: 30, example: 12, example: 12, example: 12
--outSJfilterCountUniqueMinminimum uniquely mapping read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctionsinteger, example: 3, example: 1, example: 1, example: 1
--outSJfilterCountTotalMinminimum total (multi-mapping+unique) read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctionsinteger, example: 3, example: 1, example: 1, example: 1
--outSJfilterDistToOtherSJminminimum allowed distance to other junctions’ donor/acceptor does not apply to annotated junctionsinteger, example: 10, example: 0, example: 5, example: 10
--outSJfilterIntronMaxVsReadNmaximum gap allowed for junctions supported by 1,2,3,,,N reads i.e. by default junctions supported by 1 read can have gaps <=50000b, by 2 reads: <=100000b, by 3 reads: <=200000. by >=4 reads any gap <=alignIntronMax does not apply to annotated junctionsinteger, example: 50000, example: 100000, example: 200000
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Scoring

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NameDescriptionAttributes
--scoreGapsplice junction penalty (independent on intron motif)integer, example: 0
--scoreGapNoncannon-canonical junction penalty (in addition to scoreGap)integer, example: -8
--scoreGapGCAGGC/AG and CT/GC junction penalty (in addition to scoreGap)integer, example: -4
--scoreGapATACAT/AC and GT/AT junction penalty (in addition to scoreGap)integer, example: -8
--scoreGenomicLengthLog2scaleextra score logarithmically scaled with genomic length of the alignment: scoreGenomicLengthLog2scale*log2(genomicLength)integer, example: 0
--scoreDelOpendeletion open penaltyinteger, example: -2
--scoreDelBasedeletion extension penalty per base (in addition to scoreDelOpen)integer, example: -2
--scoreInsOpeninsertion open penaltyinteger, example: -2
--scoreInsBaseinsertion extension penalty per base (in addition to scoreInsOpen)integer, example: -2
--scoreStitchSJshiftmaximum score reduction while searching for SJ boundaries in the stitching stepinteger, example: 1
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Alignments and Seeding

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NameDescriptionAttributes
--seedSearchStartLmaxdefines the search start point through the read - the read is split into pieces no longer than this valueinteger, example: 50
--seedSearchStartLmaxOverLreadseedSearchStartLmax normalized to read length (sum of mates’ lengths for paired-end reads)double, example: 1
--seedSearchLmaxdefines the maximum length of the seeds, if =0 seed length is not limitedinteger, example: 0
--seedMultimapNmaxonly pieces that map fewer than this value are utilized in the stitching procedureinteger, example: 10000
--seedPerReadNmaxmax number of seeds per readinteger, example: 1000
--seedPerWindowNmaxmax number of seeds per windowinteger, example: 50
--seedNoneLociPerWindowmax number of one seed loci per windowinteger, example: 10
--seedSplitMinmin length of the seed sequences split by Ns or mate gapinteger, example: 12
--seedMapMinmin length of seeds to be mappedinteger, example: 5
--alignIntronMinminimum intron size, genomic gap is considered intron if its length>=alignIntronMin, otherwise it is considered Deletioninteger, example: 21
--alignIntronMaxmaximum intron size, if 0, max intron size will be determined by (2^winBinNbits)*winAnchorDistNbinsinteger, example: 0
--alignMatesGapMaxmaximum gap between two mates, if 0, max intron gap will be determined by (2^winBinNbits)*winAnchorDistNbinsinteger, example: 0
--alignSJoverhangMinminimum overhang (i.e. block size) for spliced alignmentsinteger, example: 5
--alignSJstitchMismatchNmaxmaximum number of mismatches for stitching of the splice junctions (-1: no limit). (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif.integer, example: 0, example: -1, example: 0, example: 0
--alignSJDBoverhangMinminimum overhang (i.e. block size) for annotated (sjdb) spliced alignmentsinteger, example: 3
--alignSplicedMateMapLminminimum mapped length for a read mate that is splicedinteger, example: 0
--alignSplicedMateMapLminOverLmatealignSplicedMateMapLmin normalized to mate lengthdouble, example: 0.66
--alignWindowsPerReadNmaxmax number of windows per readinteger, example: 10000
--alignTranscriptsPerWindowNmaxmax number of transcripts per windowinteger, example: 100
--alignTranscriptsPerReadNmaxmax number of different alignments per read to considerinteger, example: 10000
--alignEndsTypetype of read ends alignment - Local … standard local alignment with soft-clipping allowed - EndToEnd … force end-to-end read alignment, do not soft-clip - Extend5pOfRead1 … fully extend only the 5p of the read1, all other ends: local alignment - Extend5pOfReads12 … fully extend only the 5p of the both read1 and read2, all other ends: local alignmentstring, example: "Local"
--alignEndsProtrudeallow protrusion of alignment ends, i.e. start (end) of the +strand mate downstream of the start (end) of the -strand mate 1st word: int: maximum number of protrusion bases allowed 2nd word: string: - ConcordantPair … report alignments with non-zero protrusion as concordant pairs - DiscordantPair … report alignments with non-zero protrusion as discordant pairsstring, example: "0 ConcordantPair"
--alignSoftClipAtReferenceEndsallow the soft-clipping of the alignments past the end of the chromosomes - Yes … allow - No … prohibit, useful for compatibility with Cufflinksstring, example: "Yes"
--alignInsertionFlushhow to flush ambiguous insertion positions - None … insertions are not flushed - Right … insertions are flushed to the rightstring
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Paired-End reads

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NameDescriptionAttributes
--peOverlapNbasesMinminimum number of overlapping bases to trigger mates merging and realignment. Specify >0 value to switch on the “merginf of overlapping mates” algorithm.integer, example: 0
--peOverlapMMpmaximum proportion of mismatched bases in the overlap areadouble, example: 0.01
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Windows, Anchors, Binning

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NameDescriptionAttributes
--winAnchorMultimapNmaxmax number of loci anchors are allowed to map tointeger, example: 50
--winBinNbits=log2(winBin), where winBin is the size of the bin for the windows/clustering, each window will occupy an integer number of bins.integer, example: 16
--winAnchorDistNbinsmax number of bins between two anchors that allows aggregation of anchors into one windowinteger, example: 9
--winFlankNbinslog2(winFlank), where win Flank is the size of the left and right flanking regions for each windowinteger, example: 4
--winReadCoverageRelativeMinminimum relative coverage of the read sequence by the seeds in a window, for STARlong algorithm only.double, example: 0.5
--winReadCoverageBasesMinminimum number of bases covered by the seeds in a window , for STARlong algorithm only.integer, example: 0
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Chimeric Alignments

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NameDescriptionAttributes
--chimOutTypetype of chimeric output - Junctions … Chimeric.out.junction - SeparateSAMold … output old SAM into separate Chimeric.out.sam file - WithinBAM … output into main aligned BAM files (Aligned.*.bam) - WithinBAM HardClip … (default) hard-clipping in the CIGAR for supplemental chimeric alignments (default if no 2nd word is present) - WithinBAM SoftClip … soft-clipping in the CIGAR for supplemental chimeric alignmentsstring, example: "Junctions"
--chimSegmentMinminimum length of chimeric segment length, if ==0, no chimeric outputinteger, example: 0
--chimScoreMinminimum total (summed) score of the chimeric segmentsinteger, example: 0
--chimScoreDropMaxmax drop (difference) of chimeric score (the sum of scores of all chimeric segments) from the read lengthinteger, example: 20
--chimScoreSeparationminimum difference (separation) between the best chimeric score and the next oneinteger, example: 10
--chimScoreJunctionNonGTAGpenalty for a non-GT/AG chimeric junctioninteger, example: -1
--chimJunctionOverhangMinminimum overhang for a chimeric junctioninteger, example: 20
--chimSegmentReadGapMaxmaximum gap in the read sequence between chimeric segmentsinteger, example: 0
--chimFilterdifferent filters for chimeric alignments - None … no filtering - banGenomicN … Ns are not allowed in the genome sequence around the chimeric junctionstring, example: "banGenomicN"
--chimMainSegmentMultNmaxmaximum number of multi-alignments for the main chimeric segment. =1 will prohibit multimapping main segments.integer, example: 10
--chimMultimapNmaxmaximum number of chimeric multi-alignments - 0 … use the old scheme for chimeric detection which only considered unique alignmentsinteger, example: 0
--chimMultimapScoreRangethe score range for multi-mapping chimeras below the best chimeric score. Only works with –chimMultimapNmax > 1integer, example: 1
--chimNonchimScoreDropMinto trigger chimeric detection, the drop in the best non-chimeric alignment score with respect to the read length has to be greater than this valueinteger, example: 20
--chimOutJunctionFormatformatting type for the Chimeric.out.junction file - 0 … no comment lines/headers - 1 … comment lines at the end of the file: command line and Nreads: total, unique/multi-mappinginteger, example: 0
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Quantification of Annotations

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NameDescriptionAttributes
--quantModetypes of quantification requested - - … none - TranscriptomeSAM … output SAM/BAM alignments to transcriptome into a separate file - GeneCounts … count reads per genestring
--quantTranscriptomeBAMcompression-2 to 10 transcriptome BAM compression level - -2 … no BAM output - -1 … default compression (6?) - 0 … no compression - 10 … maximum compressioninteger, example: 1
--quantTranscriptomeBanprohibit various alignment type - IndelSoftclipSingleend … prohibit indels, soft clipping and single-end alignments - compatible with RSEM - Singleend … prohibit single-end alignmentsstring, example: "IndelSoftclipSingleend"
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2-pass Mapping

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NameDescriptionAttributes
--twopassMode2-pass mapping mode. - None … 1-pass mapping - Basic … basic 2-pass mapping, with all 1st pass junctions inserted into the genome indices on the flystring
--twopass1readsNnumber of reads to process for the 1st step. Use very large number (or default -1) to map all reads in the first step.integer, example: -1
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WASP parameters

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NameDescriptionAttributes
--waspOutputModeWASP allele-specific output type. This is re-implementation of the original WASP mappability filtering by Bryce van de Geijn, Graham McVicker, Yoav Gilad & Jonathan K Pritchard. Please cite the original WASP paper: Nature Methods 12, 1061-1063 (2015), https://www.nature.com/articles/nmeth.3582 . - SAMtag … add WASP tags to the alignments that pass WASP filteringstring
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STARsolo (single cell RNA-seq) parameters

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NameDescriptionAttributes
--soloTypetype of single-cell RNA-seq - CB_UMI_Simple … (a.k.a. Droplet) one UMI and one Cell Barcode of fixed length in read2, e.g. Drop-seq and 10X Chromium. - CB_UMI_Complex … multiple Cell Barcodes of varying length, one UMI of fixed length and one adapter sequence of fixed length are allowed in read2 only (e.g. inDrop, ddSeq). - CB_samTagOut … output Cell Barcode as CR and/or CB SAm tag. No UMI counting. –readFilesIn cDNA_read1 [cDNA_read2 if paired-end] CellBarcode_read . Requires –outSAMtype BAM Unsorted [and/or SortedByCoordinate] - SmartSeq … Smart-seq: each cell in a separate FASTQ (paired- or single-end), barcodes are corresponding read-groups, no UMI sequences, alignments deduplicated according to alignment start and end (after extending soft-clipped bases)string
--soloCBwhitelistfile(s) with whitelist(s) of cell barcodes. Only –soloType CB_UMI_Complex allows more than one whitelist file. - None … no whitelist: all cell barcodes are allowedstring
--soloCBstartcell barcode start baseinteger, example: 1
--soloCBlencell barcode lengthinteger, example: 16
--soloUMIstartUMI start baseinteger, example: 17
--soloUMIlenUMI lengthinteger, example: 10
--soloBarcodeReadLengthlength of the barcode read - 1 … equal to sum of soloCBlen+soloUMIlen - 0 … not defined, do not checkinteger, example: 1
--soloBarcodeMateidentifies which read mate contains the barcode (CB+UMI) sequence - 0 … barcode sequence is on separate read, which should always be the last file in the –readFilesIn listed - 1 … barcode sequence is a part of mate 1 - 2 … barcode sequence is a part of mate 2integer, example: 0
--soloCBpositionposition of Cell Barcode(s) on the barcode read. Presently only works with –soloType CB_UMI_Complex, and barcodes are assumed to be on Read2. Format for each barcode: startAnchor_startPosition_endAnchor_endPosition start(end)Anchor defines the Anchor Base for the CB: 0: read start; 1: read end; 2: adapter start; 3: adapter end start(end)Position is the 0-based position with of the CB start(end) with respect to the Anchor Base String for different barcodes are separated by space. Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 0_0_2_-1 3_1_3_8string
--soloUMIpositionposition of the UMI on the barcode read, same as soloCBposition Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 3_9_3_14string
--soloAdapterSequenceadapter sequence to anchor barcodes. Only one adapter sequence is allowed.string
--soloAdapterMismatchesNmaxmaximum number of mismatches allowed in adapter sequence.integer, example: 1
--soloCBmatchWLtypematching the Cell Barcodes to the WhiteList - Exact … only exact matches allowed - 1MM … only one match in whitelist with 1 mismatched base allowed. Allowed CBs have to have at least one read with exact match. - 1MM_multi … multiple matches in whitelist with 1 mismatched base allowed, posterior probability calculation is used choose one of the matches. Allowed CBs have to have at least one read with exact match. This option matches best with CellRanger 2.2.0 - 1MM_multi_pseudocounts … same as 1MM_Multi, but pseudocounts of 1 are added to all whitelist barcodes. - 1MM_multi_Nbase_pseudocounts … same as 1MM_multi_pseudocounts, multimatching to WL is allowed for CBs with N-bases. This option matches best with CellRanger >= 3.0.0 - EditDist_2 … allow up to edit distance of 3 fpr each of the barcodes. May include one deletion + one insertion. Only works with –soloType CB_UMI_Complex. Matches to multiple passlist barcdoes are not allowed. Similar to ParseBio Split-seq pipeline.string, example: "1MM_multi"
--soloInputSAMattrBarcodeSeqwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode sequence (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeSeq CR UR . This parameter is required when running STARsolo with input from SAM.string
--soloInputSAMattrBarcodeQualwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode qualities (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeQual CY UY . If this parameter is ‘-’ (default), the quality ‘H’ will be assigned to all bases.string
--soloStrandstrandedness of the solo libraries: - Unstranded … no strand information - Forward … read strand same as the original RNA molecule - Reverse … read strand opposite to the original RNA moleculestring, example: "Forward"
--soloFeaturesgenomic features for which the UMI counts per Cell Barcode are collected - Gene … genes: reads match the gene transcript - SJ … splice junctions: reported in SJ.out.tab - GeneFull … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns - GeneFull_ExonOverIntron … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns: prioritize 100% overlap with exons - GeneFull_Ex50pAS … full gene (pre-RNA): count all reads overlapping genes’ exons and introns: prioritize >50% overlap with exons. Do not count reads with 100% exonic overlap in the antisense direction.string, example: "Gene"
--soloMultiMapperscounting method for reads mapping to multiple genes - Unique … count only reads that map to unique genes - Uniform … uniformly distribute multi-genic UMIs to all genes - Rescue … distribute UMIs proportionally to unique+uniform counts (~ first iteration of EM) - PropUnique … distribute UMIs proportionally to unique mappers, if present, and uniformly if not. - EM … multi-gene UMIs are distributed using Expectation Maximization algorithmstring, example: "Unique"
--soloUMIdeduptype of UMI deduplication (collapsing) algorithm - 1MM_All … all UMIs with 1 mismatch distance to each other are collapsed (i.e. counted once). - 1MM_Directional_UMItools … follows the “directional” method from the UMI-tools by Smith, Heger and Sudbery (Genome Research 2017). - 1MM_Directional … same as 1MM_Directional_UMItools, but with more stringent criteria for duplicate UMIs - Exact … only exactly matching UMIs are collapsed. - NoDedup … no deduplication of UMIs, count all reads. - 1MM_CR … CellRanger2-4 algorithm for 1MM UMI collapsing.string, example: "1MM_All"
--soloUMIfilteringtype of UMI filtering (for reads uniquely mapping to genes) - - … basic filtering: remove UMIs with N and homopolymers (similar to CellRanger 2.2.0). - MultiGeneUMI … basic + remove lower-count UMIs that map to more than one gene. - MultiGeneUMI_All … basic + remove all UMIs that map to more than one gene. - MultiGeneUMI_CR … basic + remove lower-count UMIs that map to more than one gene, matching CellRanger > 3.0.0 . Only works with –soloUMIdedup 1MM_CRstring
--soloOutFileNamesfile names for STARsolo output: file_name_prefix gene_names barcode_sequences cell_feature_count_matrixstring, example: "Solo.out/", example: "features.tsv", example: "barcodes.tsv", example: "matrix.mtx"
--soloCellFiltercell filtering type and parameters - None … do not output filtered cells - TopCells … only report top cells by UMI count, followed by the exact number of cells - CellRanger2.2 … simple filtering of CellRanger 2.2. Can be followed by numbers: number of expected cells, robust maximum percentile for UMI count, maximum to minimum ratio for UMI count The harcoded values are from CellRanger: nExpectedCells=3000; maxPercentile=0.99; maxMinRatio=10 - EmptyDrops_CR … EmptyDrops filtering in CellRanger flavor. Please cite the original EmptyDrops paper: A.T.L Lun et al, Genome Biology, 20, 63 (2019): https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1662-y Can be followed by 10 numeric parameters: nExpectedCells maxPercentile maxMinRatio indMin indMax umiMin umiMinFracMedian candMaxN FDR simN The harcoded values are from CellRanger: 3000 0.99 10 45000 90000 500 0.01 20000 0.01 10000string, example: "CellRanger2.2", example: "3000", example: "0.99", example: "10"
--soloOutFormatFeaturesGeneField3field 3 in the Gene features.tsv file. If “-”, then no 3rd field is output.string, example: "Gene Expression"
--soloCellReadStatsOutput reads statistics for each CB - Standard … standard outputstring
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HTSeq arguments

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NameDescriptionAttributes
--strandedWhether the data is from a strand-specific assay. ‘reverse’ means ‘yes’ with reversed strand interpretation.string, default: "yes"
--minimum_alignment_qualitySkip all reads with MAPQ alignment quality lower than the given minimum value. MAPQ is the 5th column of a SAM/BAM file and its usage depends on the software used to map the reads.integer, default: 10
--typeFeature type (3rd column in GTF file) to be used, all features of other type are ignored (default, suitable for Ensembl GTF files: exon)string, example: "exon"
--id_attributeGTF attribute to be used as feature ID (default, suitable for Ensembl GTF files: gene_id). All feature of the right type (see -t option) within the same GTF attribute will be added together. The typical way of using this option is to count all exonic reads from each gene and add the exons but other uses are possible as well. You can call this option multiple times: in that case, the combination of all attributes separated by colons (:) will be used as a unique identifier, e.g. for exons you might use -i gene_id -i exon_number.string, example: "gene_id"
--additional_attributesAdditional feature attributes (suitable for Ensembl GTF files: gene_name). Use multiple times for more than one additional attribute. These attributes are only used as annotations in the output, while the determination of how the counts are added together is done based on option -i.string, example: "gene_name"
--add_chromosome_infoStore information about the chromosome of each feature as an additional attribute (e.g. colunm in the TSV output file).boolean_true
--modeMode to handle reads overlapping more than one feature.string, default: "union"
--non_uniqueWhether and how to score reads that are not uniquely aligned or ambiguously assigned to features.string, default: "none"
--secondary_alignmentsWhether to score secondary alignments (0x100 flag).string
--supplementary_alignmentsWhether to score supplementary alignments (0x800 flag).string
--counts_output_sparseStore the counts as a sparse matrix (mtx, h5ad, loom).boolean_true
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Authors

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  • Angela Oliveira Pisco (author)

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  • Robrecht Cannoodt (author, maintainer)

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Multi star to h5mu

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+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: multi_star_to_h5mu
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/multi_star_to_h5mu/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "/path/to/foo"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/multi_star_to_h5mu/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputThe directory created by multi_starfile, required, example: "/path/to/foo"
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Angela Oliveira Pisco (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/samtools_sort.html b/pr-preview/pr-51/components/modules/mapping/samtools_sort.html new file mode 100644 index 00000000..1c90bd2b --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/samtools_sort.html @@ -0,0 +1,1711 @@ + + + + + + + + + + +OpenPipelines - Samtools sort + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Samtools sort

+
+ +
+
+ Sort and (optionally) index alignments. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: samtools_sort
+Namespace: mapping

+
+ +

Reads are sorted by leftmost coordinates, or by read name when --sort_by_read_names is used.

+

An appropriate @HD-SO sort order header tag will be added or an existing one updated if necessary.

+

Note that to generate an index file (by specifying --output_bai), the default coordinate sort must be used. Thus the --sort_by_read_names and --sort_by <TAG> options are incompatible with --output_bai.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/samtools_sort/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+minimizer_cluster: false
+# minimizer_kmer: 20
+sort_by_read_names: false
+# sort_by: "foo"
+no_pg: false
+
+# Input
+input: # please fill in - example: "input.bam"
+
+# Output
+# output_bam: "$id.$key.output_bam.bam"
+# output_bai: "$id.$key.output_bai.bai"
+# output_format: "bam"
+# compression: 5
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/samtools_sort/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to the SAM/BAM/CRAM files containing the mapped reads.file, required, example: "input.bam"
+
+
+

Output

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--output_bamFilename to output the counts to.file, required, example: "output.bam"
--output_baiBAI-format index for BAM file.file, example: "output.bam.bai"
--output_formatThe output format. By default, samtools tries to select a format based on the -o filename extension; if output is to standard output or no format can be deduced, bam is selected.string, example: "bam"
--compressionCompression level, from 0 (uncompressed) to 9 (bestinteger, example: 5
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--minimizer_clusterSort unmapped reads (those in chromosome “*“) by their sequence minimiser (Schleimer et al., 2003; Roberts et al., 2004), also reverse complementing as appropriate. This has the effect of collating some similar data together, improving the compressibility of the unmapped sequence. The minimiser kmer size is adjusted using the -K option. Note data compressed in this manner may need to be name collated prior to conversion back to fastq. Mapped sequences are sorted by chromosome and position.boolean_true
--minimizer_kmerSets the kmer size to be used in the -M option.integer, example: 20
--sort_by_read_namesSort by read names (i.e., the QNAME field) rather than by chromosomal coordinates.boolean_true
--sort_bySort first by this value in the alignment tag, then by position or name (if also using -n).string
--no_pgDo not add a @PG line to the header of the output file.boolean_true
+
+
+
+

Authors

+
    +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Angela Oliveira Pisco (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/star_align.html b/pr-preview/pr-51/components/modules/mapping/star_align.html new file mode 100644 index 00000000..84469bc3 --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/star_align.html @@ -0,0 +1,2958 @@ + + + + + + + + + + +OpenPipelines - Star align + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Star align

+
+ +
+
+ Align fastq files using STAR. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: star_align
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/star_align/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Input/Output
+input: # please fill in - example: ["mysample_S1_L001_R1_001.fastq.gz", "mysample_S1_L001_R2_001.fastq.gz"]
+reference: # please fill in - example: "/path/to/reference"
+# output: "$id.$key.output.output"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/star_align/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input/Output

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputThe FASTQ files to be analyzed. Corresponds to the –readFilesIn argument in the STAR command.file, required, example: "mysample_S1_L001_R1_001.fastq.gz", example: "mysample_S1_L001_R2_001.fastq.gz"
--referencePath to the reference built by star_build_reference. Corresponds to the –genomeDir argument in the STAR command.file, required, example: "/path/to/reference"
--outputPath to output directory. Corresponds to the –outFileNamePrefix argument in the STAR command.file, required, example: "/path/to/foo"
+
+
+

Run Parameters

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--runRNGseedrandom number generator seed.integer, example: 777
+
+
+

Genome Parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--genomeLoadmode of shared memory usage for the genome files. Only used with –runMode alignReads. - LoadAndKeep … load genome into shared and keep it in memory after run - LoadAndRemove … load genome into shared but remove it after run - LoadAndExit … load genome into shared memory and exit, keeping the genome in memory for future runs - Remove … do not map anything, just remove loaded genome from memory - NoSharedMemory … do not use shared memory, each job will have its own private copy of the genomestring, example: "NoSharedMemory"
--genomeFastaFilespath(s) to the fasta files with the genome sequences, separated by spaces. These files should be plain text FASTA files, they cannot be zipped. Required for the genome generation (–runMode genomeGenerate). Can also be used in the mapping (–runMode alignReads) to add extra (new) sequences to the genome (e.g. spike-ins).file
--genomeFileSizesgenome files exact sizes in bytes. Typically, this should not be defined by the user.integer, example: 0
--genomeTransformOutputwhich output to transform back to original genome - SAM … SAM/BAM alignments - SJ … splice junctions (SJ.out.tab) - None … no transformation of the outputstring
--genomeChrSetMitochondrialnames of the mitochondrial chromosomes. Presently only used for STARsolo statistics output/string, example: "chrM", example: "M", example: "MT"
+
+
+

Splice Junctions Database

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--sjdbFileChrStartEndpath to the files with genomic coordinates (chr start end strand) for the splice junction introns. Multiple files can be supplied and will be concatenated.string
--sjdbGTFfilepath to the GTF file with annotationsfile
--sjdbGTFchrPrefixprefix for chromosome names in a GTF file (e.g. ‘chr’ for using ENSMEBL annotations with UCSC genomes)string
--sjdbGTFfeatureExonfeature type in GTF file to be used as exons for building transcriptsstring, example: "exon"
--sjdbGTFtagExonParentTranscriptGTF attribute name for parent transcript ID (default “transcript_id” works for GTF files)string, example: "transcript_id"
--sjdbGTFtagExonParentGeneGTF attribute name for parent gene ID (default “gene_id” works for GTF files)string, example: "gene_id"
--sjdbGTFtagExonParentGeneNameGTF attribute name for parent gene namestring, example: "gene_name"
--sjdbGTFtagExonParentGeneTypeGTF attribute name for parent gene typestring, example: "gene_type", example: "gene_biotype"
--sjdbOverhanglength of the donor/acceptor sequence on each side of the junctions, ideally = (mate_length - 1)integer, example: 100
--sjdbScoreextra alignment score for alignments that cross database junctionsinteger, example: 2
--sjdbInsertSavewhich files to save when sjdb junctions are inserted on the fly at the mapping step - Basic … only small junction / transcript files - All … all files including big Genome, SA and SAindex - this will create a complete genome directorystring, example: "Basic"
+
+
+

Variation parameters

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--varVCFfilepath to the VCF file that contains variation data. The 10th column should contain the genotype information, e.g. 0/1string
+
+
+

Read Parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--readFilesTypeformat of input read files - Fastx … FASTA or FASTQ - SAM SE … SAM or BAM single-end reads; for BAM use –readFilesCommand samtools view - SAM PE … SAM or BAM paired-end reads; for BAM use –readFilesCommand samtools viewstring, example: "Fastx"
--readFilesSAMattrKeepfor –readFilesType SAM SE/PE, which SAM tags to keep in the output BAM, e.g.: –readFilesSAMtagsKeep RG PL - All … keep all tags - None … do not keep any tagsstring, example: "All"
--readFilesManifestpath to the “manifest” file with the names of read files. The manifest file should contain 3 tab-separated columns: paired-end reads: read1_file_name \(tab\) read2_file_name \(tab\) read_group_line. single-end reads: read1_file_name \(tab\) - \(tab\) read_group_line. Spaces, but not tabs are allowed in file names. If read_group_line does not start with ID:, it can only contain one ID field, and ID: will be added to it. If read_group_line starts with ID:, it can contain several fields separated by \(tab\), and all fields will be be copied verbatim into SAM @RG header line.file
--readFilesPrefixprefix for the read files names, i.e. it will be added in front of the strings in –readFilesInstring
--readFilesCommandcommand line to execute for each of the input file. This command should generate FASTA or FASTQ text and send it to stdout For example: zcat - to uncompress .gz files, bzcat - to uncompress .bz2 files, etc.string
--readMapNumbernumber of reads to map from the beginning of the file -1: map all readsinteger, example: -1
--readMatesLengthsInEqual/NotEqual - lengths of names,sequences,qualities for both mates are the same / not the same. NotEqual is safe in all situations.string, example: "NotEqual"
--readNameSeparatorcharacter(s) separating the part of the read names that will be trimmed in output (read name after space is always trimmed)string, example: "/"
--readQualityScoreBasenumber to be subtracted from the ASCII code to get Phred quality scoreinteger, example: 33
+
+
+

Read Clipping

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--clipAdapterTypeadapter clipping type - Hamming … adapter clipping based on Hamming distance, with the number of mismatches controlled by –clip5pAdapterMMp - CellRanger4 … 5p and 3p adapter clipping similar to CellRanger4. Utilizes Opal package by Martin Sosic: https://github.com/Martinsos/opal - None … no adapter clipping, all other clip* parameters are disregardedstring, example: "Hamming"
--clip3pNbasesnumber(s) of bases to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates.integer, example: 0
--clip3pAdapterSeqadapter sequences to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates. - polyA … polyA sequence with the length equal to read lengthstring
--clip3pAdapterMMpmax proportion of mismatches for 3p adapter clipping for each mate. If one value is given, it will be assumed the same for both mates.double, example: 0.1
--clip3pAfterAdapterNbasesnumber of bases to clip from 3p of each mate after the adapter clipping. If one value is given, it will be assumed the same for both mates.integer, example: 0
--clip5pNbasesnumber(s) of bases to clip from 5p of each mate. If one value is given, it will be assumed the same for both mates.integer, example: 0
+
+
+

Limits

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--limitGenomeGenerateRAMmaximum available RAM (bytes) for genome generationlong, example: NA
--limitIObufferSizemax available buffers size (bytes) for input/output, per threadlong, example: 30000000, example: 50000000
--limitOutSAMoneReadBytesmax size of the SAM record (bytes) for one read. Recommended value: >(2(LengthMate1+LengthMate2+100)outFilterMultimapNmaxlong, example: 100000
--limitOutSJoneReadmax number of junctions for one read (including all multi-mappers)integer, example: 1000
--limitOutSJcollapsedmax number of collapsed junctionsinteger, example: 1000000
--limitBAMsortRAMmaximum available RAM (bytes) for sorting BAM. If =0, it will be set to the genome index size. 0 value can only be used with –genomeLoad NoSharedMemory option.long, example: 0
--limitSjdbInsertNsjmaximum number of junctions to be inserted to the genome on the fly at the mapping stage, including those from annotations and those detected in the 1st step of the 2-pass runinteger, example: 1000000
--limitNreadsSoftsoft limit on the number of readsinteger, example: -1
+
+
+

Output: general

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outTmpKeepwhether to keep the temporary files after STAR runs is finished - None … remove all temporary files - All … keep all filesstring
--outStdwhich output will be directed to stdout (standard out) - Log … log messages - SAM … alignments in SAM format (which normally are output to Aligned.out.sam file), normal standard output will go into Log.std.out - BAM_Unsorted … alignments in BAM format, unsorted. Requires –outSAMtype BAM Unsorted - BAM_SortedByCoordinate … alignments in BAM format, sorted by coordinate. Requires –outSAMtype BAM SortedByCoordinate - BAM_Quant … alignments to transcriptome in BAM format, unsorted. Requires –quantMode TranscriptomeSAMstring, example: "Log"
--outReadsUnmappedoutput of unmapped and partially mapped (i.e. mapped only one mate of a paired end read) reads in separate file(s). - None … no output - Fastx … output in separate fasta/fastq files, Unmapped.out.mate1/2string
--outQSconversionAddadd this number to the quality score (e.g. to convert from Illumina to Sanger, use -31)integer, example: 0
--outMultimapperOrderorder of multimapping alignments in the output files - Old_2.4 … quasi-random order used before 2.5.0 - Random … random order of alignments for each multi-mapper. Read mates (pairs) are always adjacent, all alignment for each read stay together. This option will become default in the future releases.string, example: "Old_2.4"
+
+
+

Output: SAM and BAM

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outSAMtypetype of SAM/BAM output 1st word: - BAM … output BAM without sorting - SAM … output SAM without sorting - None … no SAM/BAM output 2nd, 3rd: - Unsorted … standard unsorted - SortedByCoordinate … sorted by coordinate. This option will allocate extra memory for sorting which can be specified by –limitBAMsortRAM.string, example: "SAM"
--outSAMmodemode of SAM output - None … no SAM output - Full … full SAM output - NoQS … full SAM but without quality scoresstring, example: "Full"
--outSAMstrandFieldCufflinks-like strand field flag - None … not used - intronMotif … strand derived from the intron motif. This option changes the output alignments: reads with inconsistent and/or non-canonical introns are filtered out.string
--outSAMattributesa string of desired SAM attributes, in the order desired for the output SAM. Tags can be listed in any combination/order. Presets: - None … no attributes - Standard … NH HI AS nM - All … NH HI AS nM NM MD jM jI MC ch Alignment: - NH … number of loci the reads maps to: =1 for unique mappers, >1 for multimappers. Standard SAM tag. - HI … multiple alignment index, starts with –outSAMattrIHstart (=1 by default). Standard SAM tag. - AS … local alignment score, +1/-1 for matches/mismateches, score* penalties for indels and gaps. For PE reads, total score for two mates. Stadnard SAM tag. - nM … number of mismatches. For PE reads, sum over two mates. - NM … edit distance to the reference (number of mismatched + inserted + deleted bases) for each mate. Standard SAM tag. - MD … string encoding mismatched and deleted reference bases (see standard SAM specifications). Standard SAM tag. - jM … intron motifs for all junctions (i.e. N in CIGAR): 0: non-canonical; 1: GT/AG, 2: CT/AC, 3: GC/AG, 4: CT/GC, 5: AT/AC, 6: GT/AT. If splice junctions database is used, and a junction is annotated, 20 is added to its motif value. - jI … start and end of introns for all junctions (1-based). - XS … alignment strand according to –outSAMstrandField. - MC … mate’s CIGAR string. Standard SAM tag. - ch … marks all segment of all chimeric alingments for –chimOutType WithinBAM output. - cN … number of bases clipped from the read ends: 5’ and 3’ Variation: - vA … variant allele - vG … genomic coordinate of the variant overlapped by the read. - vW … 1 - alignment passes WASP filtering; 2,3,4,5,6,7 - alignment does not pass WASP filtering. Requires –waspOutputMode SAMtag. STARsolo: - CR CY UR UY … sequences and quality scores of cell barcodes and UMIs for the solo* demultiplexing. - GX GN … gene ID and gene name for unique-gene reads. - gx gn … gene IDs and gene names for unique- and multi-gene reads. - CB UB … error-corrected cell barcodes and UMIs for solo* demultiplexing. Requires –outSAMtype BAM SortedByCoordinate. - sM … assessment of CB and UMI. - sS … sequence of the entire barcode (CB,UMI,adapter). - sQ … quality of the entire barcode. ***Unsupported/undocumented: - ha … haplotype (1/2) when mapping to the diploid genome. Requires genome generated with –genomeTransformType Diploid . - rB … alignment block read/genomic coordinates. - vR … read coordinate of the variant.string, example: "Standard"
--outSAMattrIHstartstart value for the IH attribute. 0 may be required by some downstream software, such as Cufflinks or StringTie.integer, example: 1
--outSAMunmappedoutput of unmapped reads in the SAM format 1st word: - None … no output - Within … output unmapped reads within the main SAM file (i.e. Aligned.out.sam) 2nd word: - KeepPairs … record unmapped mate for each alignment, and, in case of unsorted output, keep it adjacent to its mapped mate. Only affects multi-mapping reads.string
--outSAMordertype of sorting for the SAM output Paired: one mate after the other for all paired alignments PairedKeepInputOrder: one mate after the other for all paired alignments, the order is kept the same as in the input FASTQ filesstring, example: "Paired"
--outSAMprimaryFlagwhich alignments are considered primary - all others will be marked with 0x100 bit in the FLAG - OneBestScore … only one alignment with the best score is primary - AllBestScore … all alignments with the best score are primarystring, example: "OneBestScore"
--outSAMreadIDread ID record type - Standard … first word (until space) from the FASTx read ID line, removing /1,/2 from the end - Number … read number (index) in the FASTx filestring, example: "Standard"
--outSAMmapqUnique0 to 255: the MAPQ value for unique mappersinteger, example: 255
--outSAMflagOR0 to 65535: sam FLAG will be bitwise OR’d with this value, i.e. FLAG=FLAG | outSAMflagOR. This is applied after all flags have been set by STAR, and after outSAMflagAND. Can be used to set specific bits that are not set otherwise.integer, example: 0
--outSAMflagAND0 to 65535: sam FLAG will be bitwise AND’d with this value, i.e. FLAG=FLAG & outSAMflagOR. This is applied after all flags have been set by STAR, but before outSAMflagOR. Can be used to unset specific bits that are not set otherwise.integer, example: 65535
--outSAMattrRGlineSAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”. xxx will be added as RG tag to each output alignment. Any spaces in the tag values have to be double quoted. Comma separated RG lines correspons to different (comma separated) input files in –readFilesIn. Commas have to be surrounded by spaces, e.g. –outSAMattrRGline ID:xxx , ID:zzz “DS:z z” , ID:yyy DS:yyyystring
--outSAMheaderHD@HD (header) line of the SAM headerstring
--outSAMheaderPGextra @PG (software) line of the SAM header (in addition to STAR)string
--outSAMheaderCommentFilepath to the file with @CO (comment) lines of the SAM headerstring
--outSAMfilterfilter the output into main SAM/BAM files - KeepOnlyAddedReferences … only keep the reads for which all alignments are to the extra reference sequences added with –genomeFastaFiles at the mapping stage. - KeepAllAddedReferences … keep all alignments to the extra reference sequences added with –genomeFastaFiles at the mapping stage.string
--outSAMmultNmaxmax number of multiple alignments for a read that will be output to the SAM/BAM files. Note that if this value is not equal to -1, the top scoring alignment will be output first - -1 … all alignments (up to –outFilterMultimapNmax) will be outputinteger, example: -1
--outSAMtlencalculation method for the TLEN field in the SAM/BAM files - 1 … leftmost base of the (+)strand mate to rightmost base of the (-)mate. (+)sign for the (+)strand mate - 2 … leftmost base of any mate to rightmost base of any mate. (+)sign for the mate with the leftmost base. This is different from 1 for overlapping mates with protruding endsinteger, example: 1
--outBAMcompression-1 to 10 BAM compression level, -1=default compression (6?), 0=no compression, 10=maximum compressioninteger, example: 1
--outBAMsortingThreadN>=0: number of threads for BAM sorting. 0 will default to min(6,–runThreadN).integer, example: 0
--outBAMsortingBinsN>0: number of genome bins for coordinate-sortinginteger, example: 50
+
+
+

BAM processing

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--bamRemoveDuplicatesTypemark duplicates in the BAM file, for now only works with (i) sorted BAM fed with inputBAMfile, and (ii) for paired-end alignments only - - … no duplicate removal/marking - UniqueIdentical … mark all multimappers, and duplicate unique mappers. The coordinates, FLAG, CIGAR must be identical - UniqueIdenticalNotMulti … mark duplicate unique mappers but not multimappers.string
--bamRemoveDuplicatesMate2basesNnumber of bases from the 5’ of mate 2 to use in collapsing (e.g. for RAMPAGE)integer, example: 0
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Output Wiggle

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NameDescriptionAttributes
--outWigTypetype of signal output, e.g. “bedGraph” OR “bedGraph read1_5p”. Requires sorted BAM: –outSAMtype BAM SortedByCoordinate . 1st word: - None … no signal output - bedGraph … bedGraph format - wiggle … wiggle format 2nd word: - read1_5p … signal from only 5’ of the 1st read, useful for CAGE/RAMPAGE etc - read2 … signal from only 2nd readstring
--outWigStrandstrandedness of wiggle/bedGraph output - Stranded … separate strands, str1 and str2 - Unstranded … collapsed strandsstring, example: "Stranded"
--outWigReferencesPrefixprefix matching reference names to include in the output wiggle file, e.g. “chr”, default “-” - include all referencesstring
--outWigNormtype of normalization for the signal - RPM … reads per million of mapped reads - None … no normalization, “raw” countsstring, example: "RPM"
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Output Filtering

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NameDescriptionAttributes
--outFilterTypetype of filtering - Normal … standard filtering using only current alignment - BySJout … keep only those reads that contain junctions that passed filtering into SJ.out.tabstring, example: "Normal"
--outFilterMultimapScoreRangethe score range below the maximum score for multimapping alignmentsinteger, example: 1
--outFilterMultimapNmaxmaximum number of loci the read is allowed to map to. Alignments (all of them) will be output only if the read maps to no more loci than this value. Otherwise no alignments will be output, and the read will be counted as “mapped to too many loci” in the Log.final.out .integer, example: 10
--outFilterMismatchNmaxalignment will be output only if it has no more mismatches than this value.integer, example: 10
--outFilterMismatchNoverLmaxalignment will be output only if its ratio of mismatches to mapped length is less than or equal to this value.double, example: 0.3
--outFilterMismatchNoverReadLmaxalignment will be output only if its ratio of mismatches to read length is less than or equal to this value.double, example: 1
--outFilterScoreMinalignment will be output only if its score is higher than or equal to this value.integer, example: 0
--outFilterScoreMinOverLreadsame as outFilterScoreMin, but normalized to read length (sum of mates’ lengths for paired-end reads)double, example: 0.66
--outFilterMatchNminalignment will be output only if the number of matched bases is higher than or equal to this value.integer, example: 0
--outFilterMatchNminOverLreadsam as outFilterMatchNmin, but normalized to the read length (sum of mates’ lengths for paired-end reads).double, example: 0.66
--outFilterIntronMotifsfilter alignment using their motifs - None … no filtering - RemoveNoncanonical … filter out alignments that contain non-canonical junctions - RemoveNoncanonicalUnannotated … filter out alignments that contain non-canonical unannotated junctions when using annotated splice junctions database. The annotated non-canonical junctions will be kept.string
--outFilterIntronStrandsfilter alignments - RemoveInconsistentStrands … remove alignments that have junctions with inconsistent strands - None … no filteringstring, example: "RemoveInconsistentStrands"
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Output splice junctions (SJ.out.tab)

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NameDescriptionAttributes
--outSJtypetype of splice junction output - Standard … standard SJ.out.tab output - None … no splice junction outputstring, example: "Standard"
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Output Filtering: Splice Junctions

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NameDescriptionAttributes
--outSJfilterReadswhich reads to consider for collapsed splice junctions output - All … all reads, unique- and multi-mappers - Unique … uniquely mapping reads onlystring, example: "All"
--outSJfilterOverhangMinminimum overhang length for splice junctions on both sides for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif does not apply to annotated junctionsinteger, example: 30, example: 12, example: 12, example: 12
--outSJfilterCountUniqueMinminimum uniquely mapping read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctionsinteger, example: 3, example: 1, example: 1, example: 1
--outSJfilterCountTotalMinminimum total (multi-mapping+unique) read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctionsinteger, example: 3, example: 1, example: 1, example: 1
--outSJfilterDistToOtherSJminminimum allowed distance to other junctions’ donor/acceptor does not apply to annotated junctionsinteger, example: 10, example: 0, example: 5, example: 10
--outSJfilterIntronMaxVsReadNmaximum gap allowed for junctions supported by 1,2,3,,,N reads i.e. by default junctions supported by 1 read can have gaps <=50000b, by 2 reads: <=100000b, by 3 reads: <=200000. by >=4 reads any gap <=alignIntronMax does not apply to annotated junctionsinteger, example: 50000, example: 100000, example: 200000
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Scoring

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NameDescriptionAttributes
--scoreGapsplice junction penalty (independent on intron motif)integer, example: 0
--scoreGapNoncannon-canonical junction penalty (in addition to scoreGap)integer, example: -8
--scoreGapGCAGGC/AG and CT/GC junction penalty (in addition to scoreGap)integer, example: -4
--scoreGapATACAT/AC and GT/AT junction penalty (in addition to scoreGap)integer, example: -8
--scoreGenomicLengthLog2scaleextra score logarithmically scaled with genomic length of the alignment: scoreGenomicLengthLog2scale*log2(genomicLength)integer, example: 0
--scoreDelOpendeletion open penaltyinteger, example: -2
--scoreDelBasedeletion extension penalty per base (in addition to scoreDelOpen)integer, example: -2
--scoreInsOpeninsertion open penaltyinteger, example: -2
--scoreInsBaseinsertion extension penalty per base (in addition to scoreInsOpen)integer, example: -2
--scoreStitchSJshiftmaximum score reduction while searching for SJ boundaries in the stitching stepinteger, example: 1
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Alignments and Seeding

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NameDescriptionAttributes
--seedSearchStartLmaxdefines the search start point through the read - the read is split into pieces no longer than this valueinteger, example: 50
--seedSearchStartLmaxOverLreadseedSearchStartLmax normalized to read length (sum of mates’ lengths for paired-end reads)double, example: 1
--seedSearchLmaxdefines the maximum length of the seeds, if =0 seed length is not limitedinteger, example: 0
--seedMultimapNmaxonly pieces that map fewer than this value are utilized in the stitching procedureinteger, example: 10000
--seedPerReadNmaxmax number of seeds per readinteger, example: 1000
--seedPerWindowNmaxmax number of seeds per windowinteger, example: 50
--seedNoneLociPerWindowmax number of one seed loci per windowinteger, example: 10
--seedSplitMinmin length of the seed sequences split by Ns or mate gapinteger, example: 12
--seedMapMinmin length of seeds to be mappedinteger, example: 5
--alignIntronMinminimum intron size, genomic gap is considered intron if its length>=alignIntronMin, otherwise it is considered Deletioninteger, example: 21
--alignIntronMaxmaximum intron size, if 0, max intron size will be determined by (2^winBinNbits)*winAnchorDistNbinsinteger, example: 0
--alignMatesGapMaxmaximum gap between two mates, if 0, max intron gap will be determined by (2^winBinNbits)*winAnchorDistNbinsinteger, example: 0
--alignSJoverhangMinminimum overhang (i.e. block size) for spliced alignmentsinteger, example: 5
--alignSJstitchMismatchNmaxmaximum number of mismatches for stitching of the splice junctions (-1: no limit). (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif.integer, example: 0, example: -1, example: 0, example: 0
--alignSJDBoverhangMinminimum overhang (i.e. block size) for annotated (sjdb) spliced alignmentsinteger, example: 3
--alignSplicedMateMapLminminimum mapped length for a read mate that is splicedinteger, example: 0
--alignSplicedMateMapLminOverLmatealignSplicedMateMapLmin normalized to mate lengthdouble, example: 0.66
--alignWindowsPerReadNmaxmax number of windows per readinteger, example: 10000
--alignTranscriptsPerWindowNmaxmax number of transcripts per windowinteger, example: 100
--alignTranscriptsPerReadNmaxmax number of different alignments per read to considerinteger, example: 10000
--alignEndsTypetype of read ends alignment - Local … standard local alignment with soft-clipping allowed - EndToEnd … force end-to-end read alignment, do not soft-clip - Extend5pOfRead1 … fully extend only the 5p of the read1, all other ends: local alignment - Extend5pOfReads12 … fully extend only the 5p of the both read1 and read2, all other ends: local alignmentstring, example: "Local"
--alignEndsProtrudeallow protrusion of alignment ends, i.e. start (end) of the +strand mate downstream of the start (end) of the -strand mate 1st word: int: maximum number of protrusion bases allowed 2nd word: string: - ConcordantPair … report alignments with non-zero protrusion as concordant pairs - DiscordantPair … report alignments with non-zero protrusion as discordant pairsstring, example: "0 ConcordantPair"
--alignSoftClipAtReferenceEndsallow the soft-clipping of the alignments past the end of the chromosomes - Yes … allow - No … prohibit, useful for compatibility with Cufflinksstring, example: "Yes"
--alignInsertionFlushhow to flush ambiguous insertion positions - None … insertions are not flushed - Right … insertions are flushed to the rightstring
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Paired-End reads

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NameDescriptionAttributes
--peOverlapNbasesMinminimum number of overlapping bases to trigger mates merging and realignment. Specify >0 value to switch on the “merginf of overlapping mates” algorithm.integer, example: 0
--peOverlapMMpmaximum proportion of mismatched bases in the overlap areadouble, example: 0.01
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Windows, Anchors, Binning

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NameDescriptionAttributes
--winAnchorMultimapNmaxmax number of loci anchors are allowed to map tointeger, example: 50
--winBinNbits=log2(winBin), where winBin is the size of the bin for the windows/clustering, each window will occupy an integer number of bins.integer, example: 16
--winAnchorDistNbinsmax number of bins between two anchors that allows aggregation of anchors into one windowinteger, example: 9
--winFlankNbinslog2(winFlank), where win Flank is the size of the left and right flanking regions for each windowinteger, example: 4
--winReadCoverageRelativeMinminimum relative coverage of the read sequence by the seeds in a window, for STARlong algorithm only.double, example: 0.5
--winReadCoverageBasesMinminimum number of bases covered by the seeds in a window , for STARlong algorithm only.integer, example: 0
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Chimeric Alignments

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NameDescriptionAttributes
--chimOutTypetype of chimeric output - Junctions … Chimeric.out.junction - SeparateSAMold … output old SAM into separate Chimeric.out.sam file - WithinBAM … output into main aligned BAM files (Aligned.*.bam) - WithinBAM HardClip … (default) hard-clipping in the CIGAR for supplemental chimeric alignments (default if no 2nd word is present) - WithinBAM SoftClip … soft-clipping in the CIGAR for supplemental chimeric alignmentsstring, example: "Junctions"
--chimSegmentMinminimum length of chimeric segment length, if ==0, no chimeric outputinteger, example: 0
--chimScoreMinminimum total (summed) score of the chimeric segmentsinteger, example: 0
--chimScoreDropMaxmax drop (difference) of chimeric score (the sum of scores of all chimeric segments) from the read lengthinteger, example: 20
--chimScoreSeparationminimum difference (separation) between the best chimeric score and the next oneinteger, example: 10
--chimScoreJunctionNonGTAGpenalty for a non-GT/AG chimeric junctioninteger, example: -1
--chimJunctionOverhangMinminimum overhang for a chimeric junctioninteger, example: 20
--chimSegmentReadGapMaxmaximum gap in the read sequence between chimeric segmentsinteger, example: 0
--chimFilterdifferent filters for chimeric alignments - None … no filtering - banGenomicN … Ns are not allowed in the genome sequence around the chimeric junctionstring, example: "banGenomicN"
--chimMainSegmentMultNmaxmaximum number of multi-alignments for the main chimeric segment. =1 will prohibit multimapping main segments.integer, example: 10
--chimMultimapNmaxmaximum number of chimeric multi-alignments - 0 … use the old scheme for chimeric detection which only considered unique alignmentsinteger, example: 0
--chimMultimapScoreRangethe score range for multi-mapping chimeras below the best chimeric score. Only works with –chimMultimapNmax > 1integer, example: 1
--chimNonchimScoreDropMinto trigger chimeric detection, the drop in the best non-chimeric alignment score with respect to the read length has to be greater than this valueinteger, example: 20
--chimOutJunctionFormatformatting type for the Chimeric.out.junction file - 0 … no comment lines/headers - 1 … comment lines at the end of the file: command line and Nreads: total, unique/multi-mappinginteger, example: 0
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Quantification of Annotations

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NameDescriptionAttributes
--quantModetypes of quantification requested - - … none - TranscriptomeSAM … output SAM/BAM alignments to transcriptome into a separate file - GeneCounts … count reads per genestring
--quantTranscriptomeBAMcompression-2 to 10 transcriptome BAM compression level - -2 … no BAM output - -1 … default compression (6?) - 0 … no compression - 10 … maximum compressioninteger, example: 1
--quantTranscriptomeBanprohibit various alignment type - IndelSoftclipSingleend … prohibit indels, soft clipping and single-end alignments - compatible with RSEM - Singleend … prohibit single-end alignmentsstring, example: "IndelSoftclipSingleend"
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2-pass Mapping

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NameDescriptionAttributes
--twopassMode2-pass mapping mode. - None … 1-pass mapping - Basic … basic 2-pass mapping, with all 1st pass junctions inserted into the genome indices on the flystring
--twopass1readsNnumber of reads to process for the 1st step. Use very large number (or default -1) to map all reads in the first step.integer, example: -1
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WASP parameters

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NameDescriptionAttributes
--waspOutputModeWASP allele-specific output type. This is re-implementation of the original WASP mappability filtering by Bryce van de Geijn, Graham McVicker, Yoav Gilad & Jonathan K Pritchard. Please cite the original WASP paper: Nature Methods 12, 1061-1063 (2015), https://www.nature.com/articles/nmeth.3582 . - SAMtag … add WASP tags to the alignments that pass WASP filteringstring
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STARsolo (single cell RNA-seq) parameters

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NameDescriptionAttributes
--soloTypetype of single-cell RNA-seq - CB_UMI_Simple … (a.k.a. Droplet) one UMI and one Cell Barcode of fixed length in read2, e.g. Drop-seq and 10X Chromium. - CB_UMI_Complex … multiple Cell Barcodes of varying length, one UMI of fixed length and one adapter sequence of fixed length are allowed in read2 only (e.g. inDrop, ddSeq). - CB_samTagOut … output Cell Barcode as CR and/or CB SAm tag. No UMI counting. –readFilesIn cDNA_read1 [cDNA_read2 if paired-end] CellBarcode_read . Requires –outSAMtype BAM Unsorted [and/or SortedByCoordinate] - SmartSeq … Smart-seq: each cell in a separate FASTQ (paired- or single-end), barcodes are corresponding read-groups, no UMI sequences, alignments deduplicated according to alignment start and end (after extending soft-clipped bases)string
--soloCBwhitelistfile(s) with whitelist(s) of cell barcodes. Only –soloType CB_UMI_Complex allows more than one whitelist file. - None … no whitelist: all cell barcodes are allowedstring
--soloCBstartcell barcode start baseinteger, example: 1
--soloCBlencell barcode lengthinteger, example: 16
--soloUMIstartUMI start baseinteger, example: 17
--soloUMIlenUMI lengthinteger, example: 10
--soloBarcodeReadLengthlength of the barcode read - 1 … equal to sum of soloCBlen+soloUMIlen - 0 … not defined, do not checkinteger, example: 1
--soloBarcodeMateidentifies which read mate contains the barcode (CB+UMI) sequence - 0 … barcode sequence is on separate read, which should always be the last file in the –readFilesIn listed - 1 … barcode sequence is a part of mate 1 - 2 … barcode sequence is a part of mate 2integer, example: 0
--soloCBpositionposition of Cell Barcode(s) on the barcode read. Presently only works with –soloType CB_UMI_Complex, and barcodes are assumed to be on Read2. Format for each barcode: startAnchor_startPosition_endAnchor_endPosition start(end)Anchor defines the Anchor Base for the CB: 0: read start; 1: read end; 2: adapter start; 3: adapter end start(end)Position is the 0-based position with of the CB start(end) with respect to the Anchor Base String for different barcodes are separated by space. Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 0_0_2_-1 3_1_3_8string
--soloUMIpositionposition of the UMI on the barcode read, same as soloCBposition Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 3_9_3_14string
--soloAdapterSequenceadapter sequence to anchor barcodes. Only one adapter sequence is allowed.string
--soloAdapterMismatchesNmaxmaximum number of mismatches allowed in adapter sequence.integer, example: 1
--soloCBmatchWLtypematching the Cell Barcodes to the WhiteList - Exact … only exact matches allowed - 1MM … only one match in whitelist with 1 mismatched base allowed. Allowed CBs have to have at least one read with exact match. - 1MM_multi … multiple matches in whitelist with 1 mismatched base allowed, posterior probability calculation is used choose one of the matches. Allowed CBs have to have at least one read with exact match. This option matches best with CellRanger 2.2.0 - 1MM_multi_pseudocounts … same as 1MM_Multi, but pseudocounts of 1 are added to all whitelist barcodes. - 1MM_multi_Nbase_pseudocounts … same as 1MM_multi_pseudocounts, multimatching to WL is allowed for CBs with N-bases. This option matches best with CellRanger >= 3.0.0 - EditDist_2 … allow up to edit distance of 3 fpr each of the barcodes. May include one deletion + one insertion. Only works with –soloType CB_UMI_Complex. Matches to multiple passlist barcdoes are not allowed. Similar to ParseBio Split-seq pipeline.string, example: "1MM_multi"
--soloInputSAMattrBarcodeSeqwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode sequence (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeSeq CR UR . This parameter is required when running STARsolo with input from SAM.string
--soloInputSAMattrBarcodeQualwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode qualities (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeQual CY UY . If this parameter is ‘-’ (default), the quality ‘H’ will be assigned to all bases.string
--soloStrandstrandedness of the solo libraries: - Unstranded … no strand information - Forward … read strand same as the original RNA molecule - Reverse … read strand opposite to the original RNA moleculestring, example: "Forward"
--soloFeaturesgenomic features for which the UMI counts per Cell Barcode are collected - Gene … genes: reads match the gene transcript - SJ … splice junctions: reported in SJ.out.tab - GeneFull … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns - GeneFull_ExonOverIntron … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns: prioritize 100% overlap with exons - GeneFull_Ex50pAS … full gene (pre-RNA): count all reads overlapping genes’ exons and introns: prioritize >50% overlap with exons. Do not count reads with 100% exonic overlap in the antisense direction.string, example: "Gene"
--soloMultiMapperscounting method for reads mapping to multiple genes - Unique … count only reads that map to unique genes - Uniform … uniformly distribute multi-genic UMIs to all genes - Rescue … distribute UMIs proportionally to unique+uniform counts (~ first iteration of EM) - PropUnique … distribute UMIs proportionally to unique mappers, if present, and uniformly if not. - EM … multi-gene UMIs are distributed using Expectation Maximization algorithmstring, example: "Unique"
--soloUMIdeduptype of UMI deduplication (collapsing) algorithm - 1MM_All … all UMIs with 1 mismatch distance to each other are collapsed (i.e. counted once). - 1MM_Directional_UMItools … follows the “directional” method from the UMI-tools by Smith, Heger and Sudbery (Genome Research 2017). - 1MM_Directional … same as 1MM_Directional_UMItools, but with more stringent criteria for duplicate UMIs - Exact … only exactly matching UMIs are collapsed. - NoDedup … no deduplication of UMIs, count all reads. - 1MM_CR … CellRanger2-4 algorithm for 1MM UMI collapsing.string, example: "1MM_All"
--soloUMIfilteringtype of UMI filtering (for reads uniquely mapping to genes) - - … basic filtering: remove UMIs with N and homopolymers (similar to CellRanger 2.2.0). - MultiGeneUMI … basic + remove lower-count UMIs that map to more than one gene. - MultiGeneUMI_All … basic + remove all UMIs that map to more than one gene. - MultiGeneUMI_CR … basic + remove lower-count UMIs that map to more than one gene, matching CellRanger > 3.0.0 . Only works with –soloUMIdedup 1MM_CRstring
--soloOutFileNamesfile names for STARsolo output: file_name_prefix gene_names barcode_sequences cell_feature_count_matrixstring, example: "Solo.out/", example: "features.tsv", example: "barcodes.tsv", example: "matrix.mtx"
--soloCellFiltercell filtering type and parameters - None … do not output filtered cells - TopCells … only report top cells by UMI count, followed by the exact number of cells - CellRanger2.2 … simple filtering of CellRanger 2.2. Can be followed by numbers: number of expected cells, robust maximum percentile for UMI count, maximum to minimum ratio for UMI count The harcoded values are from CellRanger: nExpectedCells=3000; maxPercentile=0.99; maxMinRatio=10 - EmptyDrops_CR … EmptyDrops filtering in CellRanger flavor. Please cite the original EmptyDrops paper: A.T.L Lun et al, Genome Biology, 20, 63 (2019): https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1662-y Can be followed by 10 numeric parameters: nExpectedCells maxPercentile maxMinRatio indMin indMax umiMin umiMinFracMedian candMaxN FDR simN The harcoded values are from CellRanger: 3000 0.99 10 45000 90000 500 0.01 20000 0.01 10000string, example: "CellRanger2.2", example: "3000", example: "0.99", example: "10"
--soloOutFormatFeaturesGeneField3field 3 in the Gene features.tsv file. If “-”, then no 3rd field is output.string, example: "Gene Expression"
--soloCellReadStatsOutput reads statistics for each CB - Standard … standard outputstring
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Authors

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  • Angela Oliveira Pisco (author)

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  • Robrecht Cannoodt (author, maintainer)

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Star align v273a

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+ Align fastq files using STAR. +
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Info

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ID: star_align_v273a
+Namespace: mapping

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Example commands

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You can run the pipeline using nextflow run.

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View help

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You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/star_align_v273a/main.nf \
+  --help
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+

Run command

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+ +Example of params.yaml + +
# Input/Output
+input: # please fill in - example: ["mysample_S1_L001_R1_001.fastq.gz", "mysample_S1_L001_R2_001.fastq.gz"]
+reference: # please fill in - example: "/path/to/reference"
+# output: "$id.$key.output.output"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/star_align_v273a/main.nf \
+  -params-file params.yaml
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Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

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Argument groups

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Input/Output

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NameDescriptionAttributes
--inputThe FASTQ files to be analyzed. Corresponds to the –readFilesIn in the STAR command.file, required, example: "mysample_S1_L001_R1_001.fastq.gz", example: "mysample_S1_L001_R2_001.fastq.gz"
--referencePath to the reference built by star_build_reference. Corresponds to the –genomeDir in the STAR command.file, required, example: "/path/to/reference"
--outputPath to output directory. Corresponds to the –outFileNamePrefix in the STAR command.file, required, example: "/path/to/foo"
+
+
+

Run Parameters

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NameDescriptionAttributes
--runRNGseedrandom number generator seed.integer, example: 777
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+
+

Genome Parameters

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NameDescriptionAttributes
--genomeLoadmode of shared memory usage for the genome files. Only used with –runMode alignReads. - LoadAndKeep … load genome into shared and keep it in memory after run - LoadAndRemove … load genome into shared but remove it after run - LoadAndExit … load genome into shared memory and exit, keeping the genome in memory for future runs - Remove … do not map anything, just remove loaded genome from memory - NoSharedMemory … do not use shared memory, each job will have its own private copy of the genomestring, example: "NoSharedMemory"
--genomeFastaFilespath(s) to the fasta files with the genome sequences, separated by spaces. These files should be plain text FASTA files, they cannot be zipped. Required for the genome generation (–runMode genomeGenerate). Can also be used in the mapping (–runMode alignReads) to add extra (new) sequences to the genome (e.g. spike-ins).file
--genomeFileSizesgenome files exact sizes in bytes. Typically, this should not be defined by the user.integer, example: 0
--genomeTransformOutputwhich output to transform back to original genome - SAM … SAM/BAM alignments - SJ … splice junctions (SJ.out.tab) - None … no transformation of the outputstring
--genomeChrSetMitochondrialnames of the mitochondrial chromosomes. Presently only used for STARsolo statistics output/string, example: "chrM", example: "M", example: "MT"
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+
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Splice Junctions Database

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NameDescriptionAttributes
--sjdbFileChrStartEndpath to the files with genomic coordinates (chr start end strand) for the splice junction introns. Multiple files can be supplied and will be concatenated.string
--sjdbGTFfilepath to the GTF file with annotationsfile
--sjdbGTFchrPrefixprefix for chromosome names in a GTF file (e.g. ‘chr’ for using ENSMEBL annotations with UCSC genomes)string
--sjdbGTFfeatureExonfeature type in GTF file to be used as exons for building transcriptsstring, example: "exon"
--sjdbGTFtagExonParentTranscriptGTF attribute name for parent transcript ID (default “transcript_id” works for GTF files)string, example: "transcript_id"
--sjdbGTFtagExonParentGeneGTF attribute name for parent gene ID (default “gene_id” works for GTF files)string, example: "gene_id"
--sjdbGTFtagExonParentGeneNameGTF attribute name for parent gene namestring, example: "gene_name"
--sjdbGTFtagExonParentGeneTypeGTF attribute name for parent gene typestring, example: "gene_type", example: "gene_biotype"
--sjdbOverhanglength of the donor/acceptor sequence on each side of the junctions, ideally = (mate_length - 1)integer, example: 100
--sjdbScoreextra alignment score for alignments that cross database junctionsinteger, example: 2
--sjdbInsertSavewhich files to save when sjdb junctions are inserted on the fly at the mapping step - Basic … only small junction / transcript files - All … all files including big Genome, SA and SAindex - this will create a complete genome directorystring, example: "Basic"
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Variation parameters

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NameDescriptionAttributes
--varVCFfilepath to the VCF file that contains variation data. The 10th column should contain the genotype information, e.g. 0/1string
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+
+

Read Parameters

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NameDescriptionAttributes
--readFilesTypeformat of input read files - Fastx … FASTA or FASTQ - SAM SE … SAM or BAM single-end reads; for BAM use –readFilesCommand samtools view - SAM PE … SAM or BAM paired-end reads; for BAM use –readFilesCommand samtools viewstring, example: "Fastx"
--readFilesSAMattrKeepfor –readFilesType SAM SE/PE, which SAM tags to keep in the output BAM, e.g.: –readFilesSAMtagsKeep RG PL - All … keep all tags - None … do not keep any tagsstring, example: "All"
--readFilesManifestpath to the “manifest” file with the names of read files. The manifest file should contain 3 tab-separated columns: paired-end reads: read1_file_name \(tab\) read2_file_name \(tab\) read_group_line. single-end reads: read1_file_name \(tab\) - \(tab\) read_group_line. Spaces, but not tabs are allowed in file names. If read_group_line does not start with ID:, it can only contain one ID field, and ID: will be added to it. If read_group_line starts with ID:, it can contain several fields separated by \(tab\), and all fields will be be copied verbatim into SAM @RG header line.file
--readFilesPrefixprefix for the read files names, i.e. it will be added in front of the strings in –readFilesInstring
--readFilesCommandcommand line to execute for each of the input file. This command should generate FASTA or FASTQ text and send it to stdout For example: zcat - to uncompress .gz files, bzcat - to uncompress .bz2 files, etc.string
--readMapNumbernumber of reads to map from the beginning of the file -1: map all readsinteger, example: -1
--readMatesLengthsInEqual/NotEqual - lengths of names,sequences,qualities for both mates are the same / not the same. NotEqual is safe in all situations.string, example: "NotEqual"
--readNameSeparatorcharacter(s) separating the part of the read names that will be trimmed in output (read name after space is always trimmed)string, example: "/"
--readQualityScoreBasenumber to be subtracted from the ASCII code to get Phred quality scoreinteger, example: 33
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+

Read Clipping

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NameDescriptionAttributes
--clipAdapterTypeadapter clipping type - Hamming … adapter clipping based on Hamming distance, with the number of mismatches controlled by –clip5pAdapterMMp - CellRanger4 … 5p and 3p adapter clipping similar to CellRanger4. Utilizes Opal package by Martin Sosic: https://github.com/Martinsos/opal - None … no adapter clipping, all other clip* parameters are disregardedstring, example: "Hamming"
--clip3pNbasesnumber(s) of bases to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates.integer, example: 0
--clip3pAdapterSeqadapter sequences to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates. - polyA … polyA sequence with the length equal to read lengthstring
--clip3pAdapterMMpmax proportion of mismatches for 3p adapter clipping for each mate. If one value is given, it will be assumed the same for both mates.double, example: 0.1
--clip3pAfterAdapterNbasesnumber of bases to clip from 3p of each mate after the adapter clipping. If one value is given, it will be assumed the same for both mates.integer, example: 0
--clip5pNbasesnumber(s) of bases to clip from 5p of each mate. If one value is given, it will be assumed the same for both mates.integer, example: 0
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Limits

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NameDescriptionAttributes
--limitGenomeGenerateRAMmaximum available RAM (bytes) for genome generationlong, example: NA
--limitIObufferSizemax available buffers size (bytes) for input/output, per threadlong, example: 30000000, example: 50000000
--limitOutSAMoneReadBytesmax size of the SAM record (bytes) for one read. Recommended value: >(2(LengthMate1+LengthMate2+100)outFilterMultimapNmaxlong, example: 100000
--limitOutSJoneReadmax number of junctions for one read (including all multi-mappers)integer, example: 1000
--limitOutSJcollapsedmax number of collapsed junctionsinteger, example: 1000000
--limitBAMsortRAMmaximum available RAM (bytes) for sorting BAM. If =0, it will be set to the genome index size. 0 value can only be used with –genomeLoad NoSharedMemory option.long, example: 0
--limitSjdbInsertNsjmaximum number of junctions to be inserted to the genome on the fly at the mapping stage, including those from annotations and those detected in the 1st step of the 2-pass runinteger, example: 1000000
--limitNreadsSoftsoft limit on the number of readsinteger, example: -1
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+

Output: general

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NameDescriptionAttributes
--outTmpKeepwhether to keep the temporary files after STAR runs is finished - None … remove all temporary files - All … keep all filesstring
--outStdwhich output will be directed to stdout (standard out) - Log … log messages - SAM … alignments in SAM format (which normally are output to Aligned.out.sam file), normal standard output will go into Log.std.out - BAM_Unsorted … alignments in BAM format, unsorted. Requires –outSAMtype BAM Unsorted - BAM_SortedByCoordinate … alignments in BAM format, sorted by coordinate. Requires –outSAMtype BAM SortedByCoordinate - BAM_Quant … alignments to transcriptome in BAM format, unsorted. Requires –quantMode TranscriptomeSAMstring, example: "Log"
--outReadsUnmappedoutput of unmapped and partially mapped (i.e. mapped only one mate of a paired end read) reads in separate file(s). - None … no output - Fastx … output in separate fasta/fastq files, Unmapped.out.mate1/2string
--outQSconversionAddadd this number to the quality score (e.g. to convert from Illumina to Sanger, use -31)integer, example: 0
--outMultimapperOrderorder of multimapping alignments in the output files - Old_2.4 … quasi-random order used before 2.5.0 - Random … random order of alignments for each multi-mapper. Read mates (pairs) are always adjacent, all alignment for each read stay together. This option will become default in the future releases.string, example: "Old_2.4"
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+

Output: SAM and BAM

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NameDescriptionAttributes
--outSAMtypetype of SAM/BAM output 1st word: - BAM … output BAM without sorting - SAM … output SAM without sorting - None … no SAM/BAM output 2nd, 3rd: - Unsorted … standard unsorted - SortedByCoordinate … sorted by coordinate. This option will allocate extra memory for sorting which can be specified by –limitBAMsortRAM.string, example: "SAM"
--outSAMmodemode of SAM output - None … no SAM output - Full … full SAM output - NoQS … full SAM but without quality scoresstring, example: "Full"
--outSAMstrandFieldCufflinks-like strand field flag - None … not used - intronMotif … strand derived from the intron motif. This option changes the output alignments: reads with inconsistent and/or non-canonical introns are filtered out.string
--outSAMattributesa string of desired SAM attributes, in the order desired for the output SAM. Tags can be listed in any combination/order. Presets: - None … no attributes - Standard … NH HI AS nM - All … NH HI AS nM NM MD jM jI MC ch Alignment: - NH … number of loci the reads maps to: =1 for unique mappers, >1 for multimappers. Standard SAM tag. - HI … multiple alignment index, starts with –outSAMattrIHstart (=1 by default). Standard SAM tag. - AS … local alignment score, +1/-1 for matches/mismateches, score* penalties for indels and gaps. For PE reads, total score for two mates. Stadnard SAM tag. - nM … number of mismatches. For PE reads, sum over two mates. - NM … edit distance to the reference (number of mismatched + inserted + deleted bases) for each mate. Standard SAM tag. - MD … string encoding mismatched and deleted reference bases (see standard SAM specifications). Standard SAM tag. - jM … intron motifs for all junctions (i.e. N in CIGAR): 0: non-canonical; 1: GT/AG, 2: CT/AC, 3: GC/AG, 4: CT/GC, 5: AT/AC, 6: GT/AT. If splice junctions database is used, and a junction is annotated, 20 is added to its motif value. - jI … start and end of introns for all junctions (1-based). - XS … alignment strand according to –outSAMstrandField. - MC … mate’s CIGAR string. Standard SAM tag. - ch … marks all segment of all chimeric alingments for –chimOutType WithinBAM output. - cN … number of bases clipped from the read ends: 5’ and 3’ Variation: - vA … variant allele - vG … genomic coordinate of the variant overlapped by the read. - vW … 1 - alignment passes WASP filtering; 2,3,4,5,6,7 - alignment does not pass WASP filtering. Requires –waspOutputMode SAMtag. STARsolo: - CR CY UR UY … sequences and quality scores of cell barcodes and UMIs for the solo* demultiplexing. - GX GN … gene ID and gene name for unique-gene reads. - gx gn … gene IDs and gene names for unique- and multi-gene reads. - CB UB … error-corrected cell barcodes and UMIs for solo* demultiplexing. Requires –outSAMtype BAM SortedByCoordinate. - sM … assessment of CB and UMI. - sS … sequence of the entire barcode (CB,UMI,adapter). - sQ … quality of the entire barcode. ***Unsupported/undocumented: - ha … haplotype (1/2) when mapping to the diploid genome. Requires genome generated with –genomeTransformType Diploid . - rB … alignment block read/genomic coordinates. - vR … read coordinate of the variant.string, example: "Standard"
--outSAMattrIHstartstart value for the IH attribute. 0 may be required by some downstream software, such as Cufflinks or StringTie.integer, example: 1
--outSAMunmappedoutput of unmapped reads in the SAM format 1st word: - None … no output - Within … output unmapped reads within the main SAM file (i.e. Aligned.out.sam) 2nd word: - KeepPairs … record unmapped mate for each alignment, and, in case of unsorted output, keep it adjacent to its mapped mate. Only affects multi-mapping reads.string
--outSAMordertype of sorting for the SAM output Paired: one mate after the other for all paired alignments PairedKeepInputOrder: one mate after the other for all paired alignments, the order is kept the same as in the input FASTQ filesstring, example: "Paired"
--outSAMprimaryFlagwhich alignments are considered primary - all others will be marked with 0x100 bit in the FLAG - OneBestScore … only one alignment with the best score is primary - AllBestScore … all alignments with the best score are primarystring, example: "OneBestScore"
--outSAMreadIDread ID record type - Standard … first word (until space) from the FASTx read ID line, removing /1,/2 from the end - Number … read number (index) in the FASTx filestring, example: "Standard"
--outSAMmapqUnique0 to 255: the MAPQ value for unique mappersinteger, example: 255
--outSAMflagOR0 to 65535: sam FLAG will be bitwise OR’d with this value, i.e. FLAG=FLAG | outSAMflagOR. This is applied after all flags have been set by STAR, and after outSAMflagAND. Can be used to set specific bits that are not set otherwise.integer, example: 0
--outSAMflagAND0 to 65535: sam FLAG will be bitwise AND’d with this value, i.e. FLAG=FLAG & outSAMflagOR. This is applied after all flags have been set by STAR, but before outSAMflagOR. Can be used to unset specific bits that are not set otherwise.integer, example: 65535
--outSAMattrRGlineSAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”. xxx will be added as RG tag to each output alignment. Any spaces in the tag values have to be double quoted. Comma separated RG lines correspons to different (comma separated) input files in –readFilesIn. Commas have to be surrounded by spaces, e.g. –outSAMattrRGline ID:xxx , ID:zzz “DS:z z” , ID:yyy DS:yyyystring
--outSAMheaderHD@HD (header) line of the SAM headerstring
--outSAMheaderPGextra @PG (software) line of the SAM header (in addition to STAR)string
--outSAMheaderCommentFilepath to the file with @CO (comment) lines of the SAM headerstring
--outSAMfilterfilter the output into main SAM/BAM files - KeepOnlyAddedReferences … only keep the reads for which all alignments are to the extra reference sequences added with –genomeFastaFiles at the mapping stage. - KeepAllAddedReferences … keep all alignments to the extra reference sequences added with –genomeFastaFiles at the mapping stage.string
--outSAMmultNmaxmax number of multiple alignments for a read that will be output to the SAM/BAM files. Note that if this value is not equal to -1, the top scoring alignment will be output first - -1 … all alignments (up to –outFilterMultimapNmax) will be outputinteger, example: -1
--outSAMtlencalculation method for the TLEN field in the SAM/BAM files - 1 … leftmost base of the (+)strand mate to rightmost base of the (-)mate. (+)sign for the (+)strand mate - 2 … leftmost base of any mate to rightmost base of any mate. (+)sign for the mate with the leftmost base. This is different from 1 for overlapping mates with protruding endsinteger, example: 1
--outBAMcompression-1 to 10 BAM compression level, -1=default compression (6?), 0=no compression, 10=maximum compressioninteger, example: 1
--outBAMsortingThreadN>=0: number of threads for BAM sorting. 0 will default to min(6,–runThreadN).integer, example: 0
--outBAMsortingBinsN>0: number of genome bins for coordinate-sortinginteger, example: 50
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BAM processing

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NameDescriptionAttributes
--bamRemoveDuplicatesTypemark duplicates in the BAM file, for now only works with (i) sorted BAM fed with inputBAMfile, and (ii) for paired-end alignments only - - … no duplicate removal/marking - UniqueIdentical … mark all multimappers, and duplicate unique mappers. The coordinates, FLAG, CIGAR must be identical - UniqueIdenticalNotMulti … mark duplicate unique mappers but not multimappers.string
--bamRemoveDuplicatesMate2basesNnumber of bases from the 5’ of mate 2 to use in collapsing (e.g. for RAMPAGE)integer, example: 0
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Output Wiggle

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NameDescriptionAttributes
--outWigTypetype of signal output, e.g. “bedGraph” OR “bedGraph read1_5p”. Requires sorted BAM: –outSAMtype BAM SortedByCoordinate . 1st word: - None … no signal output - bedGraph … bedGraph format - wiggle … wiggle format 2nd word: - read1_5p … signal from only 5’ of the 1st read, useful for CAGE/RAMPAGE etc - read2 … signal from only 2nd readstring
--outWigStrandstrandedness of wiggle/bedGraph output - Stranded … separate strands, str1 and str2 - Unstranded … collapsed strandsstring, example: "Stranded"
--outWigReferencesPrefixprefix matching reference names to include in the output wiggle file, e.g. “chr”, default “-” - include all referencesstring
--outWigNormtype of normalization for the signal - RPM … reads per million of mapped reads - None … no normalization, “raw” countsstring, example: "RPM"
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Output Filtering

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NameDescriptionAttributes
--outFilterTypetype of filtering - Normal … standard filtering using only current alignment - BySJout … keep only those reads that contain junctions that passed filtering into SJ.out.tabstring, example: "Normal"
--outFilterMultimapScoreRangethe score range below the maximum score for multimapping alignmentsinteger, example: 1
--outFilterMultimapNmaxmaximum number of loci the read is allowed to map to. Alignments (all of them) will be output only if the read maps to no more loci than this value. Otherwise no alignments will be output, and the read will be counted as “mapped to too many loci” in the Log.final.out .integer, example: 10
--outFilterMismatchNmaxalignment will be output only if it has no more mismatches than this value.integer, example: 10
--outFilterMismatchNoverLmaxalignment will be output only if its ratio of mismatches to mapped length is less than or equal to this value.double, example: 0.3
--outFilterMismatchNoverReadLmaxalignment will be output only if its ratio of mismatches to read length is less than or equal to this value.double, example: 1
--outFilterScoreMinalignment will be output only if its score is higher than or equal to this value.integer, example: 0
--outFilterScoreMinOverLreadsame as outFilterScoreMin, but normalized to read length (sum of mates’ lengths for paired-end reads)double, example: 0.66
--outFilterMatchNminalignment will be output only if the number of matched bases is higher than or equal to this value.integer, example: 0
--outFilterMatchNminOverLreadsam as outFilterMatchNmin, but normalized to the read length (sum of mates’ lengths for paired-end reads).double, example: 0.66
--outFilterIntronMotifsfilter alignment using their motifs - None … no filtering - RemoveNoncanonical … filter out alignments that contain non-canonical junctions - RemoveNoncanonicalUnannotated … filter out alignments that contain non-canonical unannotated junctions when using annotated splice junctions database. The annotated non-canonical junctions will be kept.string
--outFilterIntronStrandsfilter alignments - RemoveInconsistentStrands … remove alignments that have junctions with inconsistent strands - None … no filteringstring, example: "RemoveInconsistentStrands"
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Output splice junctions (SJ.out.tab)

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NameDescriptionAttributes
--outSJtypetype of splice junction output - Standard … standard SJ.out.tab output - None … no splice junction outputstring, example: "Standard"
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Output Filtering: Splice Junctions

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NameDescriptionAttributes
--outSJfilterReadswhich reads to consider for collapsed splice junctions output - All … all reads, unique- and multi-mappers - Unique … uniquely mapping reads onlystring, example: "All"
--outSJfilterOverhangMinminimum overhang length for splice junctions on both sides for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif does not apply to annotated junctionsinteger, example: 30, example: 12, example: 12, example: 12
--outSJfilterCountUniqueMinminimum uniquely mapping read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctionsinteger, example: 3, example: 1, example: 1, example: 1
--outSJfilterCountTotalMinminimum total (multi-mapping+unique) read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctionsinteger, example: 3, example: 1, example: 1, example: 1
--outSJfilterDistToOtherSJminminimum allowed distance to other junctions’ donor/acceptor does not apply to annotated junctionsinteger, example: 10, example: 0, example: 5, example: 10
--outSJfilterIntronMaxVsReadNmaximum gap allowed for junctions supported by 1,2,3,,,N reads i.e. by default junctions supported by 1 read can have gaps <=50000b, by 2 reads: <=100000b, by 3 reads: <=200000. by >=4 reads any gap <=alignIntronMax does not apply to annotated junctionsinteger, example: 50000, example: 100000, example: 200000
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+

Scoring

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NameDescriptionAttributes
--scoreGapsplice junction penalty (independent on intron motif)integer, example: 0
--scoreGapNoncannon-canonical junction penalty (in addition to scoreGap)integer, example: -8
--scoreGapGCAGGC/AG and CT/GC junction penalty (in addition to scoreGap)integer, example: -4
--scoreGapATACAT/AC and GT/AT junction penalty (in addition to scoreGap)integer, example: -8
--scoreGenomicLengthLog2scaleextra score logarithmically scaled with genomic length of the alignment: scoreGenomicLengthLog2scale*log2(genomicLength)integer, example: 0
--scoreDelOpendeletion open penaltyinteger, example: -2
--scoreDelBasedeletion extension penalty per base (in addition to scoreDelOpen)integer, example: -2
--scoreInsOpeninsertion open penaltyinteger, example: -2
--scoreInsBaseinsertion extension penalty per base (in addition to scoreInsOpen)integer, example: -2
--scoreStitchSJshiftmaximum score reduction while searching for SJ boundaries in the stitching stepinteger, example: 1
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Alignments and Seeding

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NameDescriptionAttributes
--seedSearchStartLmaxdefines the search start point through the read - the read is split into pieces no longer than this valueinteger, example: 50
--seedSearchStartLmaxOverLreadseedSearchStartLmax normalized to read length (sum of mates’ lengths for paired-end reads)double, example: 1
--seedSearchLmaxdefines the maximum length of the seeds, if =0 seed length is not limitedinteger, example: 0
--seedMultimapNmaxonly pieces that map fewer than this value are utilized in the stitching procedureinteger, example: 10000
--seedPerReadNmaxmax number of seeds per readinteger, example: 1000
--seedPerWindowNmaxmax number of seeds per windowinteger, example: 50
--seedNoneLociPerWindowmax number of one seed loci per windowinteger, example: 10
--seedSplitMinmin length of the seed sequences split by Ns or mate gapinteger, example: 12
--seedMapMinmin length of seeds to be mappedinteger, example: 5
--alignIntronMinminimum intron size, genomic gap is considered intron if its length>=alignIntronMin, otherwise it is considered Deletioninteger, example: 21
--alignIntronMaxmaximum intron size, if 0, max intron size will be determined by (2^winBinNbits)*winAnchorDistNbinsinteger, example: 0
--alignMatesGapMaxmaximum gap between two mates, if 0, max intron gap will be determined by (2^winBinNbits)*winAnchorDistNbinsinteger, example: 0
--alignSJoverhangMinminimum overhang (i.e. block size) for spliced alignmentsinteger, example: 5
--alignSJstitchMismatchNmaxmaximum number of mismatches for stitching of the splice junctions (-1: no limit). (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif.integer, example: 0, example: -1, example: 0, example: 0
--alignSJDBoverhangMinminimum overhang (i.e. block size) for annotated (sjdb) spliced alignmentsinteger, example: 3
--alignSplicedMateMapLminminimum mapped length for a read mate that is splicedinteger, example: 0
--alignSplicedMateMapLminOverLmatealignSplicedMateMapLmin normalized to mate lengthdouble, example: 0.66
--alignWindowsPerReadNmaxmax number of windows per readinteger, example: 10000
--alignTranscriptsPerWindowNmaxmax number of transcripts per windowinteger, example: 100
--alignTranscriptsPerReadNmaxmax number of different alignments per read to considerinteger, example: 10000
--alignEndsTypetype of read ends alignment - Local … standard local alignment with soft-clipping allowed - EndToEnd … force end-to-end read alignment, do not soft-clip - Extend5pOfRead1 … fully extend only the 5p of the read1, all other ends: local alignment - Extend5pOfReads12 … fully extend only the 5p of the both read1 and read2, all other ends: local alignmentstring, example: "Local"
--alignEndsProtrudeallow protrusion of alignment ends, i.e. start (end) of the +strand mate downstream of the start (end) of the -strand mate 1st word: int: maximum number of protrusion bases allowed 2nd word: string: - ConcordantPair … report alignments with non-zero protrusion as concordant pairs - DiscordantPair … report alignments with non-zero protrusion as discordant pairsstring, example: "0 ConcordantPair"
--alignSoftClipAtReferenceEndsallow the soft-clipping of the alignments past the end of the chromosomes - Yes … allow - No … prohibit, useful for compatibility with Cufflinksstring, example: "Yes"
--alignInsertionFlushhow to flush ambiguous insertion positions - None … insertions are not flushed - Right … insertions are flushed to the rightstring
+
+
+

Paired-End reads

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--peOverlapNbasesMinminimum number of overlapping bases to trigger mates merging and realignment. Specify >0 value to switch on the “merginf of overlapping mates” algorithm.integer, example: 0
--peOverlapMMpmaximum proportion of mismatched bases in the overlap areadouble, example: 0.01
+
+
+

Windows, Anchors, Binning

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--winAnchorMultimapNmaxmax number of loci anchors are allowed to map tointeger, example: 50
--winBinNbits=log2(winBin), where winBin is the size of the bin for the windows/clustering, each window will occupy an integer number of bins.integer, example: 16
--winAnchorDistNbinsmax number of bins between two anchors that allows aggregation of anchors into one windowinteger, example: 9
--winFlankNbinslog2(winFlank), where win Flank is the size of the left and right flanking regions for each windowinteger, example: 4
--winReadCoverageRelativeMinminimum relative coverage of the read sequence by the seeds in a window, for STARlong algorithm only.double, example: 0.5
--winReadCoverageBasesMinminimum number of bases covered by the seeds in a window , for STARlong algorithm only.integer, example: 0
+
+
+

Chimeric Alignments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--chimOutTypetype of chimeric output - Junctions … Chimeric.out.junction - SeparateSAMold … output old SAM into separate Chimeric.out.sam file - WithinBAM … output into main aligned BAM files (Aligned.*.bam) - WithinBAM HardClip … (default) hard-clipping in the CIGAR for supplemental chimeric alignments (default if no 2nd word is present) - WithinBAM SoftClip … soft-clipping in the CIGAR for supplemental chimeric alignmentsstring, example: "Junctions"
--chimSegmentMinminimum length of chimeric segment length, if ==0, no chimeric outputinteger, example: 0
--chimScoreMinminimum total (summed) score of the chimeric segmentsinteger, example: 0
--chimScoreDropMaxmax drop (difference) of chimeric score (the sum of scores of all chimeric segments) from the read lengthinteger, example: 20
--chimScoreSeparationminimum difference (separation) between the best chimeric score and the next oneinteger, example: 10
--chimScoreJunctionNonGTAGpenalty for a non-GT/AG chimeric junctioninteger, example: -1
--chimJunctionOverhangMinminimum overhang for a chimeric junctioninteger, example: 20
--chimSegmentReadGapMaxmaximum gap in the read sequence between chimeric segmentsinteger, example: 0
--chimFilterdifferent filters for chimeric alignments - None … no filtering - banGenomicN … Ns are not allowed in the genome sequence around the chimeric junctionstring, example: "banGenomicN"
--chimMainSegmentMultNmaxmaximum number of multi-alignments for the main chimeric segment. =1 will prohibit multimapping main segments.integer, example: 10
--chimMultimapNmaxmaximum number of chimeric multi-alignments - 0 … use the old scheme for chimeric detection which only considered unique alignmentsinteger, example: 0
--chimMultimapScoreRangethe score range for multi-mapping chimeras below the best chimeric score. Only works with –chimMultimapNmax > 1integer, example: 1
--chimNonchimScoreDropMinto trigger chimeric detection, the drop in the best non-chimeric alignment score with respect to the read length has to be greater than this valueinteger, example: 20
--chimOutJunctionFormatformatting type for the Chimeric.out.junction file - 0 … no comment lines/headers - 1 … comment lines at the end of the file: command line and Nreads: total, unique/multi-mappinginteger, example: 0
+
+
+

Quantification of Annotations

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--quantModetypes of quantification requested - - … none - TranscriptomeSAM … output SAM/BAM alignments to transcriptome into a separate file - GeneCounts … count reads per genestring
--quantTranscriptomeBAMcompression-2 to 10 transcriptome BAM compression level - -2 … no BAM output - -1 … default compression (6?) - 0 … no compression - 10 … maximum compressioninteger, example: 1
--quantTranscriptomeBanprohibit various alignment type - IndelSoftclipSingleend … prohibit indels, soft clipping and single-end alignments - compatible with RSEM - Singleend … prohibit single-end alignmentsstring, example: "IndelSoftclipSingleend"
+
+
+

2-pass Mapping

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--twopassMode2-pass mapping mode. - None … 1-pass mapping - Basic … basic 2-pass mapping, with all 1st pass junctions inserted into the genome indices on the flystring
--twopass1readsNnumber of reads to process for the 1st step. Use very large number (or default -1) to map all reads in the first step.integer, example: -1
+
+
+

WASP parameters

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--waspOutputModeWASP allele-specific output type. This is re-implementation of the original WASP mappability filtering by Bryce van de Geijn, Graham McVicker, Yoav Gilad & Jonathan K Pritchard. Please cite the original WASP paper: Nature Methods 12, 1061-1063 (2015), https://www.nature.com/articles/nmeth.3582 . - SAMtag … add WASP tags to the alignments that pass WASP filteringstring
+
+
+

STARsolo (single cell RNA-seq) parameters

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--soloTypetype of single-cell RNA-seq - CB_UMI_Simple … (a.k.a. Droplet) one UMI and one Cell Barcode of fixed length in read2, e.g. Drop-seq and 10X Chromium. - CB_UMI_Complex … multiple Cell Barcodes of varying length, one UMI of fixed length and one adapter sequence of fixed length are allowed in read2 only (e.g. inDrop, ddSeq). - CB_samTagOut … output Cell Barcode as CR and/or CB SAm tag. No UMI counting. –readFilesIn cDNA_read1 [cDNA_read2 if paired-end] CellBarcode_read . Requires –outSAMtype BAM Unsorted [and/or SortedByCoordinate] - SmartSeq … Smart-seq: each cell in a separate FASTQ (paired- or single-end), barcodes are corresponding read-groups, no UMI sequences, alignments deduplicated according to alignment start and end (after extending soft-clipped bases)string
--soloCBwhitelistfile(s) with whitelist(s) of cell barcodes. Only –soloType CB_UMI_Complex allows more than one whitelist file. - None … no whitelist: all cell barcodes are allowedstring
--soloCBstartcell barcode start baseinteger, example: 1
--soloCBlencell barcode lengthinteger, example: 16
--soloUMIstartUMI start baseinteger, example: 17
--soloUMIlenUMI lengthinteger, example: 10
--soloBarcodeReadLengthlength of the barcode read - 1 … equal to sum of soloCBlen+soloUMIlen - 0 … not defined, do not checkinteger, example: 1
--soloBarcodeMateidentifies which read mate contains the barcode (CB+UMI) sequence - 0 … barcode sequence is on separate read, which should always be the last file in the –readFilesIn listed - 1 … barcode sequence is a part of mate 1 - 2 … barcode sequence is a part of mate 2integer, example: 0
--soloCBpositionposition of Cell Barcode(s) on the barcode read. Presently only works with –soloType CB_UMI_Complex, and barcodes are assumed to be on Read2. Format for each barcode: startAnchor_startPosition_endAnchor_endPosition start(end)Anchor defines the Anchor Base for the CB: 0: read start; 1: read end; 2: adapter start; 3: adapter end start(end)Position is the 0-based position with of the CB start(end) with respect to the Anchor Base String for different barcodes are separated by space. Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 0_0_2_-1 3_1_3_8string
--soloUMIpositionposition of the UMI on the barcode read, same as soloCBposition Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 3_9_3_14string
--soloAdapterSequenceadapter sequence to anchor barcodes. Only one adapter sequence is allowed.string
--soloAdapterMismatchesNmaxmaximum number of mismatches allowed in adapter sequence.integer, example: 1
--soloCBmatchWLtypematching the Cell Barcodes to the WhiteList - Exact … only exact matches allowed - 1MM … only one match in whitelist with 1 mismatched base allowed. Allowed CBs have to have at least one read with exact match. - 1MM_multi … multiple matches in whitelist with 1 mismatched base allowed, posterior probability calculation is used choose one of the matches. Allowed CBs have to have at least one read with exact match. This option matches best with CellRanger 2.2.0 - 1MM_multi_pseudocounts … same as 1MM_Multi, but pseudocounts of 1 are added to all whitelist barcodes. - 1MM_multi_Nbase_pseudocounts … same as 1MM_multi_pseudocounts, multimatching to WL is allowed for CBs with N-bases. This option matches best with CellRanger >= 3.0.0 - EditDist_2 … allow up to edit distance of 3 fpr each of the barcodes. May include one deletion + one insertion. Only works with –soloType CB_UMI_Complex. Matches to multiple passlist barcdoes are not allowed. Similar to ParseBio Split-seq pipeline.string, example: "1MM_multi"
--soloInputSAMattrBarcodeSeqwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode sequence (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeSeq CR UR . This parameter is required when running STARsolo with input from SAM.string
--soloInputSAMattrBarcodeQualwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode qualities (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeQual CY UY . If this parameter is ‘-’ (default), the quality ‘H’ will be assigned to all bases.string
--soloStrandstrandedness of the solo libraries: - Unstranded … no strand information - Forward … read strand same as the original RNA molecule - Reverse … read strand opposite to the original RNA moleculestring, example: "Forward"
--soloFeaturesgenomic features for which the UMI counts per Cell Barcode are collected - Gene … genes: reads match the gene transcript - SJ … splice junctions: reported in SJ.out.tab - GeneFull … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns - GeneFull_ExonOverIntron … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns: prioritize 100% overlap with exons - GeneFull_Ex50pAS … full gene (pre-RNA): count all reads overlapping genes’ exons and introns: prioritize >50% overlap with exons. Do not count reads with 100% exonic overlap in the antisense direction.string, example: "Gene"
--soloMultiMapperscounting method for reads mapping to multiple genes - Unique … count only reads that map to unique genes - Uniform … uniformly distribute multi-genic UMIs to all genes - Rescue … distribute UMIs proportionally to unique+uniform counts (~ first iteration of EM) - PropUnique … distribute UMIs proportionally to unique mappers, if present, and uniformly if not. - EM … multi-gene UMIs are distributed using Expectation Maximization algorithmstring, example: "Unique"
--soloUMIdeduptype of UMI deduplication (collapsing) algorithm - 1MM_All … all UMIs with 1 mismatch distance to each other are collapsed (i.e. counted once). - 1MM_Directional_UMItools … follows the “directional” method from the UMI-tools by Smith, Heger and Sudbery (Genome Research 2017). - 1MM_Directional … same as 1MM_Directional_UMItools, but with more stringent criteria for duplicate UMIs - Exact … only exactly matching UMIs are collapsed. - NoDedup … no deduplication of UMIs, count all reads. - 1MM_CR … CellRanger2-4 algorithm for 1MM UMI collapsing.string, example: "1MM_All"
--soloUMIfilteringtype of UMI filtering (for reads uniquely mapping to genes) - - … basic filtering: remove UMIs with N and homopolymers (similar to CellRanger 2.2.0). - MultiGeneUMI … basic + remove lower-count UMIs that map to more than one gene. - MultiGeneUMI_All … basic + remove all UMIs that map to more than one gene. - MultiGeneUMI_CR … basic + remove lower-count UMIs that map to more than one gene, matching CellRanger > 3.0.0 . Only works with –soloUMIdedup 1MM_CRstring
--soloOutFileNamesfile names for STARsolo output: file_name_prefix gene_names barcode_sequences cell_feature_count_matrixstring, example: "Solo.out/", example: "features.tsv", example: "barcodes.tsv", example: "matrix.mtx"
--soloCellFiltercell filtering type and parameters - None … do not output filtered cells - TopCells … only report top cells by UMI count, followed by the exact number of cells - CellRanger2.2 … simple filtering of CellRanger 2.2. Can be followed by numbers: number of expected cells, robust maximum percentile for UMI count, maximum to minimum ratio for UMI count The harcoded values are from CellRanger: nExpectedCells=3000; maxPercentile=0.99; maxMinRatio=10 - EmptyDrops_CR … EmptyDrops filtering in CellRanger flavor. Please cite the original EmptyDrops paper: A.T.L Lun et al, Genome Biology, 20, 63 (2019): https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1662-y Can be followed by 10 numeric parameters: nExpectedCells maxPercentile maxMinRatio indMin indMax umiMin umiMinFracMedian candMaxN FDR simN The harcoded values are from CellRanger: 3000 0.99 10 45000 90000 500 0.01 20000 0.01 10000string, example: "CellRanger2.2", example: "3000", example: "0.99", example: "10"
--soloOutFormatFeaturesGeneField3field 3 in the Gene features.tsv file. If “-”, then no 3rd field is output.string, example: "Gene Expression"
--soloCellReadStatsOutput reads statistics for each CB - Standard … standard outputstring
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/mapping/star_build_reference.html b/pr-preview/pr-51/components/modules/mapping/star_build_reference.html new file mode 100644 index 00000000..cea8d244 --- /dev/null +++ b/pr-preview/pr-51/components/modules/mapping/star_build_reference.html @@ -0,0 +1,1650 @@ + + + + + + + + + + +OpenPipelines - Star build reference + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Star build reference

+
+ +
+
+ Create a reference for STAR from a set of fasta files. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: star_build_reference
+Namespace: mapping

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/mapping/star_build_reference/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Input/Output
+genome_fasta: # please fill in - example: ["chr1.fasta", "chr2.fasta"]
+# transcriptome_gtf: "path/to/file"
+# output: "$id.$key.output.output"
+
+# Genome indexing arguments
+genomeSAindexNbases: 14
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/mapping/star_build_reference/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input/Output

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--genome_fastaThe fasta files to be included in the reference. Corresponds to the –genomeFastaFiles argument in the STAR command.file, required, example: "chr1.fasta", example: "chr2.fasta"
--transcriptome_gtfSpecifies the path to the file with annotated transcripts in the standard GTF format. STAR will extract splice junctions from this file and use them to greatly improve accuracy of the mapping. Corresponds to the –sjdbGTFfile argument in the STAR command.file
--outputPath to output directory. Corresponds to the –genomeDir argument in the STAR command.file, required, example: "/path/to/foo"
+
+
+

Genome indexing arguments

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--genomeSAindexNbasesLength (bases) of the SA pre-indexing string. Typically between 10 and 15. Longer strings will use much more memory, but allow faster searches. For small genomes, the parameter {genomeSAindexNbases must be scaled down to min(14, log2(GenomeLength)/2 - 1).integer, default: 14
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/metadata/add_id.html b/pr-preview/pr-51/components/modules/metadata/add_id.html new file mode 100644 index 00000000..a5efb307 --- /dev/null +++ b/pr-preview/pr-51/components/modules/metadata/add_id.html @@ -0,0 +1,1642 @@ + + + + + + + + + + +OpenPipelines - Add id + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Add id

+
+ +
+
+ Add id of .obs. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: add_id
+Namespace: metadata

+
+ +

Also allows to make .obs_names (the .obs index) unique by prefixing the values with an unique id per .h5mu file

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/metadata/add_id/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "sample_path"
+input_id: # please fill in - example: "foo"
+obs_output: "sample_id"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+make_observation_keys_unique: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/metadata/add_id/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to the input .h5mu.file, required, example: "sample_path"
--input_idThe input id.string, required
--obs_outputName of the .obs column where to store the id.string, default: "sample_id"
--outputfile, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--make_observation_keys_uniqueJoin the id to the .obs index (.obs_names).boolean_true
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/metadata/join_csv.html b/pr-preview/pr-51/components/modules/metadata/join_csv.html new file mode 100644 index 00000000..60a36fcd --- /dev/null +++ b/pr-preview/pr-51/components/modules/metadata/join_csv.html @@ -0,0 +1,1695 @@ + + + + + + + + + + +OpenPipelines - Join csv + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Join csv

+
+ +
+
+ Join a csv containing metadata to the .obs or .var field of a mudata file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: join_csv
+Namespace: metadata

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/metadata/join_csv/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# MuData Input
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# obs_key: "foo"
+# var_key: "foo"
+
+# MuData Output
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Metadata Input
+input_csv: # please fill in - example: "metadata.csv"
+csv_key: "id"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/metadata/join_csv/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

MuData Input

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--obs_keyObs column name where the sample id can be found for each observation to join on. Useful when adding metadata to concatenated samples. Mutually exclusive with --var_key.”string
--var_keyVar column name where the sample id can be found for each variable to join on. Mutually exclusive with --obs_key.”string
+
+
+

MuData Output

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+

Metadata Input

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--input_csv.csv file containing metadatafile, required, example: "metadata.csv"
--csv_keycolumn of the the csv that corresponds to the sample id.string, default: "id"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/metadata/join_uns_to_obs.html b/pr-preview/pr-51/components/modules/metadata/join_uns_to_obs.html new file mode 100644 index 00000000..f137f0f6 --- /dev/null +++ b/pr-preview/pr-51/components/modules/metadata/join_uns_to_obs.html @@ -0,0 +1,1627 @@ + + + + + + + + + + +OpenPipelines - Join uns to obs + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Join uns to obs

+
+ +
+
+ Join a data frame of length 1 (1 row index value) in .uns containing metadata to the .obs of a mudata file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: join_uns_to_obs
+Namespace: metadata

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/metadata/join_uns_to_obs/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+uns_key: # please fill in - example: "foo"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/metadata/join_uns_to_obs/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--uns_keystring, required
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/metadata/move_obsm_to_obs.html b/pr-preview/pr-51/components/modules/metadata/move_obsm_to_obs.html new file mode 100644 index 00000000..698bee2d --- /dev/null +++ b/pr-preview/pr-51/components/modules/metadata/move_obsm_to_obs.html @@ -0,0 +1,1657 @@ + + + + + + + + + + +OpenPipelines - Move obsm to obs + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Move obsm to obs

+
+ +
+
+ Move a matrix from .obsm to .obs. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: move_obsm_to_obs
+Namespace: metadata

+
+ +

Newly created columns in .obs will be created from the .obsm key suffixed with an underscore and the name of the columns of the specified .obsm matrix

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/metadata/move_obsm_to_obs/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# MuData Input
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+obsm_key: # please fill in - example: "foo"
+
+# MuData Output
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/metadata/move_obsm_to_obs/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

MuData Input

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--obsm_keyKey of a data structure to move from .obsm to .obs.string, required
+
+
+

MuData Output

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/neighbors/bbknn.html b/pr-preview/pr-51/components/modules/neighbors/bbknn.html new file mode 100644 index 00000000..350c2fcd --- /dev/null +++ b/pr-preview/pr-51/components/modules/neighbors/bbknn.html @@ -0,0 +1,1678 @@ + + + + + + + + + + +OpenPipelines - Bbknn + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Bbknn

+
+ +
+
+ BBKNN network generation +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: bbknn
+Namespace: neighbors

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/neighbors/bbknn/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "path/to/file"
+modality: "rna"
+obsm_input: "X_pca"
+obs_batch: "batch"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+uns_output: "neighbors"
+obsp_distances: "distances"
+obsp_connectivities: "connectivities"
+n_neighbors_within_batch: 3
+n_pcs: 50
+# n_trim: 123
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/neighbors/bbknn/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required
--modalitystring, default: "rna"
--obsm_inputThe dimensionality reduction in .obsm to use for neighbour detection. Defaults to X_pca.string, default: "X_pca"
--obs_batch.obs column name discriminating between your batches.string, default: "batch"
--outputOutput .h5mu file.file, required, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--uns_outputMandatory .uns slot to store various neighbor output objects.string, default: "neighbors"
--obsp_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "distances"
--obsp_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "connectivities"
--n_neighbors_within_batchHow many top neighbours to report for each batch; total number of neighbours in the initial k-nearest-neighbours computation will be this number times the number of batches.integer, default: 3
--n_pcsHow many dimensions (in case of PCA, principal components) to use in the analysis.integer, default: 50
--n_trimTrim the neighbours of each cell to these many top connectivities. May help with population independence and improve the tidiness of clustering. The lower the value the more independent the individual populations, at the cost of more conserved batch effect. If None (default), sets the parameter value automatically to 10 times neighbors_within_batch times the number of batches. Set to 0 to skip.integer
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (author)

    • +

  • Dries Schaumont (maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/neighbors/find_neighbors.html b/pr-preview/pr-51/components/modules/neighbors/find_neighbors.html new file mode 100644 index 00000000..806ecde1 --- /dev/null +++ b/pr-preview/pr-51/components/modules/neighbors/find_neighbors.html @@ -0,0 +1,1673 @@ + + + + + + + + + + +OpenPipelines - Find neighbors + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Find neighbors

+
+ +
+
+ Compute a neighborhood graph of observations [McInnes18]. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: find_neighbors
+Namespace: neighbors

+
+ +

The neighbor search efficiency of this heavily relies on UMAP [McInnes18], which also provides a method for estimating connectivities of data points - the connectivity of the manifold (method==‘umap’). If method==‘gauss’, connectivities are computed according to [Coifman05], in the adaption of [Haghverdi16].

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/neighbors/find_neighbors/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+obsm_input: "X_pca"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+uns_output: "neighbors"
+obsp_distances: "distances"
+obsp_connectivities: "connectivities"
+metric: "euclidean"
+num_neighbors: 15
+seed: 0
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/neighbors/find_neighbors/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--obsm_inputWhich .obsm slot to use as a starting PCA embedding.string, default: "X_pca"
--outputOutput h5mu file containing the found neighbors.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--uns_outputMandatory .uns slot to store various neighbor output objects.string, default: "neighbors"
--obsp_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "distances"
--obsp_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "connectivities"
--metricThe distance metric to be used in the generation of the nearest neighborhood network.string, default: "euclidean"
--num_neighborsThe size of local neighborhood (in terms of number of neighboring data points) used for manifold approximation. Larger values result in more global views of the manifold, while smaller values result in more local data being preserved. In general values should be in the range 2 to 100. If knn is True, number of nearest neighbors to be searched. If knn is False, a Gaussian kernel width is set to the distance of the n_neighbors neighbor.integer, default: 15
--seedA random seed.integer, default: 0
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (maintainer)

    • +

  • Robrecht Cannoodt (contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/process_10xh5/filter_10xh5.html b/pr-preview/pr-51/components/modules/process_10xh5/filter_10xh5.html new file mode 100644 index 00000000..aadfde9f --- /dev/null +++ b/pr-preview/pr-51/components/modules/process_10xh5/filter_10xh5.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Filter 10xh5 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Filter 10xh5

+
+ +
+
+ Filter a 10x h5 dataset +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: filter_10xh5
+Namespace: process_10xh5

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/process_10xh5/filter_10xh5/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "pbmc_1k_protein_v3_raw_feature_bc_matrix.h5"
+# output: "$id.$key.output.h5"
+min_library_size: 0
+min_cells_per_gene: 0
+# keep_feature_types: ["Antibody Capture"]
+verbose: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/process_10xh5/filter_10xh5/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputAn h5 file from the 10x genomics website.file, required, example: "pbmc_1k_protein_v3_raw_feature_bc_matrix.h5"
--outputOutput h5 file.file, required, example: "pbmc_1k_protein_v3_raw_feature_bc_matrix_filtered.h5"
--min_library_sizeMinimum library size.integer, default: 0
--min_cells_per_geneMinimum number of cells per gene.integer, default: 0
--keep_feature_typesSpecify which feature types will never be filtered outstring, example: "Antibody Capture"
--verboseIncrease verbosityboolean_true
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/qc/calculate_qc_metrics.html b/pr-preview/pr-51/components/modules/qc/calculate_qc_metrics.html new file mode 100644 index 00000000..dcbf0b17 --- /dev/null +++ b/pr-preview/pr-51/components/modules/qc/calculate_qc_metrics.html @@ -0,0 +1,1677 @@ + + + + + + + + + + +OpenPipelines - Calculate qc metrics + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Calculate qc metrics

+
+ +
+
+ Add basic quality control metrics to an .h5mu file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: calculate_qc_metrics
+Namespace: qc

+
+ +

The metrics are comparable to what scanpy.pp.calculate_qc_metrics output, although they have slightly different names:

+

Var metrics (name in this component -> name in scanpy): - pct_dropout -> pct_dropout_by_{expr_type} - num_nonzero_obs -> n_cells_by_{expr_type} - obs_mean -> mean_{expr_type} - total_counts -> total_{expr_type}

+

Obs metrics: - num_nonzero_vars -> n_genes_by_{expr_type} - pct_{var_qc_metrics]} -> pct_{expr_type}{qc_var} - total_counts{var_qc_metrics} -> total_{expr_type}{qc_var} - pct_of_counts_in_top{top_n_vars}vars -> pct{expr_type}in_top{n}{var_type} - total_counts -> total{expr_type}

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/qc/calculate_qc_metrics/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# layer: "raw_counts"
+# var_qc_metrics: ["ercc", "highly_variable", "mitochondrial"]
+# var_qc_metrics_fill_na_value: true
+# top_n_vars: [123]
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/qc/calculate_qc_metrics/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--layerstring, example: "raw_counts"
--var_qc_metricsKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes.string, example: "ercc,highly_variable,mitochondrial"
--var_qc_metrics_fill_na_valueFill any ‘NA’ values found in the columns specified with –var_qc_metrics to ‘True’ or ‘False’. as False.boolean
--top_n_varsNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.integer
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, example: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/qc/fastqc.html b/pr-preview/pr-51/components/modules/qc/fastqc.html new file mode 100644 index 00000000..52b0efd7 --- /dev/null +++ b/pr-preview/pr-51/components/modules/qc/fastqc.html @@ -0,0 +1,1622 @@ + + + + + + + + + + +OpenPipelines - Fastqc + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Fastqc

+
+ +
+
+ Fastqc component, please see https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: fastqc
+Namespace: qc

+
+ +

This component can take one or more files (by means of shell globbing) or a complete directory

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/qc/fastqc/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+mode: "files"
+input: # please fill in - example: "fastq_dir/"
+# output: "$id.$key.output.output"
+# threads: 123
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/qc/fastqc/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--modeThe mode in which the component works. Can be either files or dir.string, default: "files"
--inputDirectory containing input fastq files.file, required, example: "fastq_dir"
--outputOutput directory to write reports to.file, required, example: "qc"
--threadsSpecifies the number of files which can be processed simultaneously. Each thread will be allocated 250MB of memory.integer
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/qc/multiqc.html b/pr-preview/pr-51/components/modules/qc/multiqc.html new file mode 100644 index 00000000..3fd4b07e --- /dev/null +++ b/pr-preview/pr-51/components/modules/qc/multiqc.html @@ -0,0 +1,1610 @@ + + + + + + + + + + +OpenPipelines - Multiqc + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Multiqc

+
+ +
+
+ MultiQC aggregates results from bioinformatics analyses across many samples into a single report. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: multiqc
+Namespace: qc

+
+ +

It searches a given directory for analysis logs and compiles a HTML report. It’s a general use tool, perfect for summarising the output from numerous bioinformatics tools

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/qc/multiqc/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: ["input.txt"]
+# output: "$id.$key.output.output"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/qc/multiqc/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInputs for MultiQC.file, required, example: "input.txt"
--outputCreate report in the specified output directory.file, required, example: "report"
+ + +
+
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/query/cellxgene_census.html b/pr-preview/pr-51/components/modules/query/cellxgene_census.html new file mode 100644 index 00000000..58b5dc71 --- /dev/null +++ b/pr-preview/pr-51/components/modules/query/cellxgene_census.html @@ -0,0 +1,1705 @@ + + + + + + + + + + +OpenPipelines - Cellxgene census + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cellxgene census

+
+ +
+
+ Query CellxGene Census or user-specified TileDBSoma object, and eventually fetch cell and gene metadata or/and expression counts. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellxgene_census
+Namespace: query

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/query/cellxgene_census/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input_database: "CellxGene"
+modality: "rna"
+cellxgene_release: "2023-05-15"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Query
+species: "homo_sapiens"
+# cell_query: "is_primary_data == True and cell_type_ontology_term_id in ['CL:0000136', 'CL:1000311', 'CL:0002616'] and suspension_type == 'cell'"
+# cells_filter_columns: ["dataset_id", "tissue", "assay", "disease", "cell_type"]
+# min_cells_filter_columns: 100
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/query/cellxgene_census/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+

Arguments related to the input (aka query) dataset.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--input_databaseFull input database S3 prefix URL. Default: CellxGene Censusstring, default: "CellxGene", example: "s3://"
--modalityWhich modality to store the output in.string, default: "rna"
--cellxgene_releaseCellxGene Census release date. More information: https://chanzuckerberg.github.io/cellxgene-census/cellxgene_census_docsite_data_release_info.htmlstring, default: "2023-05-15"
+
+
+

Query

+

Arguments related to the query.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--speciesSpecie(s) of interest. If not specified, Homo Sapiens will be queried.string, default: "homo_sapiens", example: "homo_sapiens"
--cell_queryThe query for selecting the cells as defined by the cellxgene census schema.string, example: "is_primary_data == True and cell_type_ontology_term_id in ['CL:0000136', 'CL:1000311', 'CL:0002616'] and suspension_type == 'cell'"
--cells_filter_columnsThe query for selecting the cells as defined by the cellxgene census schema.string, example: "dataset_id", example: "tissue", example: "assay", example: "disease", example: "cell_type"
--min_cells_filter_columnsMinimum of amount of summed cells_filter_columns cellsdouble, example: 100
+
+
+

Outputs

+

Output arguments.

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput h5mu file.file, required, example: "output.h5mu"
--output_compressionstring, example: "gzip"
+
+
+
+

Authors

+
    +

  • Matthias Beyens

    • +

  • Dries De Maeyer (author)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/reference/build_bdrhap_reference.html b/pr-preview/pr-51/components/modules/reference/build_bdrhap_reference.html new file mode 100644 index 00000000..b5981d9d --- /dev/null +++ b/pr-preview/pr-51/components/modules/reference/build_bdrhap_reference.html @@ -0,0 +1,1624 @@ + + + + + + + + + + +OpenPipelines - Build bdrhap reference + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Build bdrhap reference

+
+ +
+
+ Compile a reference into a STAR index compatible with the BD Rhapsody pipeline. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: build_bdrhap_reference
+Namespace: reference

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/reference/build_bdrhap_reference/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+genome_fasta: # please fill in - example: "genome_sequence.fa.gz"
+transcriptome_gtf: # please fill in - example: "transcriptome_annotation.gtf.gz"
+# output: "$id.$key.output.gz"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/reference/build_bdrhap_reference/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--genome_fastaReference genome fasta.file, required, example: "genome_sequence.fa.gz"
--transcriptome_gtfReference transcriptome annotation.file, required, example: "transcriptome_annotation.gtf.gz"
--outputStar indexfile, required, example: "star_index.tar.gz"
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/reference/build_cellranger_reference.html b/pr-preview/pr-51/components/modules/reference/build_cellranger_reference.html new file mode 100644 index 00000000..a4c656ef --- /dev/null +++ b/pr-preview/pr-51/components/modules/reference/build_cellranger_reference.html @@ -0,0 +1,1625 @@ + + + + + + + + + + +OpenPipelines - Build cellranger reference + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Build cellranger reference

+
+ +
+
+ Build a Cell Ranger-compatible reference folder from user-supplied genome FASTA and gene GTF files. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: build_cellranger_reference
+Namespace: reference

+
+ +

Creates a new folder named after the genome.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/reference/build_cellranger_reference/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+genome_fasta: # please fill in - example: "genome_sequence.fa.gz"
+transcriptome_gtf: # please fill in - example: "transcriptome_annotation.gtf.gz"
+# output: "$id.$key.output.output"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/reference/build_cellranger_reference/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--genome_fastaReference genome fasta.file, required, example: "genome_sequence.fa.gz"
--transcriptome_gtfReference transcriptome annotation.file, required, example: "transcriptome_annotation.gtf.gz"
--outputOutput folderfile, required, example: "cellranger_reference"
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/reference/make_reference.html b/pr-preview/pr-51/components/modules/reference/make_reference.html new file mode 100644 index 00000000..5a332659 --- /dev/null +++ b/pr-preview/pr-51/components/modules/reference/make_reference.html @@ -0,0 +1,1643 @@ + + + + + + + + + + +OpenPipelines - Make reference + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Make reference

+
+ +
+
+ Preprocess and build a transcriptome reference. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: make_reference
+Namespace: reference

+
+ +

Example input files are: - genome_fasta: https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/GRCh38.primary_assembly.genome.fa.gz - transcriptome_gtf: https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/gencode.v41.annotation.gtf.gz - ercc: https://assets.thermofisher.com/TFS-Assets/LSG/manuals/ERCC92.zip

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/reference/make_reference/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+genome_fasta: # please fill in - example: "genome_fasta.fa.gz"
+transcriptome_gtf: # please fill in - example: "transcriptome.gtf.gz"
+# ercc: "ercc.zip"
+# subset_regex: "(ERCC-00002|chr1)"
+# output_fasta: "$id.$key.output_fasta.gz"
+# output_gtf: "$id.$key.output_gtf.gz"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/reference/make_reference/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--genome_fastaReference genome fasta. Example:file, required, example: "genome_fasta.fa.gz"
--transcriptome_gtfReference transcriptome annotation.file, required, example: "transcriptome.gtf.gz"
--erccERCC sequence and annotation file.file, example: "ercc.zip"
--subset_regexWill subset the reference chromosomes using the given regex.string, example: "(ERCC-00002&#124;chr1)"
--output_fastaOutput genome sequence fasta.file, required, example: "genome_sequence.fa.gz"
--output_gtfOutput transcriptome annotation gtf.file, required, example: "transcriptome_annotation.gtf.gz"
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/report/mermaid.html b/pr-preview/pr-51/components/modules/report/mermaid.html new file mode 100644 index 00000000..12179c06 --- /dev/null +++ b/pr-preview/pr-51/components/modules/report/mermaid.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Mermaid + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Mermaid

+
+ +
+
+ Generates a network from mermaid code +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: mermaid
+Namespace: report

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/report/mermaid/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "path/to/file"
+# output: "$id.$key.output.output"
+# output_format: "foo"
+width: 800
+height: 600
+background_color: "white"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/report/mermaid/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput directoryfile, required
--outputGenerated network as output.file, required
--output_formatOutput format for the generated image. By default will be inferred from the extension of the file specified with –output.string
--widthWidth of the pageinteger, default: 800
--heightHeight of the pageinteger, default: 600
--background_colorBackground color for pngs/svgs (not pdfs)string, default: "white", example: "#F0F0F0"
+
+
+
+

Authors

+
    +
  • Dries De Maeyer (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/transfer/publish.html b/pr-preview/pr-51/components/modules/transfer/publish.html new file mode 100644 index 00000000..cd90eaac --- /dev/null +++ b/pr-preview/pr-51/components/modules/transfer/publish.html @@ -0,0 +1,1612 @@ + + + + + + + + + + +OpenPipelines - Publish + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Publish

+
+ +
+
+ Publish an artifact and optionally rename with parameters +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: publish
+Namespace: transfer

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/transfer/publish/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "path/to/file"
+# output: "$id.$key.output.output"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/transfer/publish/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput filenamefile, required
--outputOutput filenamefile, required
+
+
+
+

Authors

+
    +
  • Toni Verbeiren (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/transform/clr.html b/pr-preview/pr-51/components/modules/transform/clr.html new file mode 100644 index 00000000..1a4fbaa6 --- /dev/null +++ b/pr-preview/pr-51/components/modules/transform/clr.html @@ -0,0 +1,1635 @@ + + + + + + + + + + +OpenPipelines - Clr + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Clr

+
+ +
+
+ Perform CLR normalization on CITE-seq data (Stoeckius et al., 2017) +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: clr
+Namespace: transform

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/transform/clr/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "prot"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+# output_layer: "foo"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/transform/clr/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "prot"
--outputOutput h5mu file.file, required, default: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--output_layerOutput layer to use. By default, use X.string
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/transform/delete_layer.html b/pr-preview/pr-51/components/modules/transform/delete_layer.html new file mode 100644 index 00000000..36e91b63 --- /dev/null +++ b/pr-preview/pr-51/components/modules/transform/delete_layer.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Delete layer + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Delete layer

+
+ +
+
+ Delete an anndata layer from one or more modalities +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: delete_layer
+Namespace: transform

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/transform/delete_layer/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+layer: # please fill in - example: ["foo"]
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+missing_ok: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/transform/delete_layer/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--layerInput layer to removestring, required
--outputOutput h5mu file.file, required, default: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--missing_okDo not raise an error if the layer does not exist for all modalities.boolean_true
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/transform/log1p.html b/pr-preview/pr-51/components/modules/transform/log1p.html new file mode 100644 index 00000000..2278cd71 --- /dev/null +++ b/pr-preview/pr-51/components/modules/transform/log1p.html @@ -0,0 +1,1649 @@ + + + + + + + + + + +OpenPipelines - Log1p + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Log1p

+
+ +
+
+ Logarithmize the data matrix. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: log1p
+Namespace: transform

+
+ +

Computes X = log(X + 1), where log denotes the natural logarithm unless a different base is given

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/transform/log1p/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# input_layer: "foo"
+# output_layer: "foo"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+# base: 2
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/transform/log1p/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--input_layerInput layer to use. If None, X is normalizedstring
--output_layerOutput layer to use. By default, use X.string
--outputOutput h5mu file.file, required, default: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--basedouble, example: 2
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (maintainer)

    • +

  • Robrecht Cannoodt (contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/transform/normalize_total.html b/pr-preview/pr-51/components/modules/transform/normalize_total.html new file mode 100644 index 00000000..1c898bea --- /dev/null +++ b/pr-preview/pr-51/components/modules/transform/normalize_total.html @@ -0,0 +1,1656 @@ + + + + + + + + + + +OpenPipelines - Normalize total + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Normalize total

+
+ +
+
+ Normalize counts per cell. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: normalize_total
+Namespace: transform

+
+ +

Normalize each cell by total counts over all genes, so that every cell has the same total count after normalization. If choosing target_sum=1e6, this is CPM normalization.

+

If exclude_highly_expressed=True, very highly expressed genes are excluded from the computation of the normalization factor (size factor) for each cell. This is meaningful as these can strongly influence the resulting normalized values for all other genes [Weinreb17].

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/transform/normalize_total/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# input_layer: "foo"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+# output_layer: "foo"
+target_sum: 10000
+exclude_highly_expressed: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/transform/normalize_total/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--modalitystring, default: "rna"
--input_layerInput layer to use. By default, X is normalizedstring
--outputOutput h5mu file.file, required, default: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--output_layerOutput layer to use. By default, use X.string
--target_sumIf None, after normalization, each observation (cell) has a total count equal to the median of total counts for observations (cells) before normalization.integer, default: 10000
--exclude_highly_expressedExclude (very) highly expressed genes for the computation of the normalization factor (size factor) for each cell. A gene is considered highly expressed, if it has more than max_fraction of the total counts in at least one cell. The not-excluded genes will sum up to target_sum.boolean_true
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (maintainer)

    • +

  • Robrecht Cannoodt (contributor)

    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/transform/regress_out.html b/pr-preview/pr-51/components/modules/transform/regress_out.html new file mode 100644 index 00000000..eee07590 --- /dev/null +++ b/pr-preview/pr-51/components/modules/transform/regress_out.html @@ -0,0 +1,1636 @@ + + + + + + + + + + +OpenPipelines - Regress out + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Regress out

+
+ +
+
+ Regress out (mostly) unwanted sources of variation. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: regress_out
+Namespace: transform

+
+ +

Uses simple linear regression. This is inspired by Seurat’s regressOut function in R [Satija15]. Note that this function tends to overcorrect in certain circumstances as described in issue theislab/scanpy#526. See https://github.com/theislab/scanpy/issues/526

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/transform/regress_out/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+modality: "rna"
+# obs_keys: ["foo"]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/transform/regress_out/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu filefile, required, example: "input.h5mu"
--outputOutput h5mu file.file, required, default: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
--modalityWhich modality (one or more) to run this component on.string, default: "rna"
--obs_keysWhich .obs keys to regress on.string
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer, contributor)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/transform/scale.html b/pr-preview/pr-51/components/modules/transform/scale.html new file mode 100644 index 00000000..400ee66f --- /dev/null +++ b/pr-preview/pr-51/components/modules/transform/scale.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Scale + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scale

+
+ +
+
+ Scale data to unit variance and zero mean +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scale
+Namespace: transform

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/transform/scale/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "input.h5mu"
+modality: "rna"
+# max_value: 123.0
+zero_center: true
+# output: "$id.$key.output.h5mu"
+# output_compression: "gzip"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/transform/scale/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputInput h5mu file.file, required, example: "input.h5mu"
--modalityList of modalities to process.string, default: "rna"
--max_valueClip (truncate) to this value after scaling. Does not clip by default.double
--zero_centerIf False, omit zero-centering variables, which allows to handle sparse input efficiently.boolean, default: TRUE
--outputOutput h5mu file.file, required, default: "output.h5mu"
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/velocity/scvelo.html b/pr-preview/pr-51/components/modules/velocity/scvelo.html new file mode 100644 index 00000000..3fa39a54 --- /dev/null +++ b/pr-preview/pr-51/components/modules/velocity/scvelo.html @@ -0,0 +1,1737 @@ + + + + + + + + + +OpenPipelines - Scvelo + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scvelo

+
+ + + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scvelo
+Namespace: velocity

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/velocity/scvelo/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+input: # please fill in - example: "path/to/file"
+
+# Outputs
+# output: "$id.$key.output.output"
+# output_compression: "gzip"
+
+# Filtering and normalization
+# min_counts: 123
+# min_counts_u: 123
+# min_cells: 123
+# min_cells_u: 123
+# min_shared_counts: 123
+# min_shared_cells: 123
+# n_top_genes: 123
+log_transform: true
+
+# Fitting parameters
+# n_principal_components: 123
+n_neighbors: 30
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/velocity/scvelo/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputVelocyto loom file.file, required
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputOutput directory. If it does not exist, will be created.file, required
--output_compressionThe compression format to be used on the output h5mu object.string, example: "gzip"
+
+
+

Filtering and normalization

+

Arguments for filtering, normalization an log transform (see scvelo.pp.filter_and_normalize function)

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--min_countsMinimum number of counts required for a gene to pass filtering (spliced).integer
--min_counts_uMinimum number of counts required for a gene to pass filtering (unspliced).integer
--min_cellsMinimum number of cells expressed required to pass filtering (spliced).integer
--min_cells_uMinimum number of cells expressed required to pass filtering (unspliced).integer
--min_shared_countsMinimum number of counts (both unspliced and spliced) required for a gene.integer
--min_shared_cellsMinimum number of cells required to be expressed (both unspliced and spliced).integer
--n_top_genesNumber of genes to keep.integer
--log_transformDo not log transform counts.boolean, default: TRUE
+
+
+

Fitting parameters

+

Arguments for fitting the data

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--n_principal_componentsNumber of principal components to use for calculating moments.integer
--n_neighborsNumber of neighbors to use. First/second-order moments are computed for each cell across its nearest neighbors, where the neighbor graph is obtained from euclidean distances in PCA space.integer, default: 30
+
+
+
+

Authors

+
    +
  • Dries Schaumont (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/modules/velocity/velocyto.html b/pr-preview/pr-51/components/modules/velocity/velocyto.html new file mode 100644 index 00000000..d47c04d7 --- /dev/null +++ b/pr-preview/pr-51/components/modules/velocity/velocyto.html @@ -0,0 +1,1641 @@ + + + + + + + + + + +OpenPipelines - Velocyto + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Velocyto

+
+ +
+
+ Runs the velocity analysis on a BAM file, outputting a loom file. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: velocyto
+Namespace: velocity

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script target/nextflow/velocity/velocyto/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+input: # please fill in - example: "path/to/file"
+transcriptome: # please fill in - example: "path/to/file"
+# barcode: "path/to/file"
+without_umi: false
+# output: "$id.$key.output.output"
+logic: "Default"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script target/nextflow/velocity/velocyto/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--inputPath to BAM filefile, required
--transcriptomePath to GTF filefile, required
--barcodeValid barcodes file, to filter the bam. If –bcfile is not specified all the cell barcodes will be included. Cell barcodes should be specified in the bcfile as the ‘CB’ tag for each readfile
--without_umifooboolean_true
--outputVelocyto loom filefile, required
--logicThe logic to use for the filtering.string, default: "Default"
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/index.html b/pr-preview/pr-51/components/workflows/index.html new file mode 100644 index 00000000..52139a71 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/index.html @@ -0,0 +1,1482 @@ + + + + + + + + + +OpenPipelines - Workflows + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Workflows

+
+ + + +
+ + + + +
+ + +
+ + + + +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/ingestion/bd_rhapsody.html b/pr-preview/pr-51/components/workflows/ingestion/bd_rhapsody.html new file mode 100644 index 00000000..410a6457 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/ingestion/bd_rhapsody.html @@ -0,0 +1,1897 @@ + + + + + + + + + + +OpenPipelines - BD Rhapsody + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

BD Rhapsody

+
+ +
+
+ A generic pipeline for running BD Rhapsody WTA or Targeted mapping, with support for AbSeq, VDJ and/or SMK. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: bd_rhapsody
+Namespace: ingestion

+
+ +

A wrapper for the BD Rhapsody Analysis CWL v1.10.1 pipeline.

+

This pipeline can be used for a targeted analysis (with --mode targeted) or for a whole transcriptome analysis (with --mode wta).

+
    +
  • If mode is "targeted", then either the --reference or --abseq_reference parameters must be defined.
    • +
  • If mode is "wta", then --reference and --transcriptome_annotation must be defined, --abseq_reference and --supplemental_reference is optional.
    • +
+

The reference_genome and transcriptome_annotation files can be generated with the make_reference pipeline. Alternatively, BD also provides standard references which can be downloaded from these locations:

+
    +
  • Human: http://bd-rhapsody-public.s3-website-us-east-1.amazonaws.com/Rhapsody-WTA/GRCh38-PhiX-gencodev29/
    • +
  • Mouse: http://bd-rhapsody-public.s3-website-us-east-1.amazonaws.com/Rhapsody-WTA/GRCm38-PhiX-gencodevM19/
    • +
+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/ingestion/bd_rhapsody/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+mode: # please fill in - example: "wta"
+id: # please fill in - example: "foo"
+input: # please fill in - example: ["input.fastq.gz"]
+reference: # please fill in - example: ["reference_genome.tar.gz|reference.fasta"]
+# transcriptome_annotation: "transcriptome.gtf"
+# abseq_reference: ["abseq_reference.fasta"]
+# supplemental_reference: ["supplemental_reference.fasta"]
+sample_prefix: "sample"
+
+# Outputs
+# output_raw: "$id.$key.output_raw.output_raw"
+# output_h5mu: "$id.$key.output_h5mu.h5mu"
+
+# Putative cell calling settings
+# putative_cell_call: "mRNA"
+# exact_cell_count: 10000
+disable_putative_calling: false
+
+# Subsample arguments
+# subsample: 0.01
+# subsample_seed: 3445
+
+# Multiplex arguments
+# sample_tags_version: "human"
+# tag_names: ["4-mySample", "9-myOtherSample", "6-alsoThisSample"]
+
+# VDJ arguments
+# vdj_version: "human"
+
+# CWL-runner arguments
+parallel: true
+timestamps: false
+dryrun: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/ingestion/bd_rhapsody/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--modeWhether to run a whole transcriptome analysis (WTA) or a targeted analysis.string, required, example: "wta"
--idID of the sample.string, required, example: "foo"
--inputPath to your read files in the FASTQ.GZ format. You may specify as many R1/R2 read pairs as you want.file, required, example: "input.fastq.gz"
--referenceRefence to map to. For --mode wta, this is the path to STAR index as a tar.gz file. For --mode targeted, this is the path to mRNA reference file for pre-designed, supplemental, or custom panel, in FASTA formatfile, required, example: "reference_genome.tar.gz&#124;reference.fasta"
--transcriptome_annotationPath to GTF annotation file (only for --mode wta).file, example: "transcriptome.gtf"
--abseq_referencePath to the AbSeq reference file in FASTA format. Only needed if BD AbSeq Ab-Oligos are used.file, example: "abseq_reference.fasta"
--supplemental_referencePath to the supplemental reference file in FASTA format. Only needed if there are additional transgene sequences used in the experiment (only for --mode wta).file, example: "supplemental_reference.fasta"
--sample_prefixSpecify a run name to use as the output file base name. Use only letters, numbers, or hyphens. Do not use special characters or spaces.string, default: "sample"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--output_rawThe BD Rhapsody output folder as it comes out of the BD Rhapsody pipelinefile, required, example: "output_dir"
--output_h5muThe converted h5mu file.file, required, example: "output.h5mu"
+
+
+

Putative cell calling settings

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--putative_cell_callSpecify the dataset to be used for putative cell calling. For putative cell calling using an AbSeq dataset, please provide an AbSeq_Reference fasta file above.string, example: "mRNA"
--exact_cell_countExact cell count - Set a specific number (>=1) of cells as putative, based on those with the highest error-corrected read countinteger, example: 10000
--disable_putative_callingDisable Refined Putative Cell Calling - Determine putative cells using only the basic algorithm (minimum second derivative along the cumulative reads curve). The refined algorithm attempts to remove false positives and recover false negatives, but may not be ideal for certain complex mixtures of cell types. Does not apply if Exact Cell Count is set.boolean_true
+
+
+

Subsample arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--subsampleA number >1 or fraction (0 < n < 1) to indicate the number or percentage of reads to subsample.double, example: 0.01
--subsample_seedA seed for replicating a previous subsampled run.integer, example: 3445
+
+
+

Multiplex arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--sample_tags_versionSpecify if multiplexed run.string, example: "human"
--tag_namesTag_Names (optional) - Specify the tag number followed by ‘-’ and the desired sample name to appear in Sample_Tag_Metrics.csv. Do not use the special characters: &, (), [], {}, <>, ?, |string, example: "4-mySample", example: "9-myOtherSample", example: "6-alsoThisSample"
+
+
+

VDJ arguments

+ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--vdj_versionSpecify if VDJ run.string, example: "human"
+
+
+

CWL-runner arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--parallelRun jobs in parallel.boolean, default: TRUE
--timestampsAdd timestamps to the errors, warnings, and notifications.boolean_true
--dryrunIf true, the output directory will only contain the CWL input files, but the pipeline itself will not be executed.boolean_true
+
+
+
+

Authors

+
    +
  • Robrecht Cannoodt (maintainer)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p10(bd_rhapsody)
+    p12(join)
+    p20(from_bdrhap_to_h5mu)
+    p22(join)
+    p28(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p12
+    p4-->p10
+    p10-->p12
+    p12-->p22
+    p12-->p20
+    p20-->p22
+    p22-->p28
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/ingestion/cellranger_mapping.html b/pr-preview/pr-51/components/workflows/ingestion/cellranger_mapping.html new file mode 100644 index 00000000..bbebad41 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/ingestion/cellranger_mapping.html @@ -0,0 +1,1760 @@ + + + + + + + + + + +OpenPipelines - Cell Ranger mapping + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cell Ranger mapping

+
+ +
+
+ A pipeline for running Cell Ranger mapping. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellranger_mapping
+Namespace: ingestion

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/ingestion/cellranger_mapping/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: ["sample_S1_L001_R1_001.fastq.gz", "sample_S1_L001_R2_001.fastq.gz"]
+reference: # please fill in - example: "reference.tar.gz"
+
+# Outputs
+# output_raw: "$id.$key.output_raw.output_raw"
+# output_h5mu: "$id.$key.output_h5mu.h5mu"
+obsm_metrics: "metrics_summary"
+output_type: "raw"
+
+# Cell Ranger arguments
+# expect_cells: 3000
+chemistry: "auto"
+secondary_analysis: false
+generate_bam: true
+include_introns: true
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/ingestion/cellranger_mapping/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputThe fastq.gz files to align. Can also be a single directory containing fastq.gz files.file, required, example: "sample_S1_L001_R1_001.fastq.gz", example: "sample_S1_L001_R2_001.fastq.gz"
--referenceThe path to Cell Ranger reference tar.gz file.file, required, example: "reference.tar.gz"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--output_rawLocation where the output folder from Cell Ranger will be stored.file, required, example: "output_dir"
--output_h5muThe output from Cell Ranger, converted to h5mu.file, required, example: "output.h5mu"
--obsm_metricsName of the .obsm slot under which to QC metrics (if any).string, default: "metrics_summary"
--output_typeWhich Cell Ranger output to use for converting to h5mu.string, default: "raw"
+
+
+

Cell Ranger arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--expect_cellsExpected number of recovered cells, used as input to cell calling algorithm.integer, example: 3000
--chemistryAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.string, default: "auto"
--secondary_analysisWhether or not to run the secondary analysis e.g. clustering.boolean, default: FALSE
--generate_bamWhether to generate a BAM file.boolean, default: TRUE
--include_intronsInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)boolean, default: TRUE
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Dries De Maeyer (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p11(cellranger_count)
+    p13(join)
+    p20(cellranger_count_split)
+    p22(join)
+    p30(from_10xh5_to_h5mu)
+    p32(join)
+    p39(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p13
+    p4-->p11
+    p11-->p13
+    p13-->p22
+    p13-->p20
+    p20-->p22
+    p22-->p32
+    p22-->p30
+    p30-->p32
+    p32-->p39
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/ingestion/cellranger_multi.html b/pr-preview/pr-51/components/workflows/ingestion/cellranger_multi.html new file mode 100644 index 00000000..22163d17 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/ingestion/cellranger_multi.html @@ -0,0 +1,1851 @@ + + + + + + + + + + +OpenPipelines - Cell Ranger multi + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cell Ranger multi

+
+ +
+
+ A pipeline for running Cell Ranger multi. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellranger_multi
+Namespace: ingestion

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/ingestion/cellranger_multi/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: ["sample_S1_L001_R1_001.fastq.gz", "sample_S1_L001_R2_001.fastq.gz"]
+gex_reference: # please fill in - example: "reference_genome.tar.gz"
+# vdj_reference: "reference_vdj.tar.gz"
+# feature_reference: "feature_reference.csv"
+# vdj_inner_enrichment_primers: "enrichment_primers.txt"
+
+# Outputs
+# output_raw: "$id.$key.output_raw.output_raw"
+# output_h5mu: "$id.$key.output_h5mu.h5mu"
+uns_metrics: "metrics_cellranger"
+
+# Cell multiplexing parameters
+# cell_multiplex_sample_id: "foo"
+# cell_multiplex_oligo_ids: "foo"
+# cell_multiplex_description: "foo"
+
+# Gene expression arguments
+# gex_expect_cells: 3000
+gex_chemistry: "auto"
+gex_secondary_analysis: false
+gex_generate_bam: true
+gex_include_introns: true
+
+# Library arguments
+library_id: # please fill in - example: ["mysample1"]
+library_type: # please fill in - example: ["Gene Expression"]
+# library_subsample: ["0.5"]
+# library_lanes: ["1-4"]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/ingestion/cellranger_multi/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputThe fastq.gz files to align. Can also be a single directory containing fastq.gz files.file, required, example: "sample_S1_L001_R1_001.fastq.gz", example: "sample_S1_L001_R2_001.fastq.gz"
--gex_referenceGenome refence index built by Cell Ranger mkref.file, required, example: "reference_genome.tar.gz"
--vdj_referenceVDJ refence index built by Cell Ranger mkref.file, example: "reference_vdj.tar.gz"
--feature_referencePath to the Feature reference CSV file, declaring Feature Barcode constructs and associated barcodes. Required only for Antibody Capture or CRISPR Guide Capture libraries. See https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/feature-bc-analysis#feature-ref for more information.file, example: "feature_reference.csv"
--vdj_inner_enrichment_primersV(D)J Immune Profiling libraries: if inner enrichment primers other than those provided in the 10x Genomics kits are used, they need to be specified here as a text file with one primer per line.file, example: "enrichment_primers.txt"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--output_rawThe raw output folder.file, required, example: "output_dir"
--output_h5muThe converted h5mu file.file, required, example: "output.h5mu"
--uns_metricsName of the .uns slot under which to QC metrics (if any).string, default: "metrics_cellranger"
+
+
+

Cell multiplexing parameters

+

Arguments related to cell multiplexing.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--cell_multiplex_sample_idA name to identify a multiplexed sample. Must be alphanumeric with hyphens and/or underscores, and less than 64 characters. Required for Cell Multiplexing libraries.string
--cell_multiplex_oligo_idsThe Cell Multiplexing oligo IDs used to multiplex this sample. If multiple CMOs were used for a sample, separate IDs with a pipe (e.g., CMO301|CMO302). Required for Cell Multiplexing libraries.string
--cell_multiplex_descriptionA description for the sample.string
+
+
+

Gene expression arguments

+

Arguments relevant to the analysis of gene expression data.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--gex_expect_cellsExpected number of recovered cells, used as input to cell calling algorithm.integer, example: 3000
--gex_chemistryAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.string, default: "auto"
--gex_secondary_analysisWhether or not to run the secondary analysis e.g. clustering.boolean, default: FALSE
--gex_generate_bamWhether to generate a BAM file.boolean, default: TRUE
--gex_include_intronsInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)boolean, default: TRUE
+
+
+

Library arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--library_idThe Illumina sample name to analyze. This must exactly match the ‘Sample Name’ part of the FASTQ files specified in the --input argument.string, required, example: "mysample1"
--library_typeThe underlying feature type of the library. Possible values: “Gene Expression”, “VDJ”, “VDJ-T”, “VDJ-B”, “Antibody Capture”, “CRISPR Guide Capture”, “Multiplexing Capture”string, required, example: "Gene Expression"
--library_subsampleOptional. The rate at which reads from the provided FASTQ files are sampled. Must be strictly greater than 0 and less than or equal to 1.string, example: "0.5"
--library_lanesLanes associated with this sample. Defaults to using all lanes.string, example: "1-4"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p11(cellranger_multi)
+    p13(join)
+    p20(from_cellranger_multi_to_h5mu)
+    p22(join)
+    p29(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p13
+    p4-->p11
+    p11-->p13
+    p13-->p22
+    p13-->p20
+    p20-->p22
+    p22-->p29
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/ingestion/cellranger_postprocessing.html b/pr-preview/pr-51/components/workflows/ingestion/cellranger_postprocessing.html new file mode 100644 index 00000000..354cbf5f --- /dev/null +++ b/pr-preview/pr-51/components/workflows/ingestion/cellranger_postprocessing.html @@ -0,0 +1,1764 @@ + + + + + + + + + + +OpenPipelines - Cell Ranger post-processing + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Cell Ranger post-processing

+
+ +
+
+ Post-processing Cell Ranger datasets. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: cellranger_postprocessing
+Namespace: ingestion

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/ingestion/cellranger_postprocessing/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "input.h5mu"
+
+# Outputs
+# output: "$id.$key.output.output"
+
+# Correction arguments
+perform_correction: false
+cellbender_epochs: 150
+
+# Filtering arguments
+# min_genes: 100
+# min_counts: 1000
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/ingestion/cellranger_postprocessing/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputInput h5mu file created by running Cell Ranger and converting its output to h5mu.file, required, example: "input.h5mu"
+
+
+

Outputs

+ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputThe converted h5mu file.file
+
+
+

Correction arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--perform_correctionWhether or not to run CellBender to perform count correction.boolean_true
--cellbender_epochsNumber of epochs to run CellBender for.integer, default: 150
+
+
+

Filtering arguments

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--min_genesMinimum number of counts required for a cell to pass filtering.integer, example: 100
--min_countsMinimum number of genes expressed required for a cell to pass filtering.integer, example: 1000
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p6(from_10xh5_to_h5mu)
+    p8(join)
+    p12(toSortedList)
+    p14(flatMap)
+    p15(filter)
+    p21(cellbender_remove_background)
+    p23(join)
+    p27(mix)
+    p26(filter)
+    p28(filter)
+    p34(filter_with_counts)
+    p36(join)
+    p40(mix)
+    p39(filter)
+    p46(publish)
+    p48(join)
+    p54(Output)
+    p14-->p15
+    p14-->p26
+    p26-->p27
+    p27-->p28
+    p27-->p39
+    p39-->p40
+    p0-->p8
+    p0-->p6
+    p6-->p8
+    p8-->p12
+    p12-->p14
+    p15-->p23
+    p15-->p21
+    p21-->p23
+    p23-->p27
+    p28-->p36
+    p28-->p34
+    p34-->p36
+    p36-->p40
+    p40-->p48
+    p40-->p46
+    p46-->p48
+    p48-->p54
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/ingestion/conversion.html b/pr-preview/pr-51/components/workflows/ingestion/conversion.html new file mode 100644 index 00000000..dd965576 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/ingestion/conversion.html @@ -0,0 +1,1729 @@ + + + + + + + + + + +OpenPipelines - Conversion + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Conversion

+
+ +
+
+ A pipeline to convert different file formats to .h5mu. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: conversion
+Namespace: ingestion

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/ingestion/conversion/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: ["input.h5mu"]
+input_type: # please fill in - example: "foo"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Conversion from h5ad
+# modality: ["foo"]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/ingestion/conversion/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "input.h5mu"
--input_typeType of the input filestring, required
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputName or template for the output files.file, example: "output.h5mu"
+
+
+

Conversion from h5ad

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--modalityName of the modality where the h5ad is stored in the h5mu object.string
+
+
+
+

Authors

+
    +

  • Dries Schaumont (author, maintainer)

    • +

  • Dries De Maeyer (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p5(filter)
+    p10(from_10xh5_to_h5mu)
+    p12(join)
+    p35(mix)
+    p15(filter)
+    p20(from_10xmtx_to_h5mu)
+    p22(join)
+    p25(filter)
+    p30(from_h5ad_to_h5mu)
+    p32(join)
+    p37(toSortedList)
+    p39(Output)
+    p4-->p5
+    p4-->p15
+    p4-->p25
+    p0-->p2
+    p2-->p4
+    p5-->p12
+    p5-->p10
+    p10-->p12
+    p12-->p35
+    p15-->p22
+    p15-->p20
+    p20-->p22
+    p22-->p35
+    p25-->p32
+    p25-->p30
+    p30-->p32
+    p32-->p35
+    p35-->p37
+    p37-->p39
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/ingestion/demux.html b/pr-preview/pr-51/components/workflows/ingestion/demux.html new file mode 100644 index 00000000..3dd2c51a --- /dev/null +++ b/pr-preview/pr-51/components/workflows/ingestion/demux.html @@ -0,0 +1,1705 @@ + + + + + + + + + + +OpenPipelines - Demux + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Demux

+
+ +
+
+ A generic pipeline for running bcl2fastq, bcl-convert or Cell Ranger mkfastq. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: demux
+Namespace: ingestion

+
+ +

Convert .bcl files to .fastq files using bcl2fastq, bcl-convert or Cell Ranger mkfastq.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/ingestion/demux/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Arguments
+id: # please fill in - example: "foo"
+input: # please fill in - example: "bcl_dir"
+sample_sheet: # please fill in - example: "bcl_dir"
+demultiplexer: "bcl2fastq"
+# ignore_missing: true
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/ingestion/demux/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument group

+
+

Arguments

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputInput run directoryfile, required, example: "bcl_dir"
--sample_sheetPointer to the sample sheetfile, required, example: "bcl_dir"
--demultiplexerThe multiplexer to use, one of bclconvert or mkfastqstring, default: "bcl2fastq"
--ignore_missingShould the demultiplexer ignore missing entities (filter, …)boolean
+
+
+
+

Authors

+
    +

  • Toni Verbeiren (author, maintainer)

    • +

  • Marijke Van Moerbeke (author)

    • +

  • Angela Oliveira Pisco (author)

    • +

  • Samuel D’Souza (author)

    • +

  • Robrecht Cannoodt (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p5(filter)
+    p10(cellranger_mkfastq)
+    p12(join)
+    p35(mix)
+    p15(filter)
+    p20(bcl_convert)
+    p22(join)
+    p25(filter)
+    p30(bcl2fastq)
+    p32(join)
+    p41(fastqc)
+    p43(join)
+    p46(Output)
+    p48(toSortedList)
+    p54(multiqc)
+    p56(join)
+    p59(Output)
+    p63(Output)
+    p4-->p5
+    p4-->p15
+    p4-->p25
+    p0-->p2
+    p2-->p4
+    p5-->p12
+    p5-->p10
+    p10-->p12
+    p12-->p35
+    p15-->p22
+    p15-->p20
+    p20-->p22
+    p22-->p35
+    p25-->p32
+    p25-->p30
+    p30-->p32
+    p32-->p35
+    p35-->p43
+    p35-->p41
+    p41-->p43
+    p43-->p46
+    p35-->p48
+    p48-->p56
+    p48-->p54
+    p54-->p56
+    p56-->p59
+    p35-->p63
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/ingestion/make_reference.html b/pr-preview/pr-51/components/workflows/ingestion/make_reference.html new file mode 100644 index 00000000..4679314e --- /dev/null +++ b/pr-preview/pr-51/components/workflows/ingestion/make_reference.html @@ -0,0 +1,1776 @@ + + + + + + + + + + +OpenPipelines - Make reference + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Make reference

+
+ +
+
+ Build a transcriptomics reference into one of many formats +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: make_reference
+Namespace: ingestion

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/ingestion/make_reference/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+genome_fasta: # please fill in - example: "https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/GRCh38.primary_assembly.genome.fa.gz"
+transcriptome_gtf: # please fill in - example: "https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/gencode.v41.annotation.gtf.gz"
+# ercc: "https://assets.thermofisher.com/TFS-Assets/LSG/manuals/ERCC92.zip"
+
+# Outputs
+target: ["star"]
+# output_fasta: "$id.$key.output_fasta.gz"
+# output_gtf: "$id.$key.output_gtf.gz"
+# output_cellranger: "$id.$key.output_cellranger.gz"
+# output_bd_rhapsody: "$id.$key.output_bd_rhapsody.gz"
+# output_star: "$id.$key.output_star.gz"
+
+# Arguments
+# subset_regex: "(ERCC-00002|chr1)"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/ingestion/make_reference/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the reference.string, required, example: "foo"
--genome_fastaReference genome fasta.file, required, example: "https:/ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/GRCh38.primary_assembly.genome.fa.gz"
--transcriptome_gtfReference transcriptome annotation.file, required, example: "https:/ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/gencode.v41.annotation.gtf.gz"
--erccERCC sequence and annotation file.file, example: "https:/assets.thermofisher.com/TFS-Assets/LSG/manuals/ERCC92.zip"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--targetWhich reference indices to generate.string, default: "star"
--output_fastaOutput genome sequence fasta.file, example: "genome_sequence.fa.gz"
--output_gtfOutput transcriptome annotation gtf.file, example: "transcriptome_annotation.gtf.gz"
--output_cellrangerOutput indexfile, example: "cellranger_index.tar.gz"
--output_bd_rhapsodyOutput indexfile, example: "bdrhap_index.tar.gz"
--output_starOutput indexfile, example: "star_index.tar.gz"
+
+
+

Arguments

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--subset_regexWill subset the reference chromosomes using the given regex.string, example: "(ERCC-00002&#124;chr1)"
+
+
+
+

Authors

+
    +

  • Angela Oliveira Pisco (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p11(make_reference)
+    p13(join)
+    p17(filter)
+    p22(build_cellranger_reference)
+    p24(join)
+    p54(join)
+    p29(filter)
+    p34(build_bdrhap_reference)
+    p36(join)
+    p55(join)
+    p41(filter)
+    p46(star_build_reference)
+    p48(join)
+    p56(join)
+    p57(join)
+    p62(Output)
+    p54-->p55
+    p55-->p56
+    p56-->p57
+    p0-->p2
+    p2-->p4
+    p4-->p13
+    p4-->p11
+    p11-->p13
+    p13-->p17
+    p17-->p24
+    p17-->p22
+    p22-->p24
+    p24-->p54
+    p13-->p29
+    p29-->p36
+    p29-->p34
+    p34-->p36
+    p36-->p55
+    p13-->p41
+    p41-->p48
+    p41-->p46
+    p46-->p48
+    p48-->p56
+    p0-->p57
+    p13-->p54
+    p57-->p62
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/integration/common/harmony_leiden.html b/pr-preview/pr-51/components/workflows/integration/common/harmony_leiden.html new file mode 100644 index 00000000..3094df23 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/integration/common/harmony_leiden.html @@ -0,0 +1,1834 @@ + + + + + + + + + + +OpenPipelines - Harmony leiden + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Harmony leiden

+
+ +
+
+ Run harmony integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: harmony_leiden
+Namespace: integration/common

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -main-script workflows/multiomics/integration/harmony_leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Neighbour calculation
+uns_neighbors: "harmonypy_integration_neighbors"
+obsp_neighbor_distances: "harmonypy_integration_distances"
+obsp_neighbor_connectivities: "harmonypy_integration_connectivities"
+
+# Harmony integration options
+embedding: "X_pca"
+obsm_integrated: "X_pca_integrated"
+obs_covariates: # please fill in - example: ["batch", "sample"]
+theta: [2]
+
+# Clustering options
+obs_cluster: "harmony_integration_leiden"
+leiden_resolution: [1]
+
+# Umap options
+obsm_umap: "X_leiden_harmony_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -profile docker \
+  -main-script workflows/multiomics/integration/harmony_leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "harmonypy_integration_neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "harmonypy_integration_distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "harmonypy_integration_connectivities"
+
+
+

Harmony integration options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--embeddingEmbedding to use as inputstring, default: "X_pca"
--obsm_integratedIn which .obsm slot to store the resulting integrated embedding.string, default: "X_pca_integrated"
--obs_covariatesThe .obs field(s) that define the covariate(s) to regress out.string, required, example: "batch", example: "sample"
--thetaDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.”double, default: 2
+
+
+

Clustering options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_clusterName of the .obs key under which to add the cluster labels.string, default: "harmony_integration_leiden"
--leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_leiden_harmony_umap"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p12(harmonypy)
+    p22(find_neighbors)
+    p32(leiden)
+    p42(umap)
+    p52(move_obsm_to_obs)
+    p60(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p12
+    p12-->p22
+    p22-->p32
+    p32-->p42
+    p42-->p52
+    p52-->p60
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/integration/initialize_integration/initialize_integration.html b/pr-preview/pr-51/components/workflows/integration/initialize_integration/initialize_integration.html new file mode 100644 index 00000000..b6a5efe8 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/integration/initialize_integration/initialize_integration.html @@ -0,0 +1,1785 @@ + + + + + + + + + + +OpenPipelines - Initialize integration + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Initialize integration

+
+ +
+
+ Run calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: initialize_integration
+Namespace: integration/initialize_integration

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -main-script workflows/multiomics/integration/initialize_integration/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# PCA options
+obsm_pca: "X_pca"
+# var_pca_feature_selection: "foo"
+
+# Neighbour calculation
+uns_neighbors: "neighbors"
+obsp_neighbor_distances: "distances"
+obsp_neighbor_connectivities: "connectivities"
+
+# Umap options
+obsm_umap: "X_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -profile docker \
+  -main-script workflows/multiomics/integration/initialize_integration/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

PCA options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_pcaIn which .obsm slot to store the resulting PCA embedding.string, default: "X_pca"
--var_pca_feature_selectionColumn name in .var matrix that will be used to select which genes to run the PCA on.string
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "connectivities"
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_umap"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p12(pca)
+    p22(find_neighbors)
+    p32(umap)
+    p40(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p12
+    p12-->p22
+    p22-->p32
+    p32-->p40
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/integration/scanorama_leiden/scanorama_leiden.html b/pr-preview/pr-51/components/workflows/integration/scanorama_leiden/scanorama_leiden.html new file mode 100644 index 00000000..6afefbde --- /dev/null +++ b/pr-preview/pr-51/components/workflows/integration/scanorama_leiden/scanorama_leiden.html @@ -0,0 +1,1859 @@ + + + + + + + + + + +OpenPipelines - Scanorama leiden + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scanorama leiden

+
+ +
+
+ Run scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scanorama_leiden
+Namespace: integration/scanorama_leiden

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -main-script workflows/multiomics/integration/scanorama_leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Neighbour calculation
+uns_neighbors: "scanorama_integration_neighbors"
+obsp_neighbor_distances: "scanorama_integration_distances"
+obsp_neighbor_connectivities: "scanorama_integration_connectivities"
+
+# Scanorama integration options
+obs_batch: "sample_id"
+obsm_input: "X_pca"
+obsm_output: "X_scanorama"
+knn: 20
+batch_size: 5000
+sigma: 15
+approx: true
+alpha: 0.1
+
+# Clustering options
+obs_cluster: "scanorama_integration_leiden"
+leiden_resolution: [1]
+
+# Umap options
+obsm_umap: "X_leiden_scanorama_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -profile docker \
+  -main-script workflows/multiomics/integration/scanorama_leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "scanorama_integration_neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "scanorama_integration_distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "scanorama_integration_connectivities"
+
+
+

Scanorama integration options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_batchColumn name discriminating between your batches.string, default: "sample_id"
--obsm_input.osbm slot that points to embedding to run scanorama on.string, default: "X_pca"
--obsm_outputThe name of the field in adata.obsm where the integrated embeddings will be stored after running this function. Defaults to X_scanorama.string, default: "X_scanorama"
--knnNumber of nearest neighbors to use for matching.integer, default: 20
--batch_sizeThe batch size used in the alignment vector computation. Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory.integer, default: 5000
--sigmaCorrection smoothing parameter on Gaussian kernel.double, default: 15
--approxUse approximate nearest neighbors with Python annoy; greatly speeds up matching runtime.boolean, default: TRUE
--alphaAlignment score minimum cutoffdouble, default: 0.1
+
+
+

Clustering options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_clusterName of the .obs key under which to add the cluster labels.string, default: "scanorama_integration_leiden"
--leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_leiden_scanorama_umap"
+
+
+
+

Authors

+
    +

  • Mauro Saporita (author)

    • +

  • Povilas Gibas (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p12(scanorama)
+    p22(find_neighbors)
+    p32(leiden)
+    p42(umap)
+    p52(move_obsm_to_obs)
+    p60(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p12
+    p12-->p22
+    p22-->p32
+    p32-->p42
+    p42-->p52
+    p52-->p60
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/integration/scvi/scvi.html b/pr-preview/pr-51/components/workflows/integration/scvi/scvi.html new file mode 100644 index 00000000..34ece1cb --- /dev/null +++ b/pr-preview/pr-51/components/workflows/integration/scvi/scvi.html @@ -0,0 +1,1839 @@ + + + + + + + + + + +OpenPipelines - Scvi + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scvi

+
+ +
+
+ Run scvi integration followed by neighbour calculations and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scvi
+Namespace: integration/scvi

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -main-script workflows/multiomics/integration/scvi/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_model: "$id.$key.output_model.output_model"
+
+# Neighbour calculation
+uns_neighbors: "scvi_integration_neighbors"
+obsp_neighbor_distances: "scvi_integration_distances"
+obsp_neighbor_connectivities: "scvi_integration_connectivities"
+
+# Scvi integration options
+obs_batch: # please fill in - example: "foo"
+obsm_output: "X_scvi_integrated"
+# early_stopping: true
+early_stopping_monitor: "elbo_validation"
+early_stopping_patience: 45
+early_stopping_min_delta: 0.0
+# max_epochs: 123
+reduce_lr_on_plateau: true
+lr_factor: 0.6
+lr_patience: 30
+
+# Umap options
+obsm_umap: "X_scvi_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.9.0 -latest \
+  -profile docker \
+  -main-script workflows/multiomics/integration/scvi/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
--output_modelFolder where the state of the trained model will be saved to.file, required, example: "output_dir"
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "scvi_integration_neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "scvi_integration_distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "scvi_integration_connectivities"
+
+
+

Scvi integration options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_batchColumn name discriminating between your batches.string, required
--obsm_outputIn which .obsm slot to store the resulting integrated embedding.string, default: "X_scvi_integrated"
--early_stoppingWhether to perform early stopping with respect to the validation set.boolean
--early_stopping_monitorMetric logged during validation set epoch.string, default: "elbo_validation"
--early_stopping_patienceNumber of validation epochs with no improvement after which training will be stopped.integer, default: 45
--early_stopping_min_deltaMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.double, default: 0
--max_epochsNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.integer
--reduce_lr_on_plateauWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.boolean, default: TRUE
--lr_factorFactor to reduce learning rate.double, default: 0.6
--lr_patienceNumber of epochs with no improvement after which learning rate will be reduced.double, default: 30
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_scvi_umap"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p3(toSortedList)
+    p5(flatMap)
+    p13(scvi)
+    p24(find_neighbors)
+    p34(umap)
+    p42(Output)
+    p0-->p3
+    p3-->p5
+    p5-->p13
+    p13-->p24
+    p24-->p34
+    p34-->p42
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/full_pipeline.html b/pr-preview/pr-51/components/workflows/multiomics/full_pipeline.html new file mode 100644 index 00000000..49f09fae --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/full_pipeline.html @@ -0,0 +1,2163 @@ + + + + + + + + + + +OpenPipelines - Full pipeline + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Full pipeline

+
+ +
+
+ A pipeline to analyse multiple multiomics samples. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: full_pipeline
+Namespace: multiomics

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/full_pipeline/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "input.h5mu"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Sample ID options
+add_id_to_obs: true
+add_id_obs_output: "sample_id"
+add_id_make_observation_keys_unique: true
+
+# RNA filtering options
+# rna_min_counts: 200
+# rna_max_counts: 5000000
+# rna_min_genes_per_cell: 200
+# rna_max_genes_per_cell: 1500000
+# rna_min_cells_per_gene: 3
+# rna_min_fraction_mito: 0
+# rna_max_fraction_mito: 0.2
+
+# CITE-seq filtering options
+# prot_min_counts: 3
+# prot_max_counts: 5000000
+# prot_min_proteins_per_cell: 200
+# prot_max_proteins_per_cell: 100000000
+# prot_min_cells_per_protein: 3
+
+# Highly variable gene detection
+filter_with_hvg_var_output: "filter_with_hvg"
+filter_with_hvg_obs_batch_key: "sample_id"
+
+# Mitochondrial Gene Detection
+# var_name_mitochondrial_genes: "foo"
+# var_gene_names: "gene_symbol"
+mitochondrial_gene_regex: "^[mM][tT]-"
+
+# QC metrics calculation options
+# var_qc_metrics: ["ercc", "highly_variable"]
+top_n_vars: [50, 100, 200, 500]
+
+# PCA options
+pca_overwrite: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/full_pipeline/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "input.h5mu"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Sample ID options

+

Options for adding the id to .obs on the MuData object. Having a sample id present in a requirement of several components for this pipeline.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--add_id_to_obsAdd the value passed with –id to .obs.boolean, default: TRUE
--add_id_obs_output.Obs column to add the sample IDs to. Required and only used when –add_id_to_obs is set to ‘true’string, default: "sample_id"
--add_id_make_observation_keys_uniqueJoin the id to the .obs index (.obs_names). Only used when –add_id_to_obs is set to ‘true’.boolean, default: TRUE
+
+
+

RNA filtering options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--rna_min_countsMinimum number of counts captured per cell.integer, example: 200
--rna_max_countsMaximum number of counts captured per cell.integer, example: 5000000
--rna_min_genes_per_cellMinimum of non-zero values per cell.integer, example: 200
--rna_max_genes_per_cellMaximum of non-zero values per cell.integer, example: 1500000
--rna_min_cells_per_geneMinimum of non-zero values per gene.integer, example: 3
--rna_min_fraction_mitoMinimum fraction of UMIs that are mitochondrial.double, example: 0
--rna_max_fraction_mitoMaximum fraction of UMIs that are mitochondrial.double, example: 0.2
+
+
+

CITE-seq filtering options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--prot_min_countsMinimum number of counts per cell.integer, example: 3
--prot_max_countsMinimum number of counts per cell.integer, example: 5000000
--prot_min_proteins_per_cellMinimum of non-zero values per cell.integer, example: 200
--prot_max_proteins_per_cellMaximum of non-zero values per cell.integer, example: 100000000
--prot_min_cells_per_proteinMinimum of non-zero values per protein.integer, example: 3
+
+
+

Highly variable gene detection

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--filter_with_hvg_var_outputIn which .var slot to store a boolean array corresponding to the highly variable genes.string, default: "filter_with_hvg"
--filter_with_hvg_obs_batch_keyIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method.string, default: "sample_id"
+
+
+

Mitochondrial Gene Detection

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--var_name_mitochondrial_genesIn which .var slot to store a boolean array corresponding the mitochondrial genes.string
--var_gene_names.var column name to be used to detect mitochondrial genes instead of .var_names (default if not set). Gene names matching with the regex value from –mitochondrial_gene_regex will be identified as a mitochondrial gene.string, example: "gene_symbol"
--mitochondrial_gene_regexRegex string that identifies mitochondrial genes from –var_gene_names. By default will detect human and mouse mitochondrial genes from a gene symbol.string, default: "^[mM][tT]-"
+
+
+

QC metrics calculation options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--var_qc_metricsKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes. Defaults to the combined values specified for –var_name_mitochondrial_genes and –filter_with_hvg_var_output.string, example: "ercc,highly_variable"
--top_n_varsNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.integer, default: 50, default: 100, default: 200, default: 500
+
+
+

PCA options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--pca_overwriteAllow overwriting slots for PCA output.boolean_true
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author, maintainer)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p7(toSortedList)
+    p9(Output)
+    p11(filter)
+    p17(add_id)
+    p19(join)
+    p23(mix)
+    p22(filter)
+    p25(filter)
+    p30(split_modalities)
+    p32(join)
+    p39(concat)
+    p35(filter)
+    p37(test_wf:run_wf:split_modalities_workflow:splitStub)
+    p40(flatMap)
+    p41(filter)
+    p44(toSortedList)
+    p46(flatMap)
+    p53(filter_with_counts)
+    p55(join)
+    p63(do_filter)
+    p65(join)
+    p73(filter_with_scrublet)
+    p75(join)
+    p110(concat)
+    p79(filter)
+    p82(toSortedList)
+    p84(flatMap)
+    p91(test_wf:run_wf:singlesample_processing_workflow:prot_singlesample:filter_with_counts:filter_with_counts_process1)
+    p93(join)
+    p101(test_wf:run_wf:singlesample_processing_workflow:prot_singlesample:do_filter:do_filter_process1)
+    p103(join)
+    p108(filter)
+    p112(groupTuple)
+    p118(concat)
+    p120(join)
+    p125(filter)
+    p128(toSortedList)
+    p130(flatMap)
+    p132(toSortedList)
+    p134(Output)
+    p140(normalize_total)
+    p142(join)
+    p150(log1p)
+    p152(join)
+    p160(delete_layer)
+    p162(join)
+    p170(filter_with_hvg)
+    p172(join)
+    p180(rna_calculate_qc_metrics)
+    p182(join)
+    p223(concat)
+    p188(filter)
+    p191(toSortedList)
+    p193(flatMap)
+    p195(toSortedList)
+    p197(Output)
+    p203(clr)
+    p205(join)
+    p213(prot_calculate_qc_metrics)
+    p215(join)
+    p221(filter)
+    p224(toSortedList)
+    p230(merge)
+    p232(join)
+    p235(filter)
+    p239(toSortedList)
+    p241(flatMap)
+    p248(pca)
+    p250(join)
+    p258(find_neighbors)
+    p260(join)
+    p268(umap)
+    p270(join)
+    p275(concat)
+    p274(filter)
+    p276(filter)
+    p280(toSortedList)
+    p282(flatMap)
+    p289(pca)
+    p291(join)
+    p299(find_neighbors)
+    p301(join)
+    p309(test_wf:run_wf:integration_setup_workflow:initialize_integration_prot:umap:umap_process1)
+    p311(join)
+    p316(concat)
+    p315(filter)
+    p322(publish)
+    p324(join)
+    p329(toSortedList)
+    p331(Output)
+    p22-->p23
+    p39-->p40
+    p40-->p41
+    p40-->p79
+    p40-->p108
+    p223-->p224
+    p274-->p275
+    p275-->p276
+    p275-->p315
+    p315-->p316
+    p0-->p2
+    p2-->p4
+    p4-->p7
+    p7-->p9
+    p4-->p11
+    p4-->p22
+    p11-->p19
+    p11-->p17
+    p17-->p19
+    p19-->p23
+    p23-->p25
+    p23-->p35
+    p25-->p32
+    p25-->p30
+    p30-->p32
+    p32-->p39
+    p35-->p37
+    p37-->p39
+    p41-->p44
+    p44-->p46
+    p46-->p55
+    p46-->p53
+    p53-->p55
+    p55-->p65
+    p55-->p63
+    p63-->p65
+    p65-->p75
+    p65-->p73
+    p73-->p75
+    p75-->p110
+    p79-->p82
+    p82-->p84
+    p84-->p93
+    p84-->p91
+    p91-->p93
+    p93-->p103
+    p93-->p101
+    p101-->p103
+    p103-->p110
+    p108-->p110
+    p110-->p112
+    p112-->p120
+    p112-->p118
+    p118-->p120
+    p120-->p125
+    p120-->p188
+    p120-->p221
+    p125-->p128
+    p128-->p130
+    p130-->p132
+    p132-->p134
+    p130-->p142
+    p130-->p140
+    p140-->p142
+    p142-->p152
+    p142-->p150
+    p150-->p152
+    p152-->p162
+    p152-->p160
+    p160-->p162
+    p162-->p172
+    p162-->p170
+    p170-->p172
+    p172-->p182
+    p172-->p180
+    p180-->p182
+    p182-->p223
+    p188-->p191
+    p191-->p193
+    p193-->p195
+    p195-->p197
+    p193-->p205
+    p193-->p203
+    p203-->p205
+    p205-->p215
+    p205-->p213
+    p213-->p215
+    p215-->p223
+    p221-->p223
+    p224-->p232
+    p224-->p230
+    p230-->p232
+    p232-->p235
+    p232-->p274
+    p235-->p239
+    p239-->p241
+    p241-->p250
+    p241-->p248
+    p248-->p250
+    p250-->p260
+    p250-->p258
+    p258-->p260
+    p260-->p270
+    p260-->p268
+    p268-->p270
+    p270-->p275
+    p276-->p280
+    p280-->p282
+    p282-->p291
+    p282-->p289
+    p289-->p291
+    p291-->p301
+    p291-->p299
+    p299-->p301
+    p301-->p311
+    p301-->p309
+    p309-->p311
+    p311-->p316
+    p316-->p324
+    p316-->p322
+    p322-->p324
+    p324-->p329
+    p329-->p331
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/integration.html b/pr-preview/pr-51/components/workflows/multiomics/integration.html new file mode 100644 index 00000000..319f537f --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/integration.html @@ -0,0 +1,1879 @@ + + + + + + + + + + +OpenPipelines - Integration + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Integration

+
+ +
+
+ A pipeline for demultiplexing multimodal multi-sample RNA transcriptomics data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: integration
+Namespace: multiomics

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.8.0 -latest \
+  -main-script workflows/multiomics/integration/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# PCA options
+obsm_pca: "X_pca"
+# var_pca_feature_selection: "foo"
+
+# Harmony integration options
+obsm_integrated: "X_pca_integrated"
+obs_covariates: # please fill in - example: ["batch", "sample"]
+rna_theta: [2]
+
+# Neighbour calculation
+uns_neighbors: "neighbors"
+obsp_neighbor_distances: "distances"
+obsp_neighbor_connectivities: "connectivities"
+
+# Clustering options
+obs_cluster: "leiden"
+leiden_resolution: 1
+
+# Umap options
+obsm_umap: "X_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.8.0 -latest \
+  -profile docker \
+  -main-script workflows/multiomics/integration/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

PCA options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_pcaIn which .obsm slot to store the resulting PCA embedding.string, default: "X_pca"
--var_pca_feature_selectionColumn name in .var matrix that will be used to select which genes to run the PCA on.string
+
+
+

Harmony integration options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_integratedIn which .obsm slot to store the resulting integrated embedding.string, default: "X_pca_integrated"
--obs_covariatesThe .obs field(s) that define the covariate(s) to regress out.string, required, example: "batch", example: "sample"
--rna_thetaDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.”double, default: 2
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "connectivities"
+
+
+

Clustering options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_clusterName of the .obs key under which to add the cluster labels.string, default: "leiden"
--leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_umap"
+
+
+
+

Authors

+
    +
  • Dries De Maeyer (author)
    • +
  • Robrecht Cannoodt (author, maintainer)
    • +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p15(join)
+    p13(pca)
+    p18(filter)
+    p29(concat)
+    p19(filter)
+    p27(join)
+    p25(harmonypy)
+    p38(join)
+    p36(find_neighbors)
+    p48(join)
+    p46(leiden)
+    p58(join)
+    p56(umap)
+    p64(Output)
+    p18-->p29
+    p0-->p2
+    p2-->p4
+    p4-->p15
+    p4-->p13
+    p13-->p15
+    p15-->p18
+    p15-->p19
+    p19-->p27
+    p19-->p25
+    p25-->p27
+    p27-->p29
+    p29-->p38
+    p29-->p36
+    p36-->p38
+    p38-->p48
+    p38-->p46
+    p46-->p48
+    p48-->p58
+    p48-->p56
+    p56-->p58
+    p58-->p64
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/integration/bbknn_leiden.html b/pr-preview/pr-51/components/workflows/multiomics/integration/bbknn_leiden.html new file mode 100644 index 00000000..8943e9db --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/integration/bbknn_leiden.html @@ -0,0 +1,1830 @@ + + + + + + + + + + +OpenPipelines - Bbknn leiden + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Bbknn leiden

+
+ +
+
+ Run bbknn followed by leiden clustering and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: bbknn_leiden
+Namespace: multiomics/integration

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/integration/bbknn_leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Bbknn
+obsm_input: "X_pca"
+obs_batch: "sample_id"
+uns_output: "bbknn_integration_neighbors"
+obsp_distances: "bbknn_integration_distances"
+obsp_connectivities: "bbknn_integration_connectivities"
+n_neighbors_within_batch: 3
+n_pcs: 50
+# n_trim: 123
+
+# Clustering options
+obs_cluster: "bbknn_integration_leiden"
+leiden_resolution: 1
+
+# UMAP options
+obsm_umap: "X_leiden_bbknn_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/integration/bbknn_leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Bbknn

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_inputThe dimensionality reduction in .obsm to use for neighbour detection. Defaults to X_pca.string, default: "X_pca"
--obs_batch.obs column name discriminating between your batches.string, default: "sample_id"
--uns_outputMandatory .uns slot to store various neighbor output objects.string, default: "bbknn_integration_neighbors"
--obsp_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "bbknn_integration_distances"
--obsp_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "bbknn_integration_connectivities"
--n_neighbors_within_batchHow many top neighbours to report for each batch; total number of neighbours in the initial k-nearest-neighbours computation will be this number times the number of batches.integer, default: 3
--n_pcsHow many dimensions (in case of PCA, principal components) to use in the analysis.integer, default: 50
--n_trimTrim the neighbours of each cell to these many top connectivities. May help with population independence and improve the tidiness of clustering. The lower the value the more independent the individual populations, at the cost of more conserved batch effect. If None (default), sets the parameter value automatically to 10 times neighbors_within_batch times the number of batches. Set to 0 to skip.integer
+
+
+

Clustering options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_clusterPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.string, default: "bbknn_integration_leiden"
--leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

UMAP options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_leiden_bbknn_umap"
+
+
+
+

Authors

+
    +

  • Mauro Saporita (author)

    • +

  • Povilas Gibas (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p10(bbknn)
+    p12(join)
+    p20(leiden)
+    p22(join)
+    p30(umap)
+    p32(join)
+    p40(move_obsm_to_obs)
+    p42(join)
+    p48(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p12
+    p4-->p10
+    p10-->p12
+    p12-->p22
+    p12-->p20
+    p20-->p22
+    p22-->p32
+    p22-->p30
+    p30-->p32
+    p32-->p42
+    p32-->p40
+    p40-->p42
+    p42-->p48
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/integration/harmony_leiden.html b/pr-preview/pr-51/components/workflows/multiomics/integration/harmony_leiden.html new file mode 100644 index 00000000..60d2f503 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/integration/harmony_leiden.html @@ -0,0 +1,1849 @@ + + + + + + + + + + +OpenPipelines - Harmony leiden + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Harmony leiden

+
+ +
+
+ Run harmony integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: harmony_leiden
+Namespace: multiomics/integration

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/integration/harmony_leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Neighbour calculation
+uns_neighbors: "harmonypy_integration_neighbors"
+obsp_neighbor_distances: "harmonypy_integration_distances"
+obsp_neighbor_connectivities: "harmonypy_integration_connectivities"
+
+# Harmony integration options
+embedding: "X_pca"
+obsm_integrated: "X_pca_integrated"
+obs_covariates: # please fill in - example: ["batch", "sample"]
+theta: [2]
+
+# Clustering options
+obs_cluster: "harmony_integration_leiden"
+leiden_resolution: [1]
+
+# Umap options
+obsm_umap: "X_leiden_harmony_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/integration/harmony_leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "harmonypy_integration_neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "harmonypy_integration_distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "harmonypy_integration_connectivities"
+
+
+

Harmony integration options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--embeddingEmbedding to use as inputstring, default: "X_pca"
--obsm_integratedIn which .obsm slot to store the resulting integrated embedding.string, default: "X_pca_integrated"
--obs_covariatesThe .obs field(s) that define the covariate(s) to regress out.string, required, example: "batch", example: "sample"
--thetaDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.”double, default: 2
+
+
+

Clustering options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_clusterPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.string, default: "harmony_integration_leiden"
--leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_leiden_harmony_umap"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p10(harmonypy)
+    p12(join)
+    p20(find_neighbors)
+    p22(join)
+    p30(leiden)
+    p32(join)
+    p40(umap)
+    p42(join)
+    p50(move_obsm_to_obs)
+    p52(join)
+    p58(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p12
+    p4-->p10
+    p10-->p12
+    p12-->p22
+    p12-->p20
+    p20-->p22
+    p22-->p32
+    p22-->p30
+    p30-->p32
+    p32-->p42
+    p32-->p40
+    p40-->p42
+    p42-->p52
+    p42-->p50
+    p50-->p52
+    p52-->p58
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/integration/initialize_integration.html b/pr-preview/pr-51/components/workflows/multiomics/integration/initialize_integration.html new file mode 100644 index 00000000..1b7fe2a0 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/integration/initialize_integration.html @@ -0,0 +1,1802 @@ + + + + + + + + + + +OpenPipelines - Initialize integration + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Initialize integration

+
+ +
+
+ Run calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: initialize_integration
+Namespace: multiomics/integration

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/integration/initialize_integration/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# PCA options
+obsm_pca: "X_pca"
+# var_pca_feature_selection: "foo"
+pca_overwrite: false
+
+# Neighbour calculation
+uns_neighbors: "neighbors"
+obsp_neighbor_distances: "distances"
+obsp_neighbor_connectivities: "connectivities"
+
+# Umap options
+obsm_umap: "X_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/integration/initialize_integration/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

PCA options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_pcaIn which .obsm slot to store the resulting PCA embedding.string, default: "X_pca"
--var_pca_feature_selectionColumn name in .var matrix that will be used to select which genes to run the PCA on.string
--pca_overwriteAllow overwriting slots for PCA output.boolean_true
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "connectivities"
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_umap"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p11(pca)
+    p13(join)
+    p21(find_neighbors)
+    p23(join)
+    p31(umap)
+    p33(join)
+    p38(toSortedList)
+    p40(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p13
+    p4-->p11
+    p11-->p13
+    p13-->p23
+    p13-->p21
+    p21-->p23
+    p23-->p33
+    p23-->p31
+    p31-->p33
+    p33-->p38
+    p38-->p40
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/integration/leiden_scvi.html b/pr-preview/pr-51/components/workflows/multiomics/integration/leiden_scvi.html new file mode 100644 index 00000000..1637ad6f --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/integration/leiden_scvi.html @@ -0,0 +1,1891 @@ + + + + + + + + + + +OpenPipelines - Leiden scvi + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Leiden scvi

+
+ +
+
+ Run scvi integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: leiden_scvi
+Namespace: multiomics/integration

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/integration/scvi_leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# output_model: "$id.$key.output_model.output_model"
+
+# Neighbour calculation
+uns_neighbors: "scvi_integration_neighbors"
+obsp_neighbor_distances: "scvi_integration_distances"
+obsp_neighbor_connectivities: "scvi_integration_connectivities"
+
+# Scvi integration options
+obs_batch: # please fill in - example: "foo"
+obsm_output: "X_scvi_integrated"
+# early_stopping: true
+early_stopping_monitor: "elbo_validation"
+early_stopping_patience: 45
+early_stopping_min_delta: 0.0
+# max_epochs: 123
+reduce_lr_on_plateau: true
+lr_factor: 0.6
+lr_patience: 30
+
+# Clustering options
+obs_cluster: "scvi_integration_leiden"
+leiden_resolution: [1]
+
+# Umap options
+obsm_umap: "X_scvi_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/integration/scvi_leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
--output_modelFolder where the state of the trained model will be saved to.file, required, example: "output_dir"
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "scvi_integration_neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "scvi_integration_distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "scvi_integration_connectivities"
+
+
+

Scvi integration options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_batchColumn name discriminating between your batches.string, required
--obsm_outputIn which .obsm slot to store the resulting integrated embedding.string, default: "X_scvi_integrated"
--early_stoppingWhether to perform early stopping with respect to the validation set.boolean
--early_stopping_monitorMetric logged during validation set epoch.string, default: "elbo_validation"
--early_stopping_patienceNumber of validation epochs with no improvement after which training will be stopped.integer, default: 45
--early_stopping_min_deltaMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.double, default: 0
--max_epochsNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.integer
--reduce_lr_on_plateauWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.boolean, default: TRUE
--lr_factorFactor to reduce learning rate.double, default: 0.6
--lr_patienceNumber of epochs with no improvement after which learning rate will be reduced.double, default: 30
+
+
+

Clustering options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_clusterPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.string, default: "scvi_integration_leiden"
--leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_scvi_umap"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p3(toSortedList)
+    p5(flatMap)
+    p12(scvi)
+    p14(join)
+    p23(find_neighbors)
+    p25(join)
+    p33(leiden)
+    p35(join)
+    p43(umap)
+    p45(join)
+    p53(move_obsm_to_obs)
+    p55(join)
+    p62(Output)
+    p0-->p3
+    p3-->p5
+    p5-->p14
+    p5-->p12
+    p12-->p14
+    p14-->p25
+    p14-->p23
+    p23-->p25
+    p25-->p35
+    p25-->p33
+    p33-->p35
+    p35-->p45
+    p35-->p43
+    p43-->p45
+    p45-->p55
+    p45-->p53
+    p53-->p55
+    p55-->p62
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/integration/scanorama_leiden.html b/pr-preview/pr-51/components/workflows/multiomics/integration/scanorama_leiden.html new file mode 100644 index 00000000..c073e34a --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/integration/scanorama_leiden.html @@ -0,0 +1,1874 @@ + + + + + + + + + + +OpenPipelines - Scanorama leiden + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Scanorama leiden

+
+ +
+
+ Run scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: scanorama_leiden
+Namespace: multiomics/integration

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/integration/scanorama_leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Neighbour calculation
+uns_neighbors: "scanorama_integration_neighbors"
+obsp_neighbor_distances: "scanorama_integration_distances"
+obsp_neighbor_connectivities: "scanorama_integration_connectivities"
+
+# Scanorama integration options
+obs_batch: "sample_id"
+obsm_input: "X_pca"
+obsm_output: "X_scanorama"
+knn: 20
+batch_size: 5000
+sigma: 15
+approx: true
+alpha: 0.1
+
+# Clustering options
+obs_cluster: "scanorama_integration_leiden"
+leiden_resolution: [1]
+
+# Umap options
+obsm_umap: "X_leiden_scanorama_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/integration/scanorama_leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Neighbour calculation

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "scanorama_integration_neighbors"
--obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "scanorama_integration_distances"
--obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "scanorama_integration_connectivities"
+
+
+

Scanorama integration options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_batchColumn name discriminating between your batches.string, default: "sample_id"
--obsm_input.obsm slot that points to embedding to run scanorama on.string, default: "X_pca"
--obsm_outputThe name of the field in adata.obsm where the integrated embeddings will be stored after running this function. Defaults to X_scanorama.string, default: "X_scanorama"
--knnNumber of nearest neighbors to use for matching.integer, default: 20
--batch_sizeThe batch size used in the alignment vector computation. Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory.integer, default: 5000
--sigmaCorrection smoothing parameter on Gaussian kernel.double, default: 15
--approxUse approximate nearest neighbors with Python annoy; greatly speeds up matching runtime.boolean, default: TRUE
--alphaAlignment score minimum cutoffdouble, default: 0.1
+
+
+

Clustering options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_clusterPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions specified in ‘–leiden_resolution’.string, default: "scanorama_integration_leiden"
--leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_leiden_scanorama_umap"
+
+
+
+

Authors

+
    +

  • Mauro Saporita (author)

    • +

  • Povilas Gibas (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p11(scanorama)
+    p13(join)
+    p21(find_neighbors)
+    p23(join)
+    p31(leiden)
+    p33(join)
+    p41(umap)
+    p43(join)
+    p51(move_obsm_to_obs)
+    p53(join)
+    p60(Output)
+    p0-->p2
+    p2-->p4
+    p4-->p13
+    p4-->p11
+    p11-->p13
+    p13-->p23
+    p13-->p21
+    p21-->p23
+    p23-->p33
+    p23-->p31
+    p31-->p33
+    p33-->p43
+    p33-->p41
+    p41-->p43
+    p43-->p53
+    p43-->p51
+    p51-->p53
+    p53-->p60
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/integration/totalvi_leiden.html b/pr-preview/pr-51/components/workflows/multiomics/integration/totalvi_leiden.html new file mode 100644 index 00000000..a1377ee7 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/integration/totalvi_leiden.html @@ -0,0 +1,2048 @@ + + + + + + + + + + +OpenPipelines - Totalvi leiden + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Totalvi leiden

+
+ +
+
+ Run totalVI integration followed by neighbour calculations, leiden clustering and run umap on the result. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: totalvi_leiden
+Namespace: multiomics/integration

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/integration/totalvi_leiden/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+layer: "log_normalized"
+modality: "rna"
+prot_modality: "prot"
+reference: # please fill in - example: "path/to/file"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+# reference_model_path: "$id.$key.reference_model_path.reference_model_path"
+# query_model_path: "$id.$key.query_model_path.query_model_path"
+
+# General TotalVI Options
+obs_batch: "sample_id"
+max_epochs: 400
+max_query_epochs: 200
+weight_decay: 0.0
+force_retrain: false
+# var_input: "foo"
+
+# TotalVI integration options RNA
+rna_reference_modality: "rna"
+rna_obsm_output: "X_totalvi"
+
+# TotalVI integration options ADT
+prot_reference_modality: "prot"
+prot_obsm_output: "X_totalvi"
+
+# Neighbour calculation RNA
+rna_uns_neighbors: "totalvi_integration_neighbors"
+rna_obsp_neighbor_distances: "totalvi_integration_distances"
+rna_obsp_neighbor_connectivities: "totalvi_integration_connectivities"
+
+# Neighbour calculation ADT
+prot_uns_neighbors: "totalvi_integration_neighbors"
+prot_obsp_neighbor_distances: "totalvi_integration_distances"
+prot_obsp_neighbor_connectivities: "totalvi_integration_connectivities"
+
+# Clustering options RNA
+rna_obs_cluster: "totalvi_integration_leiden"
+rna_leiden_resolution: [1]
+
+# Clustering options ADT
+prot_obs_cluster: "totalvi_integration_leiden"
+prot_leiden_resolution: [1]
+
+# Umap options
+obsm_umap: "X_totalvi_umap"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/integration/totalvi_leiden/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
--layeruse specified layer for expression values instead of the .X object from the modality.string, default: "log_normalized"
--modalityWhich modality to process.string, default: "rna"
--prot_modalityWhich modality to process.string, default: "prot"
--referenceInput h5mu file with reference data to train the TOTALVI model.file, required
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
--reference_model_pathDirectory with the reference model. If not exists, trained model will be saved therefile, default: "totalvi_model_reference"
--query_model_pathDirectory, where the query model will be savedfile, default: "totalvi_model_query"
+
+
+

General TotalVI Options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obs_batch.Obs column name discriminating between your batches.string, default: "sample_id"
--max_epochsNumber of passes through the datasetinteger, default: 400
--max_query_epochsNumber of passes through the dataset, when fine-tuning model for queryinteger, default: 200
--weight_decayWeight decay, when fine-tuning model for querydouble, default: 0
--force_retrainIf true, retrain the model and save it to reference_model_pathboolean_true
--var_inputBoolean .var column to subset data with (e.g. containing highly variable genes). By default, do not subset genes.string
+
+
+

TotalVI integration options RNA

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--rna_reference_modalitystring, default: "rna"
--rna_obsm_outputIn which .obsm slot to store the normalized RNA from TOTALVI.string, default: "X_totalvi"
+
+
+

TotalVI integration options ADT

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--prot_reference_modalityName of the modality containing proteins in the referencestring, default: "prot"
--prot_obsm_outputIn which .obsm slot to store the normalized protein data from TOTALVI.string, default: "X_totalvi"
+
+
+

Neighbour calculation RNA

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--rna_uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "totalvi_integration_neighbors"
--rna_obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "totalvi_integration_distances"
--rna_obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "totalvi_integration_connectivities"
+
+
+

Neighbour calculation ADT

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--prot_uns_neighborsIn which .uns slot to store various neighbor output objects.string, default: "totalvi_integration_neighbors"
--prot_obsp_neighbor_distancesIn which .obsp slot to store the distance matrix between the resulting neighbors.string, default: "totalvi_integration_distances"
--prot_obsp_neighbor_connectivitiesIn which .obsp slot to store the connectivities matrix between the resulting neighbors.string, default: "totalvi_integration_connectivities"
+
+
+

Clustering options RNA

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--rna_obs_clusterPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.string, default: "totalvi_integration_leiden"
--rna_leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Clustering options ADT

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--prot_obs_clusterPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.string, default: "totalvi_integration_leiden"
--prot_leiden_resolutionControl the coarseness of the clustering. Higher values lead to more clusters.double, default: 1
+
+
+

Umap options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--obsm_umapIn which .obsm slot to store the resulting UMAP embedding.string, default: "X_totalvi_umap"
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p3(toSortedList)
+    p5(flatMap)
+    p12(totalvi)
+    p14(join)
+    p23(find_neighbors)
+    p25(join)
+    p33(leiden)
+    p35(join)
+    p43(umap)
+    p45(join)
+    p53(move_obsm_to_obs)
+    p55(join)
+    p64(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:find_neighbors:find_neighbors_process1)
+    p66(join)
+    p74(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:leiden:leiden_process1)
+    p76(join)
+    p84(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:umap:umap_process1)
+    p86(join)
+    p94(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:move_obsm_to_obs:move_obsm_to_obs_process1)
+    p96(join)
+    p104(publish)
+    p106(join)
+    p112(Output)
+    p0-->p3
+    p3-->p5
+    p5-->p14
+    p5-->p12
+    p12-->p14
+    p14-->p25
+    p14-->p23
+    p23-->p25
+    p25-->p35
+    p25-->p33
+    p33-->p35
+    p35-->p45
+    p35-->p43
+    p43-->p45
+    p45-->p55
+    p45-->p53
+    p53-->p55
+    p55-->p66
+    p55-->p64
+    p64-->p66
+    p66-->p76
+    p66-->p74
+    p74-->p76
+    p76-->p86
+    p76-->p84
+    p84-->p86
+    p86-->p96
+    p86-->p94
+    p94-->p96
+    p96-->p106
+    p96-->p104
+    p104-->p106
+    p106-->p112
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/multisample.html b/pr-preview/pr-51/components/workflows/multiomics/multisample.html new file mode 100644 index 00000000..9fc035a3 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/multisample.html @@ -0,0 +1,1905 @@ + + + + + + + + + + +OpenPipelines - Multisample + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Multisample

+
+ +
+
+ This workflow serves as an entrypoint into the ‘full_pipeline’ in order to re-run the multisample processing and the integration setup. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: multisample
+Namespace: multiomics

+
+ +

An input .h5mu file will first be split in order to run the multisample processing per modality. Next, the modalities are merged again and the integration setup pipeline is executed. Please note that this workflow assumes that samples from multiple pipelines are already concatenated.

+
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/multisample/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "foo"
+input: # please fill in - example: "input.h5mu"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# Highly variable gene detection
+filter_with_hvg_var_output: "filter_with_hvg"
+filter_with_hvg_obs_batch_key: "sample_id"
+
+# QC metrics calculation options
+var_qc_metrics: ["filter_with_hvg"]
+top_n_vars: [50, 100, 200, 500]
+
+# PCA options
+pca_overwrite: false
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/multisample/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "input.h5mu"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Highly variable gene detection

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--filter_with_hvg_var_outputIn which .var slot to store a boolean array corresponding to the highly variable genes.string, default: "filter_with_hvg"
--filter_with_hvg_obs_batch_keyIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method.string, default: "sample_id"
+
+
+

QC metrics calculation options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--var_qc_metricsKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes.string, default: "filter_with_hvg", example: "ercc,highly_variable"
--top_n_varsNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.integer, default: 50, default: 100, default: 200, default: 500
+
+
+

PCA options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--pca_overwriteAllow overwriting slots for PCA output.boolean_true
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author, maintainer)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p2(toSortedList)
+    p4(flatMap)
+    p7(filter)
+    p12(split_modalities)
+    p14(join)
+    p21(concat)
+    p17(filter)
+    p19(test_wf:run_wf:split_modalities_workflow:splitStub)
+    p22(flatMap)
+    p23(filter)
+    p26(toSortedList)
+    p28(flatMap)
+    p30(toSortedList)
+    p32(Output)
+    p38(normalize_total)
+    p40(join)
+    p48(log1p)
+    p50(join)
+    p58(delete_layer)
+    p60(join)
+    p68(filter_with_hvg)
+    p70(join)
+    p78(rna_calculate_qc_metrics)
+    p80(join)
+    p121(concat)
+    p86(filter)
+    p89(toSortedList)
+    p91(flatMap)
+    p93(toSortedList)
+    p95(Output)
+    p101(clr)
+    p103(join)
+    p111(prot_calculate_qc_metrics)
+    p113(join)
+    p119(filter)
+    p122(groupTuple)
+    p128(merge)
+    p130(join)
+    p133(filter)
+    p137(toSortedList)
+    p139(flatMap)
+    p146(pca)
+    p148(join)
+    p156(find_neighbors)
+    p158(join)
+    p166(umap)
+    p168(join)
+    p173(concat)
+    p172(filter)
+    p174(filter)
+    p178(toSortedList)
+    p180(flatMap)
+    p187(pca)
+    p189(join)
+    p197(find_neighbors)
+    p199(join)
+    p207(test_wf:run_wf:integration_setup_workflow:initialize_integration_prot:umap:umap_process1)
+    p209(join)
+    p214(concat)
+    p213(filter)
+    p220(publish)
+    p222(join)
+    p227(toSortedList)
+    p229(Output)
+    p21-->p22
+    p22-->p23
+    p22-->p86
+    p22-->p119
+    p121-->p122
+    p172-->p173
+    p173-->p174
+    p173-->p213
+    p213-->p214
+    p0-->p2
+    p2-->p4
+    p4-->p7
+    p4-->p17
+    p7-->p14
+    p7-->p12
+    p12-->p14
+    p14-->p21
+    p17-->p19
+    p19-->p21
+    p23-->p26
+    p26-->p28
+    p28-->p30
+    p30-->p32
+    p28-->p40
+    p28-->p38
+    p38-->p40
+    p40-->p50
+    p40-->p48
+    p48-->p50
+    p50-->p60
+    p50-->p58
+    p58-->p60
+    p60-->p70
+    p60-->p68
+    p68-->p70
+    p70-->p80
+    p70-->p78
+    p78-->p80
+    p80-->p121
+    p86-->p89
+    p89-->p91
+    p91-->p93
+    p93-->p95
+    p91-->p103
+    p91-->p101
+    p101-->p103
+    p103-->p113
+    p103-->p111
+    p111-->p113
+    p113-->p121
+    p119-->p121
+    p122-->p130
+    p122-->p128
+    p128-->p130
+    p130-->p133
+    p130-->p172
+    p133-->p137
+    p137-->p139
+    p139-->p148
+    p139-->p146
+    p146-->p148
+    p148-->p158
+    p148-->p156
+    p156-->p158
+    p158-->p168
+    p158-->p166
+    p166-->p168
+    p168-->p173
+    p174-->p178
+    p178-->p180
+    p180-->p189
+    p180-->p187
+    p187-->p189
+    p189-->p199
+    p189-->p197
+    p197-->p199
+    p199-->p209
+    p199-->p207
+    p207-->p209
+    p209-->p214
+    p214-->p222
+    p214-->p220
+    p220-->p222
+    p222-->p227
+    p227-->p229
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/prot_multisample.html b/pr-preview/pr-51/components/workflows/multiomics/prot_multisample.html new file mode 100644 index 00000000..392a589d --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/prot_multisample.html @@ -0,0 +1,1709 @@ + + + + + + + + + + +OpenPipelines - Prot multisample + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Prot multisample

+
+ +
+
+ Processing unimodal multi-sample ADT data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: prot_multisample
+Namespace: multiomics

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/prot_multisample/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "concatenated"
+input: # please fill in - example: "dataset.h5mu"
+
+# Outputs
+# output: "$id.$key.output.h5mu"
+
+# QC metrics calculation options
+top_n_vars: [50, 100, 200, 500]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/prot_multisample/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the concatenated filestring, required, example: "concatenated"
--inputPath to the samples.file, required, example: "dataset.h5mu"
+
+
+

Outputs

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

QC metrics calculation options

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--top_n_varsNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.integer, default: 50, default: 100, default: 200, default: 500
+
+
+
+

Authors

+
    +
  • Dries Schaumont (author)
    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p3(toSortedList)
+    p5(flatMap)
+    p7(toSortedList)
+    p9(Output)
+    p15(clr)
+    p17(join)
+    p25(prot_calculate_qc_metrics)
+    p27(join)
+    p34(Output)
+    p0-->p3
+    p3-->p5
+    p5-->p7
+    p7-->p9
+    p5-->p17
+    p5-->p15
+    p15-->p17
+    p17-->p27
+    p17-->p25
+    p25-->p27
+    p27-->p34
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/prot_singlesample.html b/pr-preview/pr-51/components/workflows/multiomics/prot_singlesample.html new file mode 100644 index 00000000..6a3a75a5 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/prot_singlesample.html @@ -0,0 +1,1745 @@ + + + + + + + + + + +OpenPipelines - Prot singlesample + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Prot singlesample

+
+ +
+
+ Processing unimodal single-sample CITE-seq data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: prot_singlesample
+Namespace: multiomics

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/prot_singlesample/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Input
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+
+# Output
+# output: "$id.$key.output.h5mu"
+
+# Filtering options
+# min_counts: 200
+# max_counts: 5000000
+# min_proteins_per_cell: 200
+# max_proteins_per_cell: 1500000
+# min_cells_per_protein: 3
+# min_fraction_mito: 0
+# max_fraction_mito: 0.2
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/prot_singlesample/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
+
+
+

Output

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Filtering options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--min_countsMinimum number of counts captured per cell.integer, example: 200
--max_countsMaximum number of counts captured per cell.integer, example: 5000000
--min_proteins_per_cellMinimum of non-zero values per cell.integer, example: 200
--max_proteins_per_cellMaximum of non-zero values per cell.integer, example: 1500000
--min_cells_per_proteinMinimum of non-zero values per gene.integer, example: 3
--min_fraction_mitoMinimum fraction of proteins that are mitochondrial.double, example: 0
--max_fraction_mitoMaximum fraction of proteins that are mitochondrial.double, example: 0.2
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Dries Schaumont (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p3(toSortedList)
+    p5(flatMap)
+    p12(filter_with_counts)
+    p14(join)
+    p22(do_filter)
+    p24(join)
+    p30(toSortedList)
+    p32(Output)
+    p0-->p3
+    p3-->p5
+    p5-->p14
+    p5-->p12
+    p12-->p14
+    p14-->p24
+    p14-->p22
+    p22-->p24
+    p24-->p30
+    p30-->p32
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/rna_multisample.html b/pr-preview/pr-51/components/workflows/multiomics/rna_multisample.html new file mode 100644 index 00000000..21580403 --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/rna_multisample.html @@ -0,0 +1,1777 @@ + + + + + + + + + + +OpenPipelines - Rna multisample + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Rna multisample

+
+ +
+
+ Processing unimodal multi-sample RNA transcriptomics data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: rna_multisample
+Namespace: multiomics

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/rna_multisample/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Inputs
+id: # please fill in - example: "concatenated"
+input: # please fill in - example: "dataset.h5mu"
+
+# Output
+# output: "$id.$key.output.h5mu"
+
+# Filtering highly variable genes
+filter_with_hvg_var_output: "filter_with_hvg"
+filter_with_hvg_obs_batch_key: "sample_id"
+filter_with_hvg_flavor: "seurat"
+# filter_with_hvg_n_top_genes: 123
+
+# QC metrics calculation options
+var_qc_metrics: ["filter_with_hvg"]
+top_n_vars: [50, 100, 200, 500]
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/rna_multisample/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Inputs

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the concatenated filestring, required, example: "concatenated"
--inputPath to the samples.file, required, example: "dataset.h5mu"
+
+
+

Output

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Filtering highly variable genes

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--filter_with_hvg_var_outputIn which .var slot to store a boolean array corresponding to the highly variable genes.string, default: "filter_with_hvg"
--filter_with_hvg_obs_batch_keyIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method. For all flavors, genes are first sorted by how many batches they are a HVG. For dispersion-based flavors ties are broken by normalized dispersion. If flavor = ‘seurat_v3’, ties are broken by the median (across batches) rank based on within-batch normalized variance.string, default: "sample_id"
--filter_with_hvg_flavorChoose the flavor for identifying highly variable genes. For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_genes.string, default: "seurat"
--filter_with_hvg_n_top_genesNumber of highly-variable genes to keep. Mandatory if filter_with_hvg_flavor is set to ‘seurat_v3’.integer
+
+
+

QC metrics calculation options

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--var_qc_metricsKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes.string, default: "filter_with_hvg", example: "ercc,highly_variable"
--top_n_varsNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.integer, default: 50, default: 100, default: 200, default: 500
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Dries Schaumont (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p3(toSortedList)
+    p5(flatMap)
+    p7(toSortedList)
+    p9(Output)
+    p15(normalize_total)
+    p17(join)
+    p25(log1p)
+    p27(join)
+    p35(delete_layer)
+    p37(join)
+    p45(filter_with_hvg)
+    p47(join)
+    p55(rna_calculate_qc_metrics)
+    p57(join)
+    p64(Output)
+    p0-->p3
+    p3-->p5
+    p5-->p7
+    p7-->p9
+    p5-->p17
+    p5-->p15
+    p15-->p17
+    p17-->p27
+    p17-->p25
+    p25-->p27
+    p27-->p37
+    p27-->p35
+    p35-->p37
+    p37-->p47
+    p37-->p45
+    p45-->p47
+    p47-->p57
+    p47-->p55
+    p55-->p57
+    p57-->p64
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/components/workflows/multiomics/rna_singlesample.html b/pr-preview/pr-51/components/workflows/multiomics/rna_singlesample.html new file mode 100644 index 00000000..e5676a7c --- /dev/null +++ b/pr-preview/pr-51/components/workflows/multiomics/rna_singlesample.html @@ -0,0 +1,1787 @@ + + + + + + + + + + +OpenPipelines - Rna singlesample + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Rna singlesample

+
+ +
+
+ Processing unimodal single-sample RNA transcriptomics data. +
+
+ + +
+ + + + +
+ + +
+ + +
+
+

Info

+

ID: rna_singlesample
+Namespace: multiomics

+
+ +
+

Example commands

+

You can run the pipeline using nextflow run.

+
+

View help

+

You can use --help as a parameter to get an overview of the possible parameters.

+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -main-script ./workflows/multiomics/rna_singlesample/main.nf \
+  --help
+
+
+

Run command

+
+ +Example of params.yaml + +
# Input
+id: # please fill in - example: "foo"
+input: # please fill in - example: "dataset.h5mu"
+
+# Output
+# output: "$id.$key.output.h5mu"
+
+# Filtering options
+# min_counts: 200
+# max_counts: 5000000
+# min_genes_per_cell: 200
+# max_genes_per_cell: 1500000
+# min_cells_per_gene: 3
+# min_fraction_mito: 0
+# max_fraction_mito: 0.2
+
+# Mitochondrial gene detection
+# var_name_mitochondrial_genes: "foo"
+# var_gene_names: "gene_symbol"
+mitochondrial_gene_regex: "^[mM][tT]-"
+
+# Nextflow input-output arguments
+publish_dir: # please fill in - example: "output/"
+# param_list: "my_params.yaml"
+
+
nextflow run openpipelines-bio/openpipeline \
+  -r 0.10.0 -latest \
+  -profile docker \
+  -main-script ./workflows/multiomics/rna_singlesample/main.nf \
+  -params-file params.yaml
+
+
+
+ +
+
+Note +
+
+
+

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

+
+
+
+
+
+

Argument groups

+
+

Input

+ +++++ + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--idID of the sample.string, required, example: "foo"
--inputPath to the sample.file, required, example: "dataset.h5mu"
+
+
+

Output

+ +++++ + + + + + + + + + + + + + + +
NameDescriptionAttributes
--outputDestination path to the output.file, required, example: "output.h5mu"
+
+
+

Filtering options

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--min_countsMinimum number of counts captured per cell.integer, example: 200
--max_countsMaximum number of counts captured per cell.integer, example: 5000000
--min_genes_per_cellMinimum of non-zero values per cell.integer, example: 200
--max_genes_per_cellMaximum of non-zero values per cell.integer, example: 1500000
--min_cells_per_geneMinimum of non-zero values per gene.integer, example: 3
--min_fraction_mitoMinimum fraction of UMIs that are mitochondrial.double, example: 0
--max_fraction_mitoMaximum fraction of UMIs that are mitochondrial.double, example: 0.2
+
+
+

Mitochondrial gene detection

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionAttributes
--var_name_mitochondrial_genesIn which .var slot to store a boolean array corresponding the mitochondrial genes.string
--var_gene_names.var column name to be used to detect mitochondrial genes instead of .var_names (default if not set). Gene names matching with the regex value from –mitochondrial_gene_regex will be identified as a mitochondrial gene.string, example: "gene_symbol"
--mitochondrial_gene_regexRegex string that identifies mitochondrial genes from –var_gene_names. By default will detect human and mouse mitochondrial genes from a gene symbol.string, default: "^[mM][tT]-"
+
+
+
+

Authors

+
    +

  • Dries De Maeyer (author)

    • +

  • Robrecht Cannoodt (author, maintainer)

    • +

  • Dries Schaumont (author)

    • +
+
+
+

Visualisation

+
+
+
+
+
flowchart LR
+    p0(Input)
+    p3(toSortedList)
+    p5(flatMap)
+    p12(filter_with_counts)
+    p14(join)
+    p22(do_filter)
+    p24(join)
+    p32(filter_with_scrublet)
+    p34(join)
+    p42(Output)
+    p0-->p3
+    p3-->p5
+    p5-->p14
+    p5-->p12
+    p12-->p14
+    p14-->p24
+    p14-->p22
+    p22-->p24
+    p24-->p34
+    p24-->p32
+    p32-->p34
+    p34-->p42
+
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/contributing/creating_components.html b/pr-preview/pr-51/contributing/creating_components.html new file mode 100644 index 00000000..6140755a --- /dev/null +++ b/pr-preview/pr-51/contributing/creating_components.html @@ -0,0 +1,729 @@ + + + + + + + + + +OpenPipelines - Creating components + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Creating components

+
+ + + +
+ + + + +
+ + +
+ +
+

A common file format

+

One of the core principals of OpenPipelines is to use MuData as a common data format troughout the whole pipeline. See the concepts page for more information on openpipelines uses MuData to store single-cell data.

+
+
+

Component location

+

As discussed in the project structure, components in the repository are stored within src. Additionally, components are grouped into namespaces, according to a common functionality. An example of such a namespace is the dimensionality reduction namespace (dimred), of which the components pca and umap are members. This means that within src, the namespace folders can be found that stores the components that belong to these namespaces.

+

In order to create a new component in OpenPipelines, you will need to create a new folder that will contain the different elements of the component:

+
mkdir src/my_namespace/my_component
+
+
+
+ +
+
+Tip +
+
+
+

Take a look at the components that are already in src/! There might be a component that already does something similar to what you need.

+
+
+
+
+

The elements of a component

+

A component consists of one or more scripts that provide the functionality of the component together with metadata of the component in a configuration file. The Viash config contains metadata of your dataset, which script is used to run it, and the required dependencies. An in-depth guide on how to create components is available on the viash website, but a few specifics and guidelines will be discussed here.

+
+

The config

+
functionality:
+  name: "my_component"
+  namespace: "my_namespace"
+  description: "My new custom component"
+  authors:
+    - __merge__: ../../authors/my_name.yaml
+      roles: [ author ]
+  arguments:
+    - name: "--output"
+      type: file
+      example: "output_file.h5mu"
+      description: "Location were the output file should be written to."
+      direction: "output"
+  resources:
+    - type: python_script
+      path: script.py
+platforms:
+  - type: docker
+    image: python:3.11
+    setup:
+      - type: python
+        packages: mudata~=0.2.3
+  - type: nextflow
+    directives:
+      label: [highcpu, midmem]
+
+

Basic information

+

Each component should have the name, a namespace, a description and author information defined in the config. Because a single author can contribute to multiple components, the author information is often duplicated across components, which was causing issues with the author information being out of date and not easy to maintain. Therefore, it was decided to move author information to ./src/authors. Each author has a yaml file containing the author information, and the viash __merge__ property is used to merge this information into the viash configs.

+

Basic information checklist:

+
    +
  • Give the component a name
    • +
  • Add the component to an appropriate namespace
    • +
  • Add a description
    • +
  • Add author information
    • +
+
+
+

Arguments and argument groups

+

If you component requires arguments, they should be defined in arguments or argument_groups. Try tro group individual arguments into argument_groups when the number of arguments become too larg (10 or more as a rule of thumb).

+

Argument checklist:

+
    +
  • Add a description and name
    • +
  • Each argument should have the appropriate type.
    • +
  • Input and output files should be of type file instead of string and use the appropriate direction:
    • +
  • If possible: add an example
    • +
  • If the argument can accept multiple values, add multiple: true
    • +
  • If the possible input for an argument is limited to certain set of values, use choices:
    • +
+
+
+

(Test)resources

+

Resources define files that are required for a component to perform its function. These can be scripts, but also additional files like settings for tools you might require. Defining resources is both a necessity because viash needs to know what code to execute, but defining resources also has the added benefit that these resources are automatically made available, regardless of the build environment. For example: resources are automatically mounted within a running docker container.

+

There is a difference between defining resources and test_resources. While resources are required for a component to function, test_resources only need to be included when testing the component (with for example viash test) in addition to the regular resources. Having a look at the example above, resources are defined using the resources: property. It takes a list of multiple files or folders.

+

In openpipelines, it was decided to not use a service like git lfs to include large resources into the repository. Instead, if large resources are required, there are two possibilities: * Large resources required for testing are to uploaded into an s3 bucket that is synced automatically before running tests (both locally and on github). Please ping a maintainer when you open a PR and ask them to upload the files for you. * Other large resources that are not needed for testing can be considered as input. This means that an argument of type: file needs to be created. The downside of this method is that viash is not able to natively support remote files f

+

Resources checklist: - Script resources are located next to the config and added to the config with the correct type (python_script, r_script, …) - Small resources (<50MB) that are not scripts can also be checked in into the repo, next to the

+
+
+

Build information

+

TODO

+
+
+
+

The script file

+

TODO

+
+
+

Author information

+

TODO

+
+
+
+

Adding dependencies

+

TODO

+
+
+

Building components from their source

+

When running or testing individual components, it is not necessary to execute an extra command to run the build step, viash test and viash run will build the component on the fly. However, before integrating components into a pipeline, you will need to build the components. More specifically, openpipelines uses Nextflow to combine components into pipelines, so we need to have at least the components build for nextflow platform as target. The easiest method to build the components is to use:

+
viash ns build --parallel --setup cachedbuild
+

After using .viash ns build, the target folder will be populated with three subfolders, corresponding to the build platforms that viash supports: native, docker and nextflow. In contrast to ./bin/viash build, viash_build will use all of the platforms defined in each of the components configuration instead of the first one. Keep in mind that running ./bin/viash_build will not always cause a component to be re-build completely. Caching mechanisms in the docker platform for example will make sure only components for which alterations have been made will be build, significantly reducing build times. In summary, using ./bin/viash_build makes sure that the latest build of components are available before starting to integrate them in pipelines.

+

Building an individual component can still be useful, for example when debugging a component for which the build fails or if you want to create a standalone executable for a component to execute it without the need to use viash. To build an individual component, ./bin/viash build can be used. Note that the default build directory of this viash base command is output, which is not the location where build components will be imported from when integrating them in pipelines. Using the --output argument, you can set it to any directory you want, for example:

+
./bin/viash build ./src/filter/do_filter/config.vsh.yaml -o ./target/native/filter/do_filter/ -p native
+
+
+

Containerization

+

One of the key benefits of using Viash is that containers can be created that gather dependencies per component, which avoids building one container that has to encorporate all dependencies for a pipeline together. The containers for a single component can be reduced in size, defining the minimal requirements to run the component. That being said, building containers from scratch can be labour intensive and error prone, with base containers from reputable publishers often benefiting from improved reliability and security. Hence, a balance has to be made between reducing the container’s size and adding many dependencies to a small base container.

+

The preferred containerization setup in OpenPipelines uses the following guidelines:

+
    +
  • Choose a base container from a reputable source and use its latest version
    • +
  • Do not use base containers that have not been updated in a while
    • +
  • Use package managers to install dependencies as much as possible
    • +
  • Avoid building depdencies from source.
    • +
+

Examples of base containers that are currently being used are:

+ + + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/contributing/creating_pipelines.html b/pr-preview/pr-51/contributing/creating_pipelines.html new file mode 100644 index 00000000..6eae405e --- /dev/null +++ b/pr-preview/pr-51/contributing/creating_pipelines.html @@ -0,0 +1,545 @@ + + + + + + + + + +OpenPipelines - Creating pipelines + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Creating pipelines

+
+ + + +
+ + + + +
+ + +
+ + + + +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/contributing/getting_started.html b/pr-preview/pr-51/contributing/getting_started.html new file mode 100644 index 00000000..f947c4ab --- /dev/null +++ b/pr-preview/pr-51/contributing/getting_started.html @@ -0,0 +1,612 @@ + + + + + + + + + +OpenPipelines - Getting started + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Getting started

+
+ + + +
+ + + + +
+ + +
+ +
+

Forking the code and cloning the repository

+

The openpipelines code is hosted on GitHub. To start working on openpipeline, you should create your own copy of the repository by forking it. Visit the openpipeline repository here and use the ‘Fork’ button on the top right hand side of the page. After you are done forking, you can clone the repository to a local directory on your computer using git clone. You can choose between using an SSH key to log in to GitHub or username and password (HTTPS) to connect to github.

+
+ +
+
+
git clone https://github.com/<YOUR USERNAME>/openpipeline.git
+cd openpipeline
+git remote add upstream https://github.com/openpipeline-bio/openpipeline.git
+
+
+
git clone git@github.com:<YOUR USERNAME>/openpipeline.git
+cd openpipeline
+git remote add upstream https://github.com/openpipeline-bio/openpipeline.git
+
+
+
+
+
+

Installing viash and nextflow

+

Openpipelines is being developed in Viash and Nextflow. If you are unfamiliar with either one of these platforms, you can check out their respective documentations here and here. To start contributing to openpipelines, you will need at least a working version of Java 11, OpenJDK 11, or a later version (up to Java 18). Additionally, by using Docker,you can build and test pipeline components and pipelines without needing to manually install dependencies for these components on your machine.

+

Viash and Nextflow can be installed by following the guides in the documentation for both of these tools. Make sure the viash and nextflow binaries are located in an existing directory that is listed in your $PATH. You can check if everything worked by running the following two commands and see if they output the correct location of the executables.

+
which viash
+which nextflow
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/contributing/index.html b/pr-preview/pr-51/contributing/index.html new file mode 100644 index 00000000..994fe105 --- /dev/null +++ b/pr-preview/pr-51/contributing/index.html @@ -0,0 +1,545 @@ + + + + + + + + + +OpenPipelines - Contributing + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Contributing

+
+ + + +
+ + + + +
+ + +
+ + + + +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/contributing/project_structure.html b/pr-preview/pr-51/contributing/project_structure.html new file mode 100644 index 00000000..0a7cafc4 --- /dev/null +++ b/pr-preview/pr-51/contributing/project_structure.html @@ -0,0 +1,623 @@ + + + + + + + + + +OpenPipelines - Project structure + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Project structure

+
+ + + +
+ + + + +
+ + +
+ +
+

Project structure

+

The root of the repository contains three main folders:

+
    +
  1. src, which contains the source code for individual components.
    2. +
  2. The workflows folder containing the implementations of the pipelines (combining one or more components).
    3. +
  3. (optionally) the target folder
    4. +
+

Each subfolder from src contains a Viash namespace, a logical grouping of pipeline components that perform a similar function. Within each namespace, subfolders designate individual pipeline components. For example ./src/convert/from_bdrhap_to_h5ad contains the implementation for a component from_bdrhap_to_h5ad which is grouped together with other components such as from_10xmtx_to_h5mu into a namespace convert. In a similar manner as grouping components into namespaces, pipelines are grouped together into folders. However, these are not component namespaces and as such do not interact with viash ns commands.

+

As will become apparent later on, Viash not only provides commands to perform operations on individual components, but also on groups of components in a namespace and all components in a project. As a rule of thumb, the basic Viash commands (like ./bin/viash test) are designated for running commands on individual components, while ns commands are (./bin/viash ns test) are for namespaces. When cloning a fresh repository, there will be no target folder present. This is because the target folder will only be created after components have been build.

+
+
+

Versioning and branching strategy

+

OpenPipeline tries to use of semantic versioning to govern changes between versions. An release of openpipelines uses a version number in the format MAJOR.MINOR.PATCH. Currenly, openpipelines is still at major version 0.x.y, meaning that public-facing breaking changes are possible on MINOR releases. These breaking changes will be documented in a dedicated section of the CHANGELOG that is published with each release. A PATCH release (i.e. a release where the MAJOR and MINOR version number stay the same), is used to resolve bugs with the pipeline but should not introduce breaking changes. Keep in mind that patches might introduce behavioral changes that may look breaking but are actually rectifying changes that were inadvertently introduced previously (and were in fact also ‘breaking changes’). In this case, a bug can also be released without changing the MINOR version, in a PATH release.

+

Between releases, development progress is tracked on Git branches. A git branch represents a snapshot of a codebase in time, to which changes can be added (i.e. committed). Eventually, all new feature or bugfixes must be reconsiled into a single branch so that a new release can be created. This process is called merging and the process of requesting the merging of two branches is called a pull request. Openpipelines follows the convention that the target branch for all pull requests is the main branch. Thus, the main branch contains the latest changes for the code and it can be considered the development branch.

+

Once a pull request has been approved and merged, Github Actions CI will automatically build all components (creating the target directory) and push the result to the main_build branch. In essence, the main_build branch is a copy of the main branch, but also containing the build components. Once it is time to create a openpipelines release, the Github CI release workflow is manually triggered, the components on the main branch will be build and tested. Then, the result will be pushed to the release branch and the integration tests will be run. If all tests succeeded, a new github tag and release can be created manually from the release branch.

+
+
+
+
+
%%{init: { 'logLevel': 'debug', 'theme': 'default'} } }%%
+gitGraph
+  commit id: "initial commit"
+  branch main_build
+  commit id: "CI build"
+  checkout main
+  commit
+  checkout main_build
+  merge main
+  checkout main
+  branch feature_a
+  branch feature_b
+  checkout feature_a
+  commit
+  commit
+  checkout main
+  commit id: "#release 0.1" type: HIGHLIGHT
+  checkout main_build
+  merge main
+  checkout main
+  branch release
+  commit tag: "0.1"
+  checkout main
+  commit
+  checkout feature_b
+  commit
+  commit
+  checkout feature_a
+  commit
+  checkout main
+  merge feature_a
+  checkout main_build
+  merge main
+  checkout main
+  checkout feature_b
+  commit
+  checkout main
+  merge feature_b
+  checkout main_build
+  merge main
+  checkout release
+  merge main tag: "0.2"
+
+
+
+
+
+ + +
+ +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/contributing/pull_requests.html b/pr-preview/pr-51/contributing/pull_requests.html new file mode 100644 index 00000000..d9a620e4 --- /dev/null +++ b/pr-preview/pr-51/contributing/pull_requests.html @@ -0,0 +1,597 @@ + + + + + + + + + +OpenPipelines - Publishing your changes + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + +
+ +
+ + +
+ + + +
+ +
+
+

Publishing your changes

+
+ + + +
+ + + + +
+ + +
+ +
+

Updating your pull request or branch

+

While creating changes on your local branch, another developper could have added new changes the openpipeline repository. These changes will need to be included into your local branch before a pull request can be merged. Updating your branch involves merging the upstream branch (usually main) into your branch:

+
# download the changes from the openpipelines repo
+git fetch upstream
+# change your current branch to the branch of the pull request
+git checkout <feature_branch>
+# merge the changes from upstream into your branch
+git merge upstream/main
+# push the updates, your pull request will also be updated
+git push
+ + +
+ +
+ +
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Running tests

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Fetching the test data.

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The input data that is needed to run the tests will need to be downloaded from the openpipelines Amazon AWS s3 bucket first. To do so, the download/sync_test_resource component can be used, which will download the data to the correct location (resources_test) by default.

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./bin/viash run ./src/download/sync_test_resources/config.vsh.yaml -p docker -- --input s3://openpipelines-data
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Or, if you do not want to use Docker and have aws-cli tools installed natively:

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./bin/viash run ./src/download/sync_test_resources/config.vsh.yaml -p native -- --input s3://openpipelines-data
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+
+

Running component unittests

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To build and run tests for individual component that you are working on, use viash test with the config.vsh.yaml of the component you would like to test. For example:

+
./bin/viash test ./src/convert/from_10xh5_to_h5mu/config.vsh.yaml
+

Keep in mind that when no platform is passed to viash test, it will use the first platform that is specified in the config, which is docker for most of the components in openpipelines. Use -p native for example if you do not want to use docker.

+

It is also possible to execute the tests for all components in each namespace using ./bin/viash_test (note the underscore instead of a space).

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./bin/viash_test
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+
+

Integration tests

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Individual integration tests can be run by using the integration_test.sh scripts for a pipeline, located next to the main.nf in the workflows folder.

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./workflows/ingestion/cellranger_demux/integration_test.sh
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Running all integration tests is also possible using a helper script that can be found at workflows/test/integration_test.sh. Using this script requires a working R installation with tidyverse installed. However, as pipelines are implemented by combining individual components

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./workflows/test/integration_test.sh
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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/fundamentals/architecture.html b/pr-preview/pr-51/fundamentals/architecture.html new file mode 100644 index 00000000..ca469ff5 --- /dev/null +++ b/pr-preview/pr-51/fundamentals/architecture.html @@ -0,0 +1,975 @@ + + + + + + + + + +OpenPipelines - Architecture + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Architecture

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OpenPipeline is a pipeline for the processing of multimodal single-cell data that scales to a great many of samples. Covering the architecture requires us to explain many angles, including: what the expected inputs and outputs are for each workflow are, how do the workflows relate to each other, and what the state of the data is at each step of the pipeline. Here is an overview of the general steps involved in processing sequencing data into a single integrated object. We will discuss each of the steps further below.

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flowchart TD  
+  ingest["Ingestion"] --> split --> unimodalsinglesample["Unimodal Single Sample Processing"] --> concat --> unimodalmultisample["Unimodal Multi Sample Processing"] --> merging --> integation_setup["Integration Setup"] --> integration["Integration"]  --> downstreamprocessing["Downstream Processing"]
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+
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Figure 1: Overview of the steps included in OpenPipeline for the analysis of single cell multiomics data.
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  1. Ingestion: Convert raw sequencing data or count tables into MuData data for further processing.
    2. +
  2. Splitting modalities: Creating several MuData objects, one per modality, out of a multimodal input sample.
    3. +
  3. Unimodal Single Sample Processing: tools applied to each modality of samples individually. Mostly involves the selection of true from false cells.
    4. +
  4. Unimodal Multi Sample Processing: steps that require information from all samples together. Processing is still performed per-modality.
    5. +
  5. Merging: Creating one MuData object from several unimodal MuData input files.
    6. +
  6. Initializing Integration: Performs dimensionality reduction and cell type clustering on non-integrated samples. These are popular steps that would otherwise be executed manually or they provide input for downstream integration methods.
    7. +
  7. Integration: The alignment of cell types across samples. Can be performed per modality or based on multiple modalities.
    8. +
  8. Downstream Processing: Extra analyses performed on the integrated dataset and conversion to other file formats.
    9. +
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Available workflows

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The structure of the sections that have been laid out below follow a logical grouping of the processing according to the state of the data. However, even though this grouping makes sense from a data perspective, it does not mean that a workflow exist for each section. For example, the processing a single sample section describes how processing of single sample is performed as part of the full pipeline, but there is no singlesample workflow that a user can execute. The inverse is also possible: while there exists an multisample pipeline, it’s functionality is not limited to what has been described in the section Multisample Processing. This section lists all the available workflows and will try to describe the link with the relevant sections below.

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Ingestion workflows

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All of the following workflows from the ingestion namespace have been discussed in more detail in the ingestion section:

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Multiomics workflows

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There exists no singlesample workflow. However, the prot_singlesample and rna_singlesample pipelines do exist and they map identically to the functionality described in the single-sample antibody capture processing and single-sample gene expression processing sections respectively. If you would like to process your samples as described in the unimodal single sample processing section, you can execute both workflows in tandem for the two modalities.

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Contrary to the workflows for single sample processing, there exists a multiomics/multisample workflow. However this workflow is not just the multiomics/prot_multisample and multiomics/rna_multisample workflows that have been combined. Instead, it combines the multiomics/prot_multisample, multiomics/rna_multisample and multiomics/integration/initialize_integration workflows. The purpose of this pipeline is to provide an extra ‘entrypoint’ into the full pipeline that skips the singlesample processing, allowing reprocessing samples that have already been processed before. A popular usecase is to manually select one or more celltypes which need to be processed again or the integration of observations from multiple experiments into a single dataset. Keep in mind that concatenation is not included in the multisample pipeline, so when multiple input files are specified they are processed in parallel. If you would like to integrate multiple experiments, you need to first concatenate them in a seperate step:

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The “full” pipeline

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The name of this pipeline is a bit of a misnomer, because it does not include all the steps from ingestion to integration. As will be discussed in the ingestion section, which ingestion strategy you need is dependant on your technology provider and the chosen platform. For integration, there exist many methods and combination of methods, and you may wish to choose which integration methods are applicable for your usecase. As a consequence, these two stages in the analysis of single-cell need to be executed seperatly and not as part of a single unified pipeline. All other steps outlined below on the other hand are included into the “full” pipeline, which can therefore be summarized in the following figure:

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flowchart TD  
+  split --> unimodalsinglesample["Unimodal Single Sample Processing"] --> concat --> unimodalmultisample["Unimodal Multi Sample Processing"] --> merging --> integation_setup
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+
+
Figure 2: Overview of the steps included in the full pipelines from OpenPipeline.
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Integration workflows

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For each of the integration methods (and their optional combination with other tools), a seperate pipeline is defined. More information for each of the pipelines is available in the integration methods section.

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Important dataflow components

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While most components included in openpipelines are involved in data analysis, the sole purpose of other components is to facilitate data flow throughout the pipelines. In a workflow, output for a component is written to disk after it is done performing its task, and is read back in by the next component. However, the relation between the component and the next component is not always a clear one to one relationship. For example: some tools are capable of analyzing a single sample, while others require the input of all samples together. Additionally, not only are the input requirement of tools limiting, performance also needs to be taken into account. Tasks which are performed on each sample separately can be executed in parallel, while if the same task is performed on a single file that contains the data for all samples. In order to facilitate one-to-many or many-to-one relations between components and to allow parallel execution of tasks, component that are specialized in dataflow were implemented.

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Splitting modalities

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We refer to splitting modalities when multimodal MuData file is split into several unimodal MuData files. The number of output files is equal to the number of modalities present in the input file. Splitting the modalities works on MuData files containing data for multiple samples or for single-sample files.

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Merging of modalities

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Merging refers to combining multiple files with data for one modality into a single output file that contains all input modalities. It is the inverse operation of splitting the modalities.

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Concatenation of samples

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Joining of observations for different samples, stored in their respective MuData file, into a single MuData file for all samples together is called sample concatenation. In practice, this operation is performed for each modality separately. An extra column (with default name sample_id) is added to the annotation of the observations (.obs) to indicate where each observation originated from.

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Special care must be taken when considering annotations for observations and features while concatenating the samples. Indeed, the data from different samples can contain conflicting information. Openpipeline’s concat component provides an argument other_axis_mode that allows a user to specify what happens when conflicting information is found. The move option for this argument is the default behavior. In this mode, each annotation column (from .obs and .var) is compared across samples. When no conflicts are found or the column is unique for a sample, the column is added output object. When a conflict does occur, all of the columns are gathered from the samples and stored into a dataframe. This dataframe is then stored into .obsm for annotations for the observations and .varm for feature annotations. This way, a user can have a look at the conflicts and decide what to do with them.

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Ingestion

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Ingestion is the conversion of raw sequencing data or count tables into MuData objects that can be used for further processing.

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flowchart LR
+    RawCounts1["Raw counts"]
+    BCL[/"BCL"/]
+    Demux[/"Demultiplexing"/]
+    Fastq["Fastq"]
+    Ref["Reference"]
+    Mapping[/"Mapping"/]
+    RawDir["Raw out"]
+    Convert[/"Convert"/]
+    RawCounts1["Raw counts"]
+    BCL --> Demux --> Fastq
+    Fastq & Ref --> Mapping --> RawDir --> Convert --> RawCounts1
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+
+
+
+
+

Demultiplexing refers to a two-step process:

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    +
  1. The conversion of the binary base call (BCL) files, output by the sequencing machines, into the text-based FASTQ format.
    2. +
  2. The sorting of reads into different FASTQ files for different libraries pooled together into a single sequencing run.
    3. +
+

In order to perform demultiplexing, several tools have been made available in the demux workflow, where the --demultiplexer can be used to choose your demultiplexer of choice. Currently, three options have been made available:

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    +
  • bcl2fastq(2): a legacy tool from Illumina that has been replaced by BCL Convert
    • +
  • BCL Convert: general demultiplexing software by Illumina.
    • +
  • Cellranger’s mkfastq: a wrapper around BCL Convert that provides extra convenience features for the processing of 10X single-cell data.
    • +
+

The alignment of reads from the FASTQ files to an appropriate genome reference is called mapping. The result of the mapping process are tables that count the number of times a read has been mapped to a certain feature and metadata information for the cells (observations) and features. There are different format that can be used to store this information together. Since OpenPipeline uses MuData as a common file format throughout its pipelines, a conversion to MuData is included in the mapping pipelines. The choice between workflows for mapping is dependant on your single-cell library provider and technology:

+ +
+

Creating a transcriptomics reference

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Mapping reads from the FASTQ files to features requires a reference that needs to be provided to the mapping component. Depending on the usecase, you might even need to provide references specific for the modalities that you are trying to analyze. For gene expression data, the reference is a reference genome, together with its appropriate gene annotation. A genome reference is often indexed in order to improve the mapping speed. Additionally, some mapping frameworks provided by the single-cell technology providers require extra preprocessing of the reference before they can be used with their worklow. OpenPipelines provides a make_reference that allows you to create references in many formats which can be used to map your reads to.

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Processing a single sample

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Some processing can (or must) be performed without concatenating samples together. Even when having the choice, adding a tool to the single-sample processing is preferred because multiple samples can be processed in parallel, improving the processing speed. In general, the processing is modality specific, meaning that a multi-modal sample is first split into its unimodal counterparts. As described in the multi-sample processing, the resulting files are not merged back together after the single-sample processing is done. Instead, the output files for all samples are gathered per modality and concatenated to create a multi-sample unimodal object.

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Single-sample Gene Expression Processing

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Single-sample gene expression processing involves two steps: removing cells based on count statistics and flagging observations originating from doublets.

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The removal of cells based on basic count statistics is split up into two parts: first, cells are flagged for removal by filter_with_counts. It flags observations based on several thresholds:

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  • The number of genes that have a least a single count. Both a maximum and minimum number of genes for a cell to be removed can be specified.
    • +
  • The percentage of read counts that originated from a mitochodrial genes. Cells can be filtered based on both a maximum or minimum fraction of mitochondrial genes.
    • +
  • The minimum or maximum total number of counts captured per cell. Cells with 0 total counts are always removed.
    • +
+

Flagging cells for removal involved adding a boolean column to the .obs dataframe. After the cells have been flagged for removal, the cells are actually filtered using do_filter, which reads the values in .obs and removed the cells labeled True. This applies the general phylosophy of “separation of concerns”: one component is responsible for labeling the cells, another for removing them. This keeps the codebase for a single component small and its functionality testable.

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The next and final step in the single-sample gene expression processing is doublet detection using filter_with_scrublet. Like filter_with_counts, it will not remove cells but add a column to .obs (which have the name filter_with_scrublet by default). The single-sample GEX workflow will not remove not be removed during the processing (hence no do_filter). However, you can choose to remove them yourself before doing your analyses by applying a filter with the column in .obs yourself.

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Single-sample Antibody Capture Processing

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The process of filtering antibody capture data is similar to the filtering in the single-sample gene-expression processing, but without doublet detection. In some particular cases you can use your ADT data to perform doublet detection using for example cell-type maskers. More information can be found in the single-cell best practices book.

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Multisample Processing

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After the processing of individual samples has been concluded, samples can be concatenated for further processing. Like with the single-sample processing the multisample processing is not performed on multimodal objects, but each modality separately in order to tailor for the specific modality in question. This means that the result from the singlesample processing is merged together per-modality to create unimodal multisample objects. After processing each modality, all of the modalities can finally be merged and a single object is created that is ready for the integration.

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Multisample Gene Expression Processing

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Processing multisample gene expression involved the following steps:

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  1. Normalization: Normalization aims to adjust the raw counts in the dataset for variable sampling effects by scaling the observable variance to a specified range. There are different ways to transform the data, but the normalization method is to make sure each observation (cell) has a total count equal to the median of total counts over all genes for observations (cells) before normalization.
    2. +
  2. Log transformation: Calculates \(X = ln(X + 1)\), which converts multiplicative relative changes to additive differences. This allows for interpreting the gene expression in terms of relative, rather than absolute, abundances of genes.
    3. +
  3. Highly variable gene detection: Detects genes that have a large change in expression between samples. By default, OpenPipeline uses the method from Seurat (Satija et al.). As with other “filtering” components, the filter_with_hvg component does not remove features, but rather annotates genes of interest by adding a boolean column to .var.
    4. +
  4. QC metric calculations
    5. +
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Multisample Antibody Capture Processing

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Processing the ADT modality for multiple samples

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Integration

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Dimensionality Reduction

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scRNA-seq is a high-throughput sequencing technology that produces datasets with high dimensions in the number of cells and genes. It is true that the data should provide more information, but it also contains more noise and redudant information, making it harder to distill the usefull information. The number of genes and cells can already reduced by gene filtering, but further reduction is a necessity for downstream analysis. Dimensionality reduction projects high-dimensional data into a lower dimensional space (like taking a photo (2D) of some 3D structure). The lower dimensional representation still captures the underlying information of the data, while having fewer dimensions.

+

Several dimensionality reduction methods have been developed and applied to single-cell data analysis. Two of which are being applied in OpenPipeline:

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  1. Principal Component Analysis (PCA): PCA reduces the dimension of a dataset by creating a new set of variables (principal components, PCs) from a linear combination of the original features in such a way that they are as uncorrelated as possible. The PCs can be ranked in the order by which they explain the largest variability in the original dataset. By keeping the top n PCs, the PCs with the lowest variance are discarded to effectively reduce the dimensionality of the data without losing information.
    2. +
  2. Uniform manifold approximation and projection (UMAP): a non-linear dimensionality technique. It constructs a high dimensional graph representation of the dataset and optimizes the low-dimensional graph representation to be structurally as similar as possible to the original graph. In a review by Xiang et al., 2021 it showed the highest stability and separates best the original cell populations.
    3. +
  3. t-SNE is another popular non-linear, graph based dimensionality technique which is very similar to UMAP, but it has not yet been implemented in OpenPipeline.
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Initializing integration

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As will be descibed in more details later on, many integration methods exist and therefore there is no single integration which is executed by default. However, there are common tasks which are run before integration either because they provide required input for many downstream integration methods or because they popular steps that would otherwise be done manually. These operations are executed by default when using the “full pipeline” as part of the initialize_integration subworkflow.

+

PCA is used to reduce the dimensionality of the dataset as described previously. Find Neighbors and Leiden Clustering are useful for the identification of cell types or states in the data. Here we apply a popular method to accomplish this is to first calculate a neighborhood graph on a low dimensinonal representation of the data and then cluster the data based on similarity between data points. Finally, UMAP allows us to visualise the clusters by reducing the dimensionality of the data while still providing an accurate representation of the underlying cell population structure.

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Integration Methods

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Integration is the alignment of cell types across samples. There exist three different types of integration methods, based on the degree of integration across modalities:

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  1. Unimodal integration across batches. For example: scVI, scanorama, harmony
    2. +
  2. Multimodal integration across batches and modalities. Can be used to integrate joint-profiling data where multiple modalities are measured. For example: totalVI
    3. +
  3. Mosaic integration: data integration across batches and modalities where not all cells are profiled in all modalities and it may be the case that no cells contain profiles in all integrated modalities. Mosaic integration methods have not been made available in OpenPipeline yet. An example of a tool that performs mosaic integration is StabMap.
    4. +
+

In either of the three cases, concatenated samples are required, and merged modalities preferred. A plethora of integration methods exist, which in turn interact with other functionality (like clustering and dimensionality reduction methods) to generate a large number of possible usecases which one pipeline cannot cover in an easy manner. Therefore, there is no single integration step that is part of a global pipeline which is executed by default. Instead, a user can choose from the integration workflows provided, and ‘stack’ integration methods by adding the outputs to different output slots of the MuData object. The following sections will descibe the integration workflows that are available in OpenPipeline.

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+

Unimodal integration

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For unimodal integration, scVI, scanorama and harmony have been added to the scvi_leiden, scanorama_leiden, and harmony_leiden workflows respectively. After executing the integration methods themselves, Find Neighbors and Leiden Clustering are run the results of the integration as wel as UMAP in order to be able to visualise the results. The functioning of these components has already been described here.

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Multimodal Integration

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A single multimodal integration method is currently avaiable in OpenPipeline: totalVI. It allows using information from both the gene-expression data and the antibody-capture data together to integrate the cell types. As with the other integration workflows, after running totalVI, Find Neighbors, Leiden Clustering and UMAP are run on the result. However in this case the three components are executed on both of the integrated modalities.

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Putting it all together: the “Full Pipeline”

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+flowchart TB
+  Raw1[/Sample 1/]:::file --> Split
+  Raw2[/Sample 2/]:::file --> Split2
+  subgraph FullPipeline [Full Pipeline]
+    NoIntegration -.-> MultimodalFile[/Multisample\nMultimodal File/]:::file -.-> MultiSample
+    Split([Split\nmodalities]):::component --gex modality--> ProcGEX1
+    Split([Split\nmodalities]):::component --prot modality--> ProcADT1
+    Split([Split\nmodalities]):::component -- other--> ConcatVDJ
+
+    Split2([Split\nmodalities]):::component --gex modality--> ProcGEX1 
+    Split2([Split\nmodalities]):::component --prot modality--> ProcADT1
+    Split2([Split\nmodalities]):::component -- other--> ConcatVDJ
+    
+
+    subgraph MultiSample [Multisample]
+      subgraph MultisampleRNA [Multisample RNA]
+      end
+      MultisampleRNA:::workflow
+      subgraph MultisampleADT [Multisample ADT]
+      end
+      MultisampleADT:::workflow
+      subgraph Unknown["Untreated modality (e.g. VDJ)"]
+      end
+      Unknown:::logicalgrouping
+    end
+    ConcatVDJ([Concatenate]):::component
+    NoIntegration[Multisample Multimodality]
+
+    ConcatVDJ([Concatenate]):::component --> Unknown
+    ConcatGEX([Concatenate]):::component --> MultisampleRNA
+    ConcatADT([Concatenate]):::component --> MultisampleADT
+
+    MultisampleRNA & MultisampleADT & Unknown--> Merge([Merge\nmodalities]):::component --> NoIntegration:::workflow
+    
+  end
+
+  subgraph Wrapper
+    subgraph Integration[Integration]
+      subgraph IntegrationRNA[Integration RNA]
+          direction LR
+          hamony_leiden_rna[Harmony + Leiden]:::workflow
+          scvi_rna[scVI + Leiden]:::workflow
+          scanorama[Scanorama + Leiden]:::workflow
+          other[...]:::workflow
+      end
+      subgraph IntegrationProt[Integration ADT]
+          direction LR
+          hamony_leiden_prot[Harmony + Leiden]:::workflow
+          otherprot[...]:::workflow
+      end
+      subgraph multimodal_integration[Multimodal integration]
+          totalVI([totalVI]):::component
+      end
+      multimodal_integration:::logicalgrouping
+      IntegrationRNA:::logicalgrouping --choose from--> IntegrationProt:::logicalgrouping
+      NoIntegration ---> totalVI
+    end
+    Integration:::logicalgrouping
+    subgraph LegendBox[Legend]
+      direction LR
+      component([component]):::component
+      multiple_component((Multiple Components)):::component
+      workflow["(Sub)workflow"]:::workflow
+      file[/file/]:::file
+      Logicalgrouping[Logical grouping]:::logicalgrouping
+    end
+  LegendBox:::legend
+  end
+  Wrapper:::hide
+
+
+  NoIntegration --choose from--> IntegrationRNA
+  %% NoIntegration ~~~ LegendBox
+
+  ProcGEX1[Process GEX\nSingle Sample]:::workflow --> ConcatGEX
+  ProcADT1[Process ADT\nSingle Sample]:::workflow --> ConcatADT
+
+
+
+  style FullPipeline fill: #5cc,font-size:1.4em,color:#000;
+  classDef hide fill:transparent,color:transparent,stroke:transparent;
+  classDef legend fill:transparent;
+  classDef file fill: #5c5c5c,color:#fff,stroke-dasharray: 5 5;
+  classDef logicalgrouping fill:transparent,stroke-dasharray: 5 5;
+  classDef workflow fill:#ffffde,color:#000;
+  classDef component fill:#ececff,color:#000;
+
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Figure 3: Overview single cell processing steps in OpenPipeline. Rectangles are data objects, parallelograms are Viash modules or subworkflows.
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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/fundamentals/concepts.html b/pr-preview/pr-51/fundamentals/concepts.html new file mode 100644 index 00000000..91a94875 --- /dev/null +++ b/pr-preview/pr-51/fundamentals/concepts.html @@ -0,0 +1,614 @@ + + + + + + + + + +OpenPipelines - Concepts + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Concepts

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Goals

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OpenPipelines strives to provide easy ways to interact with the pipeline and/or codebase for three types of users:

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  • Pipeline executor: runs the pipeline from a GUI side
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  • Pipeline editor: adapts pipelines with existing components for specific projects
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  • Component developer: develops novel components and or pipelines
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This means that openpipelines must be:

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  • Usable by non-experts
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  • Easy to deploy
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  • Provide reproducable results
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  • Scalable
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  • Easy to maintain and adapt
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Requirements

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To meet these demands, the following concepts have been implemented at the core of Openpipeline:

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A common file format: AnnData and MuData 💾

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One of the core principals of OpenPipelines is to use MuData as a common data format throughout the whole pipeline. This means that the input and output for most components and workflows will be a MuData file and converters from and to other common data formats are provided to improve compatibility with up-and downstream applications. Choosing a common data format greatly diminishes the development complexity because it facilitates interfacing between different tools in a pipeline without needing to convert multiple times.

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MuData is a format to store annotated multimodal data. It is derived from the AnnData format. If you are unfamiliar with AnnData or MuData, it is recommended to read up on AnnData first as it is the unimodal counterpart of MuData. MuData can be roughly described as collection of several AnnData objects (stored as a associative array in the .mod attribute). MuData provides a hierarchical way to store the data:

+
MuData
+├─ .mod
+│  ├─ modality_1 (AnnData Object)
+│     ├─ .X
+│     ├─ .layers
+│         ├─ layer_1 
+│         ├─ ...
+│     ├─ .var
+│     ├─ .obs
+│     ├─ .obsm
+│     ├─ .varm
+│     ├─ .uns
+│  ├─ modality_2 (AnnData Object)
+├─ .var
+├─ .obs
+├─ .obms
+├─ .varm
+├─ .uns
+
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  • .mod: an associative array of AnnData objects. Used in OpenPipelines to store the different modalities (CITE-seq, RNA abundance, …)
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  • .X and .layers: matrices storing the measurements with the columns being the variables measured and the rows being the observations (cells in most cases).
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  • .var: metadata for the variables (i.e. annotation for the columns of .X or any matrix in .layers). The number of rows in the .var datafame (or the length of each entry in the dictionairy) is equal to the number of columns in the measurement matrices.
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  • .obs: metadata for the observations (i.e. annotation for the rows of .X or any matrix in .layers). The number of rows in the .obs datafame (or the length of each entry in the dictionairy) is equal to the number of rows in the measurement matrices.
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  • varm: the multi-dimensional variable annotation. A key-dataframe mapping where the number of rows in each dataframe is equal to the number of columns in the measurement matrices.
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  • obsm: the multi-dimensional observation annotation. A key-dataframe mapping where the number of rows in each dataframe is equal to the number of rows in the measurement matrices.
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  • .uns: A mapping where no restrictions are enforced on the dimensions of the data.
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Modularity and a language independent framework 🔳

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TODO

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A graphical interface 📺

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TODO

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Fundamentals

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Philosophy

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Mission

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OpenPipelines are best-practice living workflows for single-cell uni- and multi-omics data. Building a best-practice pipeline requires knowledge and time that not one single person can provide, but rather requires input from a community. Additionally, a best-pratice pipeline needs constant maintenance to keep up to date with the latest standards, ideally sourcing input from a ‘living’ benchmark. Continuous improvement necessitates a robust system for sourcing and applying community input both from a technical and organisational standpoint.

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graph TB
+  ben["🌱📈 Living benchmarks"]
+  pra["🌱📖 Living best practices"]
+  pip["🌱⚙️ Living reproducible pipelines"]
+  ben --> pra --> pip
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Roadmap

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flowchart LR
+  classDef done fill:#a3f6cf,stroke:#000000;
+  classDef wip fill:#f4cb93,stroke:#000000;
+  classDef unprocessed fill:#afadff,stroke:#000000;
+
+  Raw1[Sample 1] --> Split1[/Split\nmodalities/]:::done --> ProcGEX1 & ProcRNAV1 & ProcADT1 & ProcATAC1 & ProcVDJ1
+  ProcGEX1[/Process GEX\nprofile/]:::done --> ConcatGEX[/Concatenate\nprofiles/]:::done --> ProcGEX[/Process GEX\nprofiles/]:::done
+  ProcRNAV1[/Process RNAV\nprofile/]:::wip --> ConcatRNAV[/Concatenate\nprofiles/]:::done --> ProcRNAV[/Process RNAV\nprofiles/]:::wip
+  ProcADT1[/Process ADT\nprofile/]:::done --> ConcatADT[/Concatenate\nprofiles/]:::done --> ProcADT[/Process ADT\nprofiles/]:::done
+  ProcATAC1[/Process ATAC\nprofile/]:::unprocessed --> ConcatATAC[/Concatenate\nprofiles/]:::done --> ProcATAC[/Process ATAC\nprofiles/]:::unprocessed
+  ProcVDJ1[/Process VDJ\nprofile/]:::unprocessed --> ConcatVDJ[/Concatenate\nprofiles/]:::done --> ProcVDJ[/Process VDJ\nprofiles/]:::unprocessed
+  ProcGEX & ProcRNAV & ProcADT & ProcATAC & ProcVDJ --> Merge[/Merge\nmodalities/]:::done --> SetupIntegration[/Setup\nintegration/]:::done --> Integration[/Integration/]:::done
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+
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Figure 1: Status of implemented components. Green: implemented, orange: work in progress, purple: modality included in output but unprocessed,
+GEX: Gene-expression. RNAV: RNA Velocity. ADT: Antibody-Derived Tags. ATAC: Assay for Transposase-Accessible Chromatin.
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OpenPipelines

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Best-practice workflows for single-cell single- and multi-omics data

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"/more_information/code_of_conduct.html", + "/more_information/data_api.html", + "/more_information/faq.html", + "/more_information/index.html" + ] + }, + { + "listing": "/components/index.html", + "items": [ + "/components/workflows/index.html", + "/components/workflows/ingestion/bd_rhapsody.html", + "/components/workflows/multiomics/integration/bbknn_leiden.html", + "/components/workflows/ingestion/cellranger_mapping.html", + "/components/workflows/ingestion/cellranger_multi.html", + "/components/workflows/ingestion/cellranger_postprocessing.html", + "/components/workflows/ingestion/conversion.html", + "/components/workflows/ingestion/demux.html", + "/components/workflows/multiomics/full_pipeline.html", + "/components/workflows/integration/common/harmony_leiden.html", + "/components/workflows/multiomics/integration/harmony_leiden.html", + "/components/workflows/integration/initialize_integration/initialize_integration.html", + "/components/workflows/multiomics/integration/initialize_integration.html", + "/components/workflows/multiomics/integration.html", + "/components/workflows/multiomics/integration/leiden_scvi.html", + "/components/workflows/ingestion/make_reference.html", + "/components/workflows/multiomics/multisample.html", + "/components/workflows/multiomics/prot_multisample.html", + "/components/workflows/multiomics/prot_singlesample.html", + "/components/workflows/multiomics/rna_multisample.html", + "/components/workflows/multiomics/rna_singlesample.html", + "/components/workflows/integration/scanorama_leiden/scanorama_leiden.html", + "/components/workflows/multiomics/integration/scanorama_leiden.html", + "/components/workflows/integration/scvi/scvi.html", + "/components/workflows/multiomics/integration/totalvi_leiden.html", + "/components/modules/index.html", + "/components/modules/metadata/add_id.html", + "/components/modules/mapping/bd_rhapsody.html", + "/components/modules/neighbors/bbknn.html", + "/components/modules/demux/bcl_convert.html", + "/components/modules/demux/bcl2fastq.html", + "/components/modules/reference/build_bdrhap_reference.html", + "/components/modules/reference/build_cellranger_reference.html", + "/components/modules/qc/calculate_qc_metrics.html", + "/components/modules/correction/cellbender_remove_background.html", + "/components/modules/correction/cellbender_remove_background_v0_2.html", + "/components/modules/mapping/cellranger_count.html", + "/components/modules/mapping/cellranger_count_split.html", + "/components/modules/demux/cellranger_mkfastq.html", + "/components/modules/mapping/cellranger_multi.html", + "/components/modules/query/cellxgene_census.html", + "/components/modules/transform/clr.html", + "/components/modules/compression/compress_h5mu.html", + "/components/modules/dataflow/concat.html", + "/components/modules/transform/delete_layer.html", + "/components/modules/filter/do_filter.html", + "/components/modules/download/download_file.html", + "/components/modules/qc/fastqc.html", + "/components/modules/process_10xh5/filter_10xh5.html", + "/components/modules/filter/filter_with_counts.html", + "/components/modules/filter/filter_with_hvg.html", + "/components/modules/filter/filter_with_scrublet.html", + "/components/modules/neighbors/find_neighbors.html", + "/components/modules/convert/from_10xh5_to_h5mu.html", + "/components/modules/convert/from_10xmtx_to_h5mu.html", + "/components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html", + "/components/modules/convert/from_bdrhap_to_h5mu.html", + "/components/modules/convert/from_cellranger_multi_to_h5mu.html", + "/components/modules/convert/from_h5ad_to_h5mu.html", + "/components/modules/convert/from_h5mu_to_h5ad.html", + "/components/modules/integrate/harmonypy.html", + "/components/modules/mapping/htseq_count.html", + "/components/modules/mapping/htseq_count_to_h5mu.html", + "/components/modules/metadata/join_csv.html", + "/components/modules/metadata/join_uns_to_obs.html", + "/components/modules/labels_transfer/knn.html", + "/components/modules/cluster/leiden.html", + "/components/modules/interpret/lianapy.html", + "/components/modules/transform/log1p.html", + "/components/modules/files/make_params.html", + "/components/modules/reference/make_reference.html", + "/components/modules/dataflow/merge.html", + "/components/modules/report/mermaid.html", + "/components/modules/metadata/move_obsm_to_obs.html", + "/components/modules/mapping/multi_star.html", + "/components/modules/mapping/multi_star_to_h5mu.html", + "/components/modules/qc/multiqc.html", + "/components/modules/transform/normalize_total.html", + "/components/modules/dimred/pca.html", + "/components/modules/annotate/popv.html", + "/components/modules/transfer/publish.html", + "/components/modules/transform/regress_out.html", + "/components/modules/filter/remove_modality.html", + "/components/modules/mapping/samtools_sort.html", + "/components/modules/transform/scale.html", + "/components/modules/integrate/scanorama.html", + "/components/modules/integrate/scarches.html", + "/components/modules/velocity/scvelo.html", + "/components/modules/integrate/scvi.html", + "/components/modules/dataflow/split_modalities.html", + "/components/modules/mapping/star_align.html", + "/components/modules/mapping/star_align_v273a.html", + "/components/modules/mapping/star_build_reference.html", + "/components/modules/filter/subset_h5mu.html", + "/components/modules/download/sync_test_resources.html", + "/components/modules/integrate/totalvi.html", + "/components/modules/dimred/umap.html", + "/components/modules/velocity/velocyto.html", + "/components/modules/convert/velocyto_to_h5mu.html", + "/components/modules/labels_transfer/xgboost.html" + ] + }, + { + "listing": "/team/index.html", + "items": [ + "/team/angela_oliveira_pisco/index.html", + "/team/dries_de_maeyer/index.html", 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Data API

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File formats are being discussed in openpipelines-bio/openpipeline#102

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Dataset

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obs:
+ index # cell id
+ sample
+ cell_type
+ organism
+ tissue
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+mod:
+ rna:
+ rnav:
+ prot:
+ atac:
+ vdj:
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+
+

RNA modality

+
mod:
+ rna:
+   layers:
+     counts
+     normalized
+   obs:
+     <qc metrics>
+     doublet_score
+     doublet_bool
+     cluster
+   var:
+     index # feature_id, preferably an ensembl id
+     feature_name
+     <qc metrics>
+     highly_variable
+     highly_variable_score
+   obsm:
+     X_pca
+     X_integrated
+     X_umap
+     annotation # scvi, bbknn, ...
+   obsp:
+     connectivities
+     distances
+
+
+

ADT modality

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mod:
+ prot:
+   layers:
+     counts
+   var:
+      index # feature_id
+      feature_name # Associated protein names
+
+
+

VDJ modality

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mod:
+ vdj:
+   obsm:
+     vdj_t
+     vdj_b
+
+
+

ATAC modality

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mod:
+ atac:
+   layers:
+     counts
+   var:
+     interval
+
+
+

RNA velocity modality

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mod:
+ rnav:
+   layers:
+     spliced
+     unspliced
+ + +
+ +
+ +
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FAQ

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More information

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/robots.txt b/pr-preview/pr-51/robots.txt new file mode 100644 index 00000000..e6e781fe --- /dev/null +++ b/pr-preview/pr-51/robots.txt @@ -0,0 +1 @@ +Sitemap: https://openpipelines.bio/sitemap.xml diff --git a/pr-preview/pr-51/search.json b/pr-preview/pr-51/search.json new file mode 100644 index 00000000..4171a83e --- /dev/null +++ b/pr-preview/pr-51/search.json @@ -0,0 +1,3236 @@ +[ + { + "objectID": "contributing/creating_components.html", + "href": "contributing/creating_components.html", + "title": "Creating components", + "section": "", + "text": "One of the core principals of OpenPipelines is to use MuData as a common data format troughout the whole pipeline. See the concepts page for more information on openpipelines uses MuData to store single-cell data." + }, + { + "objectID": "contributing/creating_components.html#the-config", + "href": "contributing/creating_components.html#the-config", + "title": "Creating components", + "section": "The config", + "text": "The config\nfunctionality:\n name: \"my_component\"\n namespace: \"my_namespace\"\n description: \"My new custom component\"\n authors:\n - __merge__: ../../authors/my_name.yaml\n roles: [ author ]\n arguments:\n - name: \"--output\"\n type: file\n example: \"output_file.h5mu\"\n description: \"Location were the output file should be written to.\"\n direction: \"output\"\n resources:\n - type: python_script\n path: script.py\nplatforms:\n - type: docker\n image: python:3.11\n setup:\n - type: python\n packages: mudata~=0.2.3\n - type: nextflow\n directives:\n label: [highcpu, midmem]\n\nBasic information\nEach component should have the name, a namespace, a description and author information defined in the config. Because a single author can contribute to multiple components, the author information is often duplicated across components, which was causing issues with the author information being out of date and not easy to maintain. Therefore, it was decided to move author information to ./src/authors. Each author has a yaml file containing the author information, and the viash __merge__ property is used to merge this information into the viash configs.\nBasic information checklist:\n\nGive the component a name\nAdd the component to an appropriate namespace\nAdd a description\nAdd author information\n\n\n\nArguments and argument groups\nIf you component requires arguments, they should be defined in arguments or argument_groups. Try tro group individual arguments into argument_groups when the number of arguments become too larg (10 or more as a rule of thumb).\nArgument checklist:\n\nAdd a description and name\nEach argument should have the appropriate type.\nInput and output files should be of type file instead of string and use the appropriate direction:\nIf possible: add an example\nIf the argument can accept multiple values, add multiple: true\nIf the possible input for an argument is limited to certain set of values, use choices:\n\n\n\n(Test)resources\nResources define files that are required for a component to perform its function. These can be scripts, but also additional files like settings for tools you might require. Defining resources is both a necessity because viash needs to know what code to execute, but defining resources also has the added benefit that these resources are automatically made available, regardless of the build environment. For example: resources are automatically mounted within a running docker container.\nThere is a difference between defining resources and test_resources. While resources are required for a component to function, test_resources only need to be included when testing the component (with for example viash test) in addition to the regular resources. Having a look at the example above, resources are defined using the resources: property. It takes a list of multiple files or folders.\nIn openpipelines, it was decided to not use a service like git lfs to include large resources into the repository. Instead, if large resources are required, there are two possibilities: * Large resources required for testing are to uploaded into an s3 bucket that is synced automatically before running tests (both locally and on github). Please ping a maintainer when you open a PR and ask them to upload the files for you. * Other large resources that are not needed for testing can be considered as input. This means that an argument of type: file needs to be created. The downside of this method is that viash is not able to natively support remote files f\nResources checklist: - Script resources are located next to the config and added to the config with the correct type (python_script, r_script, …) - Small resources (<50MB) that are not scripts can also be checked in into the repo, next to the\n\n\nBuild information\nTODO" + }, + { + "objectID": "contributing/creating_components.html#the-script-file", + "href": "contributing/creating_components.html#the-script-file", + "title": "Creating components", + "section": "The script file", + "text": "The script file\nTODO" + }, + { + "objectID": "contributing/creating_components.html#author-information", + "href": "contributing/creating_components.html#author-information", + "title": "Creating components", + "section": "Author information", + "text": "Author information\nTODO" + }, + { + "objectID": "CHANGELOG.html", + "href": "CHANGELOG.html", + "title": "OpenPipelines.bio v0.9.0", + "section": "", + "text": "Update component documentation to v0.9.0 release.\n\n\n\n\n\nUpdate to Viash actions 0.4.0." + }, + { + "objectID": "CHANGELOG.html#major-changes", + "href": "CHANGELOG.html#major-changes", + "title": "OpenPipelines.bio v0.9.0", + "section": "", + "text": "Update component documentation to v0.9.0 release." + }, + { + "objectID": "CHANGELOG.html#minor-changes", + "href": "CHANGELOG.html#minor-changes", + "title": "OpenPipelines.bio v0.9.0", + "section": "", + "text": "Update to Viash actions 0.4.0." + }, + { + "objectID": "CHANGELOG.html#major-changes-1", + "href": "CHANGELOG.html#major-changes-1", + "title": "OpenPipelines.bio v0.9.0", + "section": "MAJOR CHANGES", + "text": "MAJOR CHANGES\n\nUpdate component documentation to v0.8.0 release.\nUse git submodule to access openpipeline repo\nPropose new website structure\nUpdate author page" + }, + { + "objectID": "components/modules/neighbors/bbknn.html", + "href": "components/modules/neighbors/bbknn.html", + "title": "Bbknn", + "section": "", + "text": "ID: bbknn\nNamespace: neighbors\n\n\n\nSource" + }, + { + "objectID": "components/modules/neighbors/bbknn.html#example-commands", + "href": "components/modules/neighbors/bbknn.html#example-commands", + "title": "Bbknn", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/neighbors/bbknn/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"path/to/file\"\nmodality: \"rna\"\nobsm_input: \"X_pca\"\nobs_batch: \"batch\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nuns_output: \"neighbors\"\nobsp_distances: \"distances\"\nobsp_connectivities: \"connectivities\"\nn_neighbors_within_batch: 3\nn_pcs: 50\n# n_trim: 123\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/neighbors/bbknn/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/neighbors/bbknn.html#argument-group", + "href": "components/modules/neighbors/bbknn.html#argument-group", + "title": "Bbknn", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--obsm_input\nThe dimensionality reduction in .obsm to use for neighbour detection. Defaults to X_pca.\nstring, default: \"X_pca\"\n\n\n--obs_batch\n.obs column name discriminating between your batches.\nstring, default: \"batch\"\n\n\n--output\nOutput .h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--uns_output\nMandatory .uns slot to store various neighbor output objects.\nstring, default: \"neighbors\"\n\n\n--obsp_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"distances\"\n\n\n--obsp_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"connectivities\"\n\n\n--n_neighbors_within_batch\nHow many top neighbours to report for each batch; total number of neighbours in the initial k-nearest-neighbours computation will be this number times the number of batches.\ninteger, default: 3\n\n\n--n_pcs\nHow many dimensions (in case of PCA, principal components) to use in the analysis.\ninteger, default: 50\n\n\n--n_trim\nTrim the neighbours of each cell to these many top connectivities. May help with population independence and improve the tidiness of clustering. The lower the value the more independent the individual populations, at the cost of more conserved batch effect. If None (default), sets the parameter value automatically to 10 times neighbors_within_batch times the number of batches. Set to 0 to skip.\ninteger" + }, + { + "objectID": "components/modules/neighbors/bbknn.html#authors", + "href": "components/modules/neighbors/bbknn.html#authors", + "title": "Bbknn", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (author)\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/transform/scale.html", + "href": "components/modules/transform/scale.html", + "title": "Scale", + "section": "", + "text": "ID: scale\nNamespace: transform\n\n\n\nSource" + }, + { + "objectID": "components/modules/transform/scale.html#example-commands", + "href": "components/modules/transform/scale.html#example-commands", + "title": "Scale", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/transform/scale/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# max_value: 123.0\nzero_center: true\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/transform/scale/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/transform/scale.html#argument-group", + "href": "components/modules/transform/scale.html#argument-group", + "title": "Scale", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file.\nfile, required, example: \"input.h5mu\"\n\n\n--modality\nList of modalities to process.\nstring, default: \"rna\"\n\n\n--max_value\nClip (truncate) to this value after scaling. Does not clip by default.\ndouble\n\n\n--zero_center\nIf False, omit zero-centering variables, which allows to handle sparse input efficiently.\nboolean, default: TRUE\n\n\n--output\nOutput h5mu file.\nfile, required, default: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/transform/scale.html#authors", + "href": "components/modules/transform/scale.html#authors", + "title": "Scale", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/transform/clr.html", + "href": "components/modules/transform/clr.html", + "title": "Clr", + "section": "", + "text": "ID: clr\nNamespace: transform\n\n\n\nSource" + }, + { + "objectID": "components/modules/transform/clr.html#example-commands", + "href": "components/modules/transform/clr.html#example-commands", + "title": "Clr", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/transform/clr/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"prot\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n# output_layer: \"foo\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/transform/clr/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/transform/clr.html#argument-group", + "href": "components/modules/transform/clr.html#argument-group", + "title": "Clr", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"prot\"\n\n\n--output\nOutput h5mu file.\nfile, required, default: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--output_layer\nOutput layer to use. By default, use X.\nstring" + }, + { + "objectID": "components/modules/transform/clr.html#authors", + "href": "components/modules/transform/clr.html#authors", + "title": "Clr", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/transform/log1p.html", + "href": "components/modules/transform/log1p.html", + "title": "Log1p", + "section": "", + "text": "ID: log1p\nNamespace: transform\n\n\n\nSource\nComputes X = log(X + 1), where log denotes the natural logarithm unless a different base is given" + }, + { + "objectID": "components/modules/transform/log1p.html#example-commands", + "href": "components/modules/transform/log1p.html#example-commands", + "title": "Log1p", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/transform/log1p/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# input_layer: \"foo\"\n# output_layer: \"foo\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n# base: 2\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/transform/log1p/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/transform/log1p.html#argument-group", + "href": "components/modules/transform/log1p.html#argument-group", + "title": "Log1p", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--input_layer\nInput layer to use. If None, X is normalized\nstring\n\n\n--output_layer\nOutput layer to use. By default, use X.\nstring\n\n\n--output\nOutput h5mu file.\nfile, required, default: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--base\n\ndouble, example: 2" + }, + { + "objectID": "components/modules/transform/log1p.html#authors", + "href": "components/modules/transform/log1p.html#authors", + "title": "Log1p", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)\nRobrecht Cannoodt (contributor)" + }, + { + "objectID": "components/modules/dataflow/concat.html", + "href": "components/modules/dataflow/concat.html", + "title": "Concat", + "section": "", + "text": "ID: concat\nNamespace: dataflow\n\n\n\nSource" + }, + { + "objectID": "components/modules/dataflow/concat.html#example-commands", + "href": "components/modules/dataflow/concat.html#example-commands", + "title": "Concat", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/dataflow/concat/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: [\"sample_paths\"]\n# input_id: [\"foo\"]\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nobs_sample_name: \"sample_id\"\nother_axis_mode: \"move\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/dataflow/concat/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/dataflow/concat.html#argument-group", + "href": "components/modules/dataflow/concat.html#argument-group", + "title": "Concat", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPaths to the different samples to be concatenated.\nfile, required, example: \"sample_paths\"\n\n\n--input_id\nNames of the different samples that have to be concatenated. Must be specified when using ‘–mode move’. In this case, the ids will be used for the columns names of the dataframes registring the conflicts. If specified, must be of same length as --input.\nstring\n\n\n--output\n\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--obs_sample_name\nName of the .obs key under which to add the sample names.\nstring, default: \"sample_id\"\n\n\n--other_axis_mode\nHow to handle the merging of other axis (var, obs, …). - None: keep no data - same: only keep elements of the matrices which are the same in each of the samples - unique: only keep elements for which there is only 1 possible value (1 value that can occur in multiple samples) - first: keep the annotation from the first sample - only: keep elements that show up in only one of the objects (1 unique element in only 1 sample) - move: identical to ‘same’, but moving the conflicting values to .varm or .obsm\nstring, default: \"move\"" + }, + { + "objectID": "components/modules/dataflow/concat.html#authors", + "href": "components/modules/dataflow/concat.html#authors", + "title": "Concat", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/process_10xh5/filter_10xh5.html", + "href": "components/modules/process_10xh5/filter_10xh5.html", + "title": "Filter 10xh5", + "section": "", + "text": "ID: filter_10xh5\nNamespace: process_10xh5\n\n\n\nSource" + }, + { + "objectID": "components/modules/process_10xh5/filter_10xh5.html#example-commands", + "href": "components/modules/process_10xh5/filter_10xh5.html#example-commands", + "title": "Filter 10xh5", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/process_10xh5/filter_10xh5/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"pbmc_1k_protein_v3_raw_feature_bc_matrix.h5\"\n# output: \"$id.$key.output.h5\"\nmin_library_size: 0\nmin_cells_per_gene: 0\n# keep_feature_types: [\"Antibody Capture\"]\nverbose: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/process_10xh5/filter_10xh5/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/process_10xh5/filter_10xh5.html#argument-group", + "href": "components/modules/process_10xh5/filter_10xh5.html#argument-group", + "title": "Filter 10xh5", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nAn h5 file from the 10x genomics website.\nfile, required, example: \"pbmc_1k_protein_v3_raw_feature_bc_matrix.h5\"\n\n\n--output\nOutput h5 file.\nfile, required, example: \"pbmc_1k_protein_v3_raw_feature_bc_matrix_filtered.h5\"\n\n\n--min_library_size\nMinimum library size.\ninteger, default: 0\n\n\n--min_cells_per_gene\nMinimum number of cells per gene.\ninteger, default: 0\n\n\n--keep_feature_types\nSpecify which feature types will never be filtered out\nstring, example: \"Antibody Capture\"\n\n\n--verbose\nIncrease verbosity\nboolean_true" + }, + { + "objectID": "components/modules/process_10xh5/filter_10xh5.html#authors", + "href": "components/modules/process_10xh5/filter_10xh5.html#authors", + "title": "Filter 10xh5", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/metadata/join_uns_to_obs.html", + "href": "components/modules/metadata/join_uns_to_obs.html", + "title": "Join uns to obs", + "section": "", + "text": "ID: join_uns_to_obs\nNamespace: metadata\n\n\n\nSource" + }, + { + "objectID": "components/modules/metadata/join_uns_to_obs.html#example-commands", + "href": "components/modules/metadata/join_uns_to_obs.html#example-commands", + "title": "Join uns to obs", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/metadata/join_uns_to_obs/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\nuns_key: # please fill in - example: \"foo\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/metadata/join_uns_to_obs/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/metadata/join_uns_to_obs.html#argument-group", + "href": "components/modules/metadata/join_uns_to_obs.html#argument-group", + "title": "Join uns to obs", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--uns_key\n\nstring, required\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/metadata/move_obsm_to_obs.html", + "href": "components/modules/metadata/move_obsm_to_obs.html", + "title": "Move obsm to obs", + "section": "", + "text": "ID: move_obsm_to_obs\nNamespace: metadata\n\n\n\nSource\nNewly created columns in .obs will be created from the .obsm key suffixed with an underscore and the name of the columns of the specified .obsm matrix" + }, + { + "objectID": "components/modules/metadata/move_obsm_to_obs.html#example-commands", + "href": "components/modules/metadata/move_obsm_to_obs.html#example-commands", + "title": "Move obsm to obs", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/metadata/move_obsm_to_obs/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# MuData Input\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\nobsm_key: # please fill in - example: \"foo\"\n\n# MuData Output\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/metadata/move_obsm_to_obs/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/metadata/move_obsm_to_obs.html#argument-groups", + "href": "components/modules/metadata/move_obsm_to_obs.html#argument-groups", + "title": "Move obsm to obs", + "section": "Argument groups", + "text": "Argument groups\n\nMuData Input\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--obsm_key\nKey of a data structure to move from .obsm to .obs.\nstring, required\n\n\n\n\n\nMuData Output\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/metadata/move_obsm_to_obs.html#authors", + "href": "components/modules/metadata/move_obsm_to_obs.html#authors", + "title": "Move obsm to obs", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/modules/demux/cellranger_mkfastq.html", + "href": "components/modules/demux/cellranger_mkfastq.html", + "title": "Cellranger mkfastq", + "section": "", + "text": "ID: cellranger_mkfastq\nNamespace: demux\n\n\n\nSource" + }, + { + "objectID": "components/modules/demux/cellranger_mkfastq.html#example-commands", + "href": "components/modules/demux/cellranger_mkfastq.html#example-commands", + "title": "Cellranger mkfastq", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/demux/cellranger_mkfastq/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"/path/to/bcl\"\nsample_sheet: # please fill in - example: \"SampleSheet.csv\"\n# output: \"$id.$key.output.output\"\n# reports: \"$id.$key.reports.reports\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/demux/cellranger_mkfastq/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/demux/cellranger_mkfastq.html#argument-group", + "href": "components/modules/demux/cellranger_mkfastq.html#argument-group", + "title": "Cellranger mkfastq", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to the (untarred) BCL files. Expects ‘RunParameters.xml’ at ‘./’.\nfile, required, example: \"/path/to/bcl\"\n\n\n--sample_sheet\nThe path to the sample sheet.\nfile, required, example: \"SampleSheet.csv\"\n\n\n--output\nThe folder to store the demux results\nfile, required, default: \"fastqs\", example: \"/path/to/output\"\n\n\n--reports\nReports directory\nfile, example: \"reports_dir\"" + }, + { + "objectID": "components/modules/demux/cellranger_mkfastq.html#authors", + "href": "components/modules/demux/cellranger_mkfastq.html#authors", + "title": "Cellranger mkfastq", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nSamuel D’Souza (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/demux/bcl_convert.html", + "href": "components/modules/demux/bcl_convert.html", + "title": "Bcl convert", + "section": "", + "text": "ID: bcl_convert\nNamespace: demux\n\n\n\nSource\nInformation about upgrading from bcl2fastq via https://emea.support.illumina.com/bulletins/2020/10/upgrading-from-bcl2fastq-to-bcl-convert.html and https://support.illumina.com/sequencing/sequencing_software/bcl-convert/compatibility.html" + }, + { + "objectID": "components/modules/demux/bcl_convert.html#example-commands", + "href": "components/modules/demux/bcl_convert.html#example-commands", + "title": "Bcl convert", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/demux/bcl_convert/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"bcl_dir\"\nsample_sheet: # please fill in - example: \"bcl_dir\"\n# output: \"$id.$key.output.output\"\n# reports: \"$id.$key.reports.reports\"\ntest_mode: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/demux/bcl_convert/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/demux/bcl_convert.html#argument-group", + "href": "components/modules/demux/bcl_convert.html#argument-group", + "title": "Bcl convert", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput run directory\nfile, required, example: \"bcl_dir\"\n\n\n--sample_sheet\nPointer to the sample sheet\nfile, required, example: \"bcl_dir\"\n\n\n--output\nOutput directory containig fastq files\nfile, required, example: \"fastq_dir\"\n\n\n--reports\nReports directory\nfile, example: \"reports_dir\"\n\n\n--test_mode\nShould bcl-convert be run in test mode (using –first-tile-only)?\nboolean, default: FALSE" + }, + { + "objectID": "components/modules/demux/bcl_convert.html#authors", + "href": "components/modules/demux/bcl_convert.html#authors", + "title": "Bcl convert", + "section": "Authors", + "text": "Authors\n\nToni Verbeiren (author, maintainer)\nMarijke Van Moerbeke (author)" + }, + { + "objectID": "components/modules/cluster/leiden.html", + "href": "components/modules/cluster/leiden.html", + "title": "Leiden", + "section": "", + "text": "ID: leiden\nNamespace: cluster\n\n\n\nSource\nLeiden is an improved version of the Louvain algorithm [Blondel08]. It has been proposed for single-cell analysis by [Levine15]. This requires having ran neighbors/find_neighbors or neighbors/bbknn first.\nBlondel08: Blondel et al. (2008), Fast unfolding of communities in large networks, J. Stat. Mech.\nLevine15: Levine et al. (2015), Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis, Cell.\nTraag18: Traag et al. (2018), From Louvain to Leiden: guaranteeing well-connected communities arXiv.\nWolf18: Wolf et al. (2018), Scanpy: large-scale single-cell gene expression data analysis, Genome Biology." + }, + { + "objectID": "components/modules/cluster/leiden.html#example-commands", + "href": "components/modules/cluster/leiden.html#example-commands", + "title": "Leiden", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/cluster/leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\nobsp_connectivities: \"connectivities\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nobsm_name: \"leiden\"\nresolution: [1]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/cluster/leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/cluster/leiden.html#argument-group", + "href": "components/modules/cluster/leiden.html#argument-group", + "title": "Leiden", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput file.\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--obsp_connectivities\nIn which .obsp slot the neighbor connectivities can be found.\nstring, default: \"connectivities\"\n\n\n--output\nOutput file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"\n\n\n--obsm_name\nName of the .obsm key under which to add the cluster labels. The name of the columns in the matrix will correspond to the resolutions.\nstring, default: \"leiden\"\n\n\n--resolution\nA parameter value controlling the coarseness of the clustering. Higher values lead to more clusters. Multiple values will result in clustering being performed multiple times.\ndouble, default: 1" + }, + { + "objectID": "components/modules/cluster/leiden.html#authors", + "href": "components/modules/cluster/leiden.html#authors", + "title": "Leiden", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)" + }, + { + "objectID": "components/modules/qc/multiqc.html", + "href": "components/modules/qc/multiqc.html", + "title": "Multiqc", + "section": "", + "text": "ID: multiqc\nNamespace: qc\n\n\n\nSource\nIt searches a given directory for analysis logs and compiles a HTML report. It’s a general use tool, perfect for summarising the output from numerous bioinformatics tools" + }, + { + "objectID": "components/modules/qc/multiqc.html#example-commands", + "href": "components/modules/qc/multiqc.html#example-commands", + "title": "Multiqc", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/qc/multiqc/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: [\"input.txt\"]\n# output: \"$id.$key.output.output\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/qc/multiqc/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/qc/multiqc.html#argument-group", + "href": "components/modules/qc/multiqc.html#argument-group", + "title": "Multiqc", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInputs for MultiQC.\nfile, required, example: \"input.txt\"\n\n\n--output\nCreate report in the specified output directory.\nfile, required, example: \"report\"" + }, + { + "objectID": "components/modules/download/sync_test_resources.html", + "href": "components/modules/download/sync_test_resources.html", + "title": "Sync test resources", + "section": "", + "text": "ID: sync_test_resources\nNamespace: download\n\n\n\nSource" + }, + { + "objectID": "components/modules/download/sync_test_resources.html#example-commands", + "href": "components/modules/download/sync_test_resources.html#example-commands", + "title": "Sync test resources", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/download/sync_test_resources/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: \"s3://openpipelines-data\"\n# output: \"$id.$key.output.output\"\nquiet: false\ndryrun: false\ndelete: false\n# exclude: [\"foo\"]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/download/sync_test_resources/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/download/sync_test_resources.html#argument-group", + "href": "components/modules/download/sync_test_resources.html#argument-group", + "title": "Sync test resources", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to the S3 bucket to sync from.\nstring, default: \"s3://openpipelines-data\"\n\n\n--output\nPath to the test resource directory.\nfile, default: \"resources_test\"\n\n\n--quiet\nDisplays the operations that would be performed using the specified command without actually running them.\nboolean_true\n\n\n--dryrun\nDoes not display the operations performed from the specified command.\nboolean_true\n\n\n--delete\nFiles that exist in the destination but not in the source are deleted during sync.\nboolean_true\n\n\n--exclude\nExclude all files or objects from the command that matches the specified pattern.\nstring" + }, + { + "objectID": "components/modules/download/sync_test_resources.html#authors", + "href": "components/modules/download/sync_test_resources.html#authors", + "title": "Sync test resources", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/compression/compress_h5mu.html", + "href": "components/modules/compression/compress_h5mu.html", + "title": "Compress h5mu", + "section": "", + "text": "ID: compress_h5mu\nNamespace: compression\n\n\n\nSource" + }, + { + "objectID": "components/modules/compression/compress_h5mu.html#example-commands", + "href": "components/modules/compression/compress_h5mu.html#example-commands", + "title": "Compress h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/compression/compress_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"sample_path\"\n# output: \"$id.$key.output.output\"\ncompression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/compression/compress_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/compression/compress_h5mu.html#argument-group", + "href": "components/modules/compression/compress_h5mu.html#argument-group", + "title": "Compress h5mu", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to the input .h5mu.\nfile, required, example: \"sample_path\"\n\n\n--output\nlocation of output file.\nfile, required\n\n\n--compression\nCompression type.\nstring, default: \"gzip\"" + }, + { + "objectID": "components/modules/compression/compress_h5mu.html#authors", + "href": "components/modules/compression/compress_h5mu.html#authors", + "title": "Compress h5mu", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/annotate/popv.html", + "href": "components/modules/annotate/popv.html", + "title": "Popv", + "section": "", + "text": "ID: popv\nNamespace: annotate\n\n\n\nSource\nNote that this is a one-shot version of PopV." + }, + { + "objectID": "components/modules/annotate/popv.html#example-commands", + "href": "components/modules/annotate/popv.html#example-commands", + "title": "Popv", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/annotate/popv/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# input_layer: \"foo\"\n# input_obs_batch: \"foo\"\n# input_var_subset: \"foo\"\n# input_obs_label: \"foo\"\nunknown_celltype_label: \"unknown\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Arguments\nmethods: # please fill in - example: [\"knn_on_scvi\", \"scanvi\"]\n\n# Reference\nreference: # please fill in - example: \"TS_Bladder_filtered.h5ad\"\n# reference_layer: \"foo\"\nreference_obs_label: \"cell_ontology_class\"\nreference_obs_batch: \"donor_assay\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/annotate/popv/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/annotate/popv.html#argument-groups", + "href": "components/modules/annotate/popv.html#argument-groups", + "title": "Popv", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\nArguments related to the input (aka query) dataset.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file.\nfile, required, example: \"input.h5mu\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n--input_layer\nWhich layer to use. If no value is provided, the counts are assumed to be in the .X slot. Otherwise, count data is expected to be in .layers[input_layer].\nstring\n\n\n--input_obs_batch\nKey in obs field of input adata for batch information. If no value is provided, batch label is assumed to be unknown.\nstring\n\n\n--input_var_subset\nSubset the input object with this column.\nstring\n\n\n--input_obs_label\nKey in obs field of input adata for label information. This is only used for training scANVI. Unlabelled cells should be set to \"unknown_celltype_label\".\nstring\n\n\n--unknown_celltype_label\nIf input_obs_label is specified, cells with this value will be treated as unknown and will be predicted by the model.\nstring, default: \"unknown\"\n\n\n\n\n\nReference\nArguments related to the reference dataset.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--reference\nUser-provided reference tissue. The data that will be used as reference to call cell types.\nfile, required, example: \"TS_Bladder_filtered.h5ad\"\n\n\n--reference_layer\nWhich layer to use. If no value is provided, the counts are assumed to be in the .X slot. Otherwise, count data is expected to be in .layers[reference_layer].\nstring\n\n\n--reference_obs_label\nKey in obs field of reference AnnData with cell-type information.\nstring, default: \"cell_ontology_class\"\n\n\n--reference_obs_batch\nKey in obs field of input adata for batch information.\nstring, default: \"donor_assay\"\n\n\n\n\n\nOutputs\nOutput arguments.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"\n\n\n\n\n\nArguments\nOther arguments.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--methods\nMethods to call cell types. By default, runs to knn_on_scvi and scanvi.\nstring, required, example: \"knn_on_scvi\", example: \"scanvi\"" + }, + { + "objectID": "components/modules/annotate/popv.html#authors", + "href": "components/modules/annotate/popv.html#authors", + "title": "Popv", + "section": "Authors", + "text": "Authors\n\nMatthias Beyens (author)\nRobrecht Cannoodt (author)" + }, + { + "objectID": "components/modules/labels_transfer/xgboost.html", + "href": "components/modules/labels_transfer/xgboost.html", + "title": "Xgboost", + "section": "", + "text": "ID: xgboost\nNamespace: labels_transfer\n\n\n\nSource" + }, + { + "objectID": "components/modules/labels_transfer/xgboost.html#example-commands", + "href": "components/modules/labels_transfer/xgboost.html#example-commands", + "title": "Xgboost", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/labels_transfer/xgboost/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Execution arguments\nforce_retrain: false\nuse_gpu: false\nverbosity: 1\n# model_output: \"$id.$key.model_output.model_output\"\n\n# Learning parameters\nlearning_rate: 0.3\nmin_split_loss: 0\nmax_depth: 6\nmin_child_weight: 1\nmax_delta_step: 0\nsubsample: 1\nsampling_method: \"uniform\"\ncolsample_bytree: 1\ncolsample_bylevel: 1\ncolsample_bynode: 1\nreg_lambda: 1\nreg_alpha: 0\nscale_pos_weight: 1\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/labels_transfer/xgboost/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/labels_transfer/xgboost.html#argument-groups", + "href": "components/modules/labels_transfer/xgboost.html#argument-groups", + "title": "Xgboost", + "section": "Argument groups", + "text": "Argument groups\n\nInput dataset (query) arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nThe query data to transfer the labels to. Should be a .h5mu file.\nfile, required\n\n\n--modality\nWhich modality to use.\nstring, default: \"rna\"\n\n\n--input_obsm_features\nThe .obsm key of the embedding to use for the classifier’s inference. If not provided, the .X slot will be used instead. Make sure that embedding was obtained in the same way as the reference embedding (e.g. by the same model or preprocessing).\nstring, example: \"X_integrated_scanvi\"\n\n\n\n\n\nReference dataset arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--reference\nThe reference data to train classifiers on.\nfile, example: \"https:/zenodo.org/record/6337966/files/HLCA_emb_and_metadata.h5ad\"\n\n\n--reference_obsm_features\nThe .obsm key of the embedding to use for the classifier’s training. Make sure that embedding was obtained in the same way as the query embedding (e.g. by the same model or preprocessing).\nstring, required, default: \"X_integrated_scanvi\"\n\n\n--reference_obs_targets\nThe .obs key of the target labels to tranfer.\nstring, default: \"ann_level_1\", default: \"ann_level_2\", default: \"ann_level_3\", default: \"ann_level_4\", default: \"ann_level_5\", default: \"ann_finest_level\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nThe query data in .h5mu format with predicted labels transfered from the reference.\nfile, required\n\n\n--output_obs_predictions\nIn which .obs slots to store the predicted information. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the \"_pred\" suffix.\nstring\n\n\n--output_obs_uncertainty\nIn which .obs slots to store the uncertainty of the predictions. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the \"_uncertainty\" suffix.\nstring\n\n\n--output_uns_parameters\nThe .uns key to store additional information about the parameters used for the label transfer.\nstring, default: \"labels_transfer\"\n\n\n\n\n\nExecution arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--force_retrain\nRetrain models on the reference even if model_output directory already has trained classifiers. WARNING! It will rewrite existing classifiers for targets in the model_output directory!\nboolean_true\n\n\n--use_gpu\nUse GPU during models training and inference (recommended).\nboolean, default: FALSE\n\n\n--verbosity\nThe verbosity level for evaluation of the classifier from the range [0,2]\ninteger, default: 1\n\n\n--model_output\nOutput directory for model\nfile, default: \"model\"\n\n\n\n\n\nLearning parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--learning_rate\nStep size shrinkage used in update to prevents overfitting. Range: [0,1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 0.3\n\n\n--min_split_loss\nMinimum loss reduction required to make a further partition on a leaf node of the tree. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 0\n\n\n--max_depth\nMaximum depth of a tree. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ninteger, default: 6\n\n\n--min_child_weight\nMinimum sum of instance weight (hessian) needed in a child. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ninteger, default: 1\n\n\n--max_delta_step\nMaximum delta step we allow each leaf output to be. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 0\n\n\n--subsample\nSubsample ratio of the training instances. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 1\n\n\n--sampling_method\nThe method to use to sample the training instances. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\nstring, default: \"uniform\"\n\n\n--colsample_bytree\nFraction of columns to be subsampled. Range (0, 1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 1\n\n\n--colsample_bylevel\nSubsample ratio of columns for each level. Range (0, 1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 1\n\n\n--colsample_bynode\nSubsample ratio of columns for each node (split). Range (0, 1]. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 1\n\n\n--reg_lambda\nL2 regularization term on weights. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 1\n\n\n--reg_alpha\nL1 regularization term on weights. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 0\n\n\n--scale_pos_weight\nControl the balance of positive and negative weights, useful for unbalanced classes. See https://xgboost.readthedocs.io/en/stable/parameter.html#parameters-for-tree-booster for the reference\ndouble, default: 1" + }, + { + "objectID": "components/modules/labels_transfer/xgboost.html#authors", + "href": "components/modules/labels_transfer/xgboost.html#authors", + "title": "Xgboost", + "section": "Authors", + "text": "Authors\n\nVladimir Shitov (author)" + }, + { + "objectID": "components/modules/convert/from_cellranger_multi_to_h5mu.html", + "href": "components/modules/convert/from_cellranger_multi_to_h5mu.html", + "title": "From cellranger multi to h5mu", + "section": "", + "text": "ID: from_cellranger_multi_to_h5mu\nNamespace: convert\n\n\n\nSource\nBy default, will map the following library type names to modality names: - Gene Expression: rna - Peaks: atac - Antibody Capture: prot - VDJ: vdj - VDJ-T: vdj_t - VDJ-B: vdj_b - CRISPR Guide Capture: crispr - Multiplexing Capture: hashing\nOther library types have their whitepace removed and dashes replaced by underscores to generate the modality name.\nCurrently does not allow parsing the output from cell barcode demultiplexing." + }, + { + "objectID": "components/modules/convert/from_cellranger_multi_to_h5mu.html#example-commands", + "href": "components/modules/convert/from_cellranger_multi_to_h5mu.html#example-commands", + "title": "From cellranger multi to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/from_cellranger_multi_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input_dir_containing_modalities\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nuns_metrics: \"metrics_cellranger\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/from_cellranger_multi_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/from_cellranger_multi_to_h5mu.html#argument-group", + "href": "components/modules/convert/from_cellranger_multi_to_h5mu.html#argument-group", + "title": "From cellranger multi to h5mu", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput folder. Must contain the output from a cellranger multi run.\nfile, required, example: \"input_dir_containing_modalities\"\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"\n\n\n--uns_metrics\nName of the .uns slot under which to QC metrics (if any).\nstring, default: \"metrics_cellranger\"" + }, + { + "objectID": "components/modules/convert/from_cellranger_multi_to_h5mu.html#authors", + "href": "components/modules/convert/from_cellranger_multi_to_h5mu.html#authors", + "title": "From cellranger multi to h5mu", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/convert/from_h5ad_to_h5mu.html", + "href": "components/modules/convert/from_h5ad_to_h5mu.html", + "title": "From h5ad to h5mu", + "section": "", + "text": "ID: from_h5ad_to_h5mu\nNamespace: convert\n\n\n\nSource" + }, + { + "objectID": "components/modules/convert/from_h5ad_to_h5mu.html#example-commands", + "href": "components/modules/convert/from_h5ad_to_h5mu.html#example-commands", + "title": "From h5ad to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/from_h5ad_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: [\"input.h5ad\"]\nmodality: [\"rna\"]\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/from_h5ad_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/from_h5ad_to_h5mu.html#argument-group", + "href": "components/modules/convert/from_h5ad_to_h5mu.html#argument-group", + "title": "From h5ad to h5mu", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5ad files\nfile, required, default: \"input.h5ad\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--output\nOutput MuData file.\nfile, default: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/convert/from_h5ad_to_h5mu.html#authors", + "href": "components/modules/convert/from_h5ad_to_h5mu.html#authors", + "title": "From h5ad to h5mu", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)" + }, + { + "objectID": "components/modules/convert/velocyto_to_h5mu.html", + "href": "components/modules/convert/velocyto_to_h5mu.html", + "title": "Velocyto to h5mu", + "section": "", + "text": "ID: velocyto_to_h5mu\nNamespace: convert\n\n\n\nSource\nIf an input h5mu file is also provided, the velocity h5ad object will get added to that h5mu instead." + }, + { + "objectID": "components/modules/convert/velocyto_to_h5mu.html#example-commands", + "href": "components/modules/convert/velocyto_to_h5mu.html#example-commands", + "title": "Velocyto to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/velocyto_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput_loom: # please fill in - example: \"input.loom\"\n# input_h5mu: \"input.h5mu\"\nmodality: \"rna_velocity\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nlayer_spliced: \"velo_spliced\"\nlayer_unspliced: \"velo_unspliced\"\nlayer_ambiguous: \"velo_ambiguous\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/velocyto_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/velocyto_to_h5mu.html#argument-groups", + "href": "components/modules/convert/velocyto_to_h5mu.html#argument-groups", + "title": "Velocyto to h5mu", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input_loom\nPath to the input loom file.\nfile, required, example: \"input.loom\"\n\n\n--input_h5mu\nIf a MuData file is provided,\nfile, example: \"input.h5mu\"\n\n\n--modality\nThe name of the modality to operate on.\nstring, default: \"rna_velocity\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nPath to the output MuData file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--layer_spliced\nOutput layer for the spliced reads.\nstring, default: \"velo_spliced\"\n\n\n--layer_unspliced\nOutput layer for the unspliced reads.\nstring, default: \"velo_unspliced\"\n\n\n--layer_ambiguous\nOutput layer for the ambiguous reads.\nstring, default: \"velo_ambiguous\"" + }, + { + "objectID": "components/modules/convert/velocyto_to_h5mu.html#authors", + "href": "components/modules/convert/velocyto_to_h5mu.html#authors", + "title": "Velocyto to h5mu", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer, author)\nRobrecht Cannoodt (author)\nAngela Oliveira Pisco (contributor)" + }, + { + "objectID": "components/modules/convert/from_bdrhap_to_h5mu.html", + "href": "components/modules/convert/from_bdrhap_to_h5mu.html", + "title": "From bdrhap to h5mu", + "section": "", + "text": "ID: from_bdrhap_to_h5mu\nNamespace: convert\n\n\n\nSource" + }, + { + "objectID": "components/modules/convert/from_bdrhap_to_h5mu.html#example-commands", + "href": "components/modules/convert/from_bdrhap_to_h5mu.html#example-commands", + "title": "From bdrhap to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/from_bdrhap_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"my_id\"\ninput: # please fill in - example: \"input_dir/\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/from_bdrhap_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/from_bdrhap_to_h5mu.html#argument-groups", + "href": "components/modules/convert/from_bdrhap_to_h5mu.html#argument-groups", + "title": "From bdrhap to h5mu", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nA sample ID.\nstring, required, example: \"my_id\"\n\n\n--input\nThe output of a BD Rhapsody workflow.\nfile, required, example: \"input_dir\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/convert/from_bdrhap_to_h5mu.html#authors", + "href": "components/modules/convert/from_bdrhap_to_h5mu.html#authors", + "title": "From bdrhap to h5mu", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/correction/cellbender_remove_background_v0_2.html", + "href": "components/modules/correction/cellbender_remove_background_v0_2.html", + "title": "Cellbender remove background v0 2", + "section": "", + "text": "ID: cellbender_remove_background_v0_2\nNamespace: correction\n\n\n\nSource\nThis module removes counts due to ambient RNA molecules and random barcode swapping from (raw) UMI-based scRNA-seq count matrices. At the moment, only the count matrices produced by the CellRanger count pipeline is supported. Support for additional tools and protocols will be added in the future. A quick start tutorial can be found here.\nFleming et al. 2022, bioRxiv." + }, + { + "objectID": "components/modules/correction/cellbender_remove_background_v0_2.html#example-commands", + "href": "components/modules/correction/cellbender_remove_background_v0_2.html#example-commands", + "title": "Cellbender remove background v0 2", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/correction/cellbender_remove_background_v0_2/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nlayer_output: \"corrected\"\nobs_latent_rt_efficiency: \"latent_rt_efficiency\"\nobs_latent_cell_probability: \"latent_cell_probability\"\nobs_latent_scale: \"latent_scale\"\nvar_ambient_expression: \"ambient_expression\"\nobsm_latent_gene_encoding: \"cellbender_latent_gene_encoding\"\n\n# Arguments\n# expected_cells: 1000\n# total_droplets_included: 25000\nexpected_cells_from_qc: true\nmodel: \"full\"\nepochs: 150\nlow_count_threshold: 15\nz_dim: 100\nz_layers: [500]\ntraining_fraction: 0.9\nempty_drop_training_fraction: 0.5\nfpr: [0.01]\nexclude_antibody_capture: false\n# learning_rate: 1.0E-4\ncuda: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/correction/cellbender_remove_background_v0_2/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/correction/cellbender_remove_background_v0_2.html#argument-groups", + "href": "components/modules/correction/cellbender_remove_background_v0_2.html#argument-groups", + "title": "Cellbender remove background v0 2", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file.\nfile, required, example: \"input.h5mu\"\n\n\n--modality\nList of modalities to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nFull count matrix as an h5mu file, with background RNA removed. This file contains all the original droplet barcodes.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"\n\n\n--layer_output\nOutput layer\nstring, default: \"corrected\"\n\n\n--obs_latent_rt_efficiency\n\nstring, default: \"latent_rt_efficiency\"\n\n\n--obs_latent_cell_probability\n\nstring, default: \"latent_cell_probability\"\n\n\n--obs_latent_scale\n\nstring, default: \"latent_scale\"\n\n\n--var_ambient_expression\n\nstring, default: \"ambient_expression\"\n\n\n--obsm_latent_gene_encoding\n\nstring, default: \"cellbender_latent_gene_encoding\"\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--expected_cells\nNumber of cells expected in the dataset (a rough estimate within a factor of 2 is sufficient).\ninteger, example: 1000\n\n\n--total_droplets_included\nThe number of droplets from the rank-ordered UMI plot that will be analyzed. The largest ‘total_droplets’ droplets will have their cell probabilities inferred as an output.\ninteger, example: 25000\n\n\n--expected_cells_from_qc\nWill use the Cell Ranger QC to determine the estimated number of cells\nboolean, default: TRUE\n\n\n--model\nWhich model is being used for count data. ‘simple’ does not model either ambient RNA or random barcode swapping (for debugging purposes – not recommended). ‘ambient’ assumes background RNA is incorporated into droplets. ‘swapping’ assumes background RNA comes from random barcode swapping. ‘full’ uses a combined ambient and swapping model.\nstring, default: \"full\"\n\n\n--epochs\nNumber of epochs to train.\ninteger, default: 150\n\n\n--low_count_threshold\nDroplets with UMI counts below this number are completely excluded from the analysis. This can help identify the correct prior for empty droplet counts in the rare case where empty counts are extremely high (over 200).\ninteger, default: 15\n\n\n--z_dim\nDimension of latent variable z.\ninteger, default: 100\n\n\n--z_layers\nDimension of hidden layers in the encoder for z.\ninteger, default: 500\n\n\n--training_fraction\nTraining detail: the fraction of the data used for training. The rest is never seen by the inference algorithm. Speeds up learning.\ndouble, default: 0.9\n\n\n--empty_drop_training_fraction\nTraining detail: the fraction of the training data each epoch that is drawn (randomly sampled) from surely empty droplets.\ndouble, default: 0.5\n\n\n--fpr\nTarget false positive rate in (0, 1). A false positive is a true signal count that is erroneously removed. More background removal is accompanied by more signal removal at high values of FPR. You can specify multiple values, which will create multiple output files.\ndouble, default: 0.01\n\n\n--exclude_antibody_capture\nIncluding the flag –exclude-antibody-capture will cause remove-background to operate on gene counts only, ignoring other features.\nboolean_true\n\n\n--learning_rate\nTraining detail: lower learning rate for inference. A OneCycle learning rate schedule is used, where the upper learning rate is ten times this value. (For this value, probably do not exceed 1e-3).\ndouble, example: 1e-04\n\n\n--cuda\nIncluding the flag –cuda will run the inference on a GPU.\nboolean_true" + }, + { + "objectID": "components/modules/filter/remove_modality.html", + "href": "components/modules/filter/remove_modality.html", + "title": "Remove modality", + "section": "", + "text": "ID: remove_modality\nNamespace: filter\n\n\n\nSource" + }, + { + "objectID": "components/modules/filter/remove_modality.html#example-commands", + "href": "components/modules/filter/remove_modality.html#example-commands", + "title": "Remove modality", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/filter/remove_modality/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: # please fill in - example: [\"foo\"]\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/filter/remove_modality/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/filter/remove_modality.html#argument-group", + "href": "components/modules/filter/remove_modality.html#argument-group", + "title": "Remove modality", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, required\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/filter/remove_modality.html#authors", + "href": "components/modules/filter/remove_modality.html#authors", + "title": "Remove modality", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/filter/filter_with_scrublet.html", + "href": "components/modules/filter/filter_with_scrublet.html", + "title": "Filter with scrublet", + "section": "", + "text": "ID: filter_with_scrublet\nNamespace: filter\n\n\n\nSource\nThe method tests for potential doublets by using the expression profiles of cells to generate synthetic potential doubles which are tested against cells. The method returns a “doublet score” on which it calls for potential doublets.\nFor the source code please visit https://github.com/AllonKleinLab/scrublet.\nFor 10x we expect the doublet rates to be: Multiplet Rate (%) - # of Cells Loaded - # of Cells Recovered ~0.4% ~800 ~500 ~0.8% ~1,600 ~1,000 ~1.6% ~3,200 ~2,000 ~2.3% ~4,800 ~3,000 ~3.1% ~6,400 ~4,000 ~3.9% ~8,000 ~5,000 ~4.6% ~9,600 ~6,000 ~5.4% ~11,200 ~7,000 ~6.1% ~12,800 ~8,000 ~6.9% ~14,400 ~9,000 ~7.6% ~16,000 ~10,000" + }, + { + "objectID": "components/modules/filter/filter_with_scrublet.html#example-commands", + "href": "components/modules/filter/filter_with_scrublet.html#example-commands", + "title": "Filter with scrublet", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/filter/filter_with_scrublet/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nobs_name_filter: \"filter_with_scrublet\"\ndo_subset: false\nobs_name_doublet_score: \"scrublet_doublet_score\"\nmin_counts: 2\nmin_cells: 3\nmin_gene_variablity_percent: 85\nnum_pca_components: 30\ndistance_metric: \"euclidean\"\nallow_automatic_threshold_detection_fail: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/filter/filter_with_scrublet/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/filter/filter_with_scrublet.html#argument-group", + "href": "components/modules/filter/filter_with_scrublet.html#argument-group", + "title": "Filter with scrublet", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--obs_name_filter\nIn which .obs slot to store a boolean array corresponding to which observations should be filtered out.\nstring, default: \"filter_with_scrublet\"\n\n\n--do_subset\nWhether to subset before storing the output.\nboolean_true\n\n\n--obs_name_doublet_score\nName of the doublet scores column in the obs slot of the returned object.\nstring, default: \"scrublet_doublet_score\"\n\n\n--min_counts\nThe number of minimal UMI counts per cell that have to be present for initial cell detection.\ninteger, default: 2\n\n\n--min_cells\nThe number of cells in which UMIs for a gene were detected.\ninteger, default: 3\n\n\n--min_gene_variablity_percent\nUsed for gene filtering prior to PCA. Keep the most highly variable genes (in the top min_gene_variability_pctl percentile), as measured by the v-statistic [Klein et al., Cell 2015].\ndouble, default: 85\n\n\n--num_pca_components\nNumber of principal components to use during PCA dimensionality reduction.\ninteger, default: 30\n\n\n--distance_metric\nThe distance metric used for computing similarities.\nstring, default: \"euclidean\"\n\n\n--allow_automatic_threshold_detection_fail\nWhen scrublet fails to automatically determine the double score threshold, allow the component to continue and set the output columns to NA.\nboolean_true" + }, + { + "objectID": "components/modules/filter/filter_with_scrublet.html#authors", + "href": "components/modules/filter/filter_with_scrublet.html#authors", + "title": "Filter with scrublet", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (contributor)\nRobrecht Cannoodt (maintainer, contributor)" + }, + { + "objectID": "components/modules/filter/filter_with_counts.html", + "href": "components/modules/filter/filter_with_counts.html", + "title": "Filter with counts", + "section": "", + "text": "ID: filter_with_counts\nNamespace: filter\n\n\n\nSource\nThis is based on both the UMI counts, the gene counts and the mitochondrial genes (genes starting with mt/MT)" + }, + { + "objectID": "components/modules/filter/filter_with_counts.html#example-commands", + "href": "components/modules/filter/filter_with_counts.html#example-commands", + "title": "Filter with counts", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/filter/filter_with_counts/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# layer: \"raw_counts\"\n# var_gene_names: \"gene_symbol\"\nmitochondrial_gene_regex: \"^[mM][tT]-\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\ndo_subset: false\nobs_name_filter: \"filter_with_counts\"\nvar_name_filter: \"filter_with_counts\"\n# var_name_mitochondrial_genes: \"foo\"\n\n# Arguments\n# min_counts: 200\n# max_counts: 5000000\n# min_genes_per_cell: 200\n# max_genes_per_cell: 1500000\n# min_cells_per_gene: 3\n# min_fraction_mito: 0\n# max_fraction_mito: 0.2\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/filter/filter_with_counts/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/filter/filter_with_counts.html#argument-groups", + "href": "components/modules/filter/filter_with_counts.html#argument-groups", + "title": "Filter with counts", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--layer\n\nstring, example: \"raw_counts\"\n\n\n--var_gene_names\n.var column name to be used to detect mitochondrial genes instead of .var_names (default if not set). Gene names matching with the regex value from –mitochondrial_gene_regex will be identified as a mitochondrial gene.\nstring, example: \"gene_symbol\"\n\n\n--mitochondrial_gene_regex\nRegex string that identifies mitochondrial genes from –var_gene_names. By default will detect human and mouse mitochondrial genes from a gene symbol.\nstring, default: \"^[mM][tT]-\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--do_subset\nWhether to subset before storing the output.\nboolean_true\n\n\n--obs_name_filter\nIn which .obs slot to store a boolean array corresponding to which observations should be removed.\nstring, default: \"filter_with_counts\"\n\n\n--var_name_filter\nIn which .var slot to store a boolean array corresponding to which variables should be removed.\nstring, default: \"filter_with_counts\"\n\n\n--var_name_mitochondrial_genes\nIn which .var slot to store a boolean array corresponding the mitochondrial genes. Will only be used if –min_fraction_mito or –max_fraction_mito are specified.\nstring\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--min_counts\nMinimum number of counts captured per cell.\ninteger, example: 200\n\n\n--max_counts\nMaximum number of counts captured per cell.\ninteger, example: 5000000\n\n\n--min_genes_per_cell\nMinimum of non-zero values per cell.\ninteger, example: 200\n\n\n--max_genes_per_cell\nMaximum of non-zero values per cell.\ninteger, example: 1500000\n\n\n--min_cells_per_gene\nMinimum of non-zero values per gene.\ninteger, example: 3\n\n\n--min_fraction_mito\nMinimum fraction of UMIs that are mitochondrial.\ndouble, example: 0\n\n\n--max_fraction_mito\nMaximum fraction of UMIs that are mitochondrial.\ndouble, example: 0.2" + }, + { + "objectID": "components/modules/filter/filter_with_counts.html#authors", + "href": "components/modules/filter/filter_with_counts.html#authors", + "title": "Filter with counts", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (author)\nRobrecht Cannoodt (maintainer, author)" + }, + { + "objectID": "components/modules/dimred/pca.html", + "href": "components/modules/dimred/pca.html", + "title": "Pca", + "section": "", + "text": "ID: pca\nNamespace: dimred\n\n\n\nSource\nUses the implementation of scikit-learn [Pedregosa11]" + }, + { + "objectID": "components/modules/dimred/pca.html#example-commands", + "href": "components/modules/dimred/pca.html#example-commands", + "title": "Pca", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/dimred/pca/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# layer: \"foo\"\n# var_input: \"filter_with_hvg\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nobsm_output: \"X_pca\"\nvarm_output: \"pca_loadings\"\nuns_output: \"pca_variance\"\n# num_components: 25\noverwrite: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/dimred/pca/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/dimred/pca.html#argument-group", + "href": "components/modules/dimred/pca.html#argument-group", + "title": "Pca", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--layer\nUse specified layer for expression values instead of the .X object from the modality.\nstring\n\n\n--var_input\nColumn name in .var matrix that will be used to select which genes to run the PCA on.\nstring, example: \"filter_with_hvg\"\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--obsm_output\nIn which .obsm slot to store the resulting embedding.\nstring, default: \"X_pca\"\n\n\n--varm_output\nIn which .varm slot to store the resulting loadings matrix.\nstring, default: \"pca_loadings\"\n\n\n--uns_output\nIn which .uns slot to store the resulting variance objects.\nstring, default: \"pca_variance\"\n\n\n--num_components\nNumber of principal components to compute. Defaults to 50, or 1 - minimum dimension size of selected representation.\ninteger, example: 25\n\n\n--overwrite\nAllow overwriting .obsm, .varm and .uns slots.\nboolean_true" + }, + { + "objectID": "components/modules/dimred/pca.html#authors", + "href": "components/modules/dimred/pca.html#authors", + "title": "Pca", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)" + }, + { + "objectID": "components/modules/reference/make_reference.html", + "href": "components/modules/reference/make_reference.html", + "title": "Make reference", + "section": "", + "text": "ID: make_reference\nNamespace: reference\n\n\n\nSource\nExample input files are: - genome_fasta: https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/GRCh38.primary_assembly.genome.fa.gz - transcriptome_gtf: https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/gencode.v41.annotation.gtf.gz - ercc: https://assets.thermofisher.com/TFS-Assets/LSG/manuals/ERCC92.zip" + }, + { + "objectID": "components/modules/reference/make_reference.html#example-commands", + "href": "components/modules/reference/make_reference.html#example-commands", + "title": "Make reference", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/reference/make_reference/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ngenome_fasta: # please fill in - example: \"genome_fasta.fa.gz\"\ntranscriptome_gtf: # please fill in - example: \"transcriptome.gtf.gz\"\n# ercc: \"ercc.zip\"\n# subset_regex: \"(ERCC-00002|chr1)\"\n# output_fasta: \"$id.$key.output_fasta.gz\"\n# output_gtf: \"$id.$key.output_gtf.gz\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/reference/make_reference/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/reference/make_reference.html#argument-group", + "href": "components/modules/reference/make_reference.html#argument-group", + "title": "Make reference", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genome_fasta\nReference genome fasta. Example:\nfile, required, example: \"genome_fasta.fa.gz\"\n\n\n--transcriptome_gtf\nReference transcriptome annotation.\nfile, required, example: \"transcriptome.gtf.gz\"\n\n\n--ercc\nERCC sequence and annotation file.\nfile, example: \"ercc.zip\"\n\n\n--subset_regex\nWill subset the reference chromosomes using the given regex.\nstring, example: \"(ERCC-00002|chr1)\"\n\n\n--output_fasta\nOutput genome sequence fasta.\nfile, required, example: \"genome_sequence.fa.gz\"\n\n\n--output_gtf\nOutput transcriptome annotation gtf.\nfile, required, example: \"transcriptome_annotation.gtf.gz\"" + }, + { + "objectID": "components/modules/reference/make_reference.html#authors", + "href": "components/modules/reference/make_reference.html#authors", + "title": "Make reference", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/reference/build_cellranger_reference.html", + "href": "components/modules/reference/build_cellranger_reference.html", + "title": "Build cellranger reference", + "section": "", + "text": "ID: build_cellranger_reference\nNamespace: reference\n\n\n\nSource\nCreates a new folder named after the genome." + }, + { + "objectID": "components/modules/reference/build_cellranger_reference.html#example-commands", + "href": "components/modules/reference/build_cellranger_reference.html#example-commands", + "title": "Build cellranger reference", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/reference/build_cellranger_reference/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ngenome_fasta: # please fill in - example: \"genome_sequence.fa.gz\"\ntranscriptome_gtf: # please fill in - example: \"transcriptome_annotation.gtf.gz\"\n# output: \"$id.$key.output.output\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/reference/build_cellranger_reference/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/reference/build_cellranger_reference.html#argument-group", + "href": "components/modules/reference/build_cellranger_reference.html#argument-group", + "title": "Build cellranger reference", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genome_fasta\nReference genome fasta.\nfile, required, example: \"genome_sequence.fa.gz\"\n\n\n--transcriptome_gtf\nReference transcriptome annotation.\nfile, required, example: \"transcriptome_annotation.gtf.gz\"\n\n\n--output\nOutput folder\nfile, required, example: \"cellranger_reference\"" + }, + { + "objectID": "components/modules/reference/build_cellranger_reference.html#authors", + "href": "components/modules/reference/build_cellranger_reference.html#authors", + "title": "Build cellranger reference", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/integrate/scanorama.html", + "href": "components/modules/integrate/scanorama.html", + "title": "Scanorama", + "section": "", + "text": "ID: scanorama\nNamespace: integrate\n\n\n\nSource" + }, + { + "objectID": "components/modules/integrate/scanorama.html#example-commands", + "href": "components/modules/integrate/scanorama.html#example-commands", + "title": "Scanorama", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/integrate/scanorama/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"path/to/file\"\nmodality: \"rna\"\n# output: \"$id.$key.output.h5ad\"\n# output_compression: \"gzip\"\nobs_batch: \"batch\"\nobsm_input: \"X_pca\"\nobsm_output: \"X_scanorama\"\nknn: 20\nbatch_size: 5000\nsigma: 15\napprox: true\nalpha: 0.1\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/integrate/scanorama/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/integrate/scanorama.html#argument-group", + "href": "components/modules/integrate/scanorama.html#argument-group", + "title": "Scanorama", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--output\nOutput .h5mu file\nfile, required, default: \"output.h5ad\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--obs_batch\nColumn name discriminating between your batches.\nstring, default: \"batch\"\n\n\n--obsm_input\nBasis obsm slot to run scanorama on.\nstring, default: \"X_pca\"\n\n\n--obsm_output\nThe name of the field in adata.obsm where the integrated embeddings will be stored after running this function. Defaults to X_scanorama.\nstring, default: \"X_scanorama\"\n\n\n--knn\nNumber of nearest neighbors to use for matching.\ninteger, default: 20\n\n\n--batch_size\nThe batch size used in the alignment vector computation. Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory.\ninteger, default: 5000\n\n\n--sigma\nCorrection smoothing parameter on Gaussian kernel.\ndouble, default: 15\n\n\n--approx\nUse approximate nearest neighbors with Python annoy; greatly speeds up matching runtime.\nboolean, default: TRUE\n\n\n--alpha\nAlignment score minimum cutoff\ndouble, default: 0.1" + }, + { + "objectID": "components/modules/integrate/scanorama.html#authors", + "href": "components/modules/integrate/scanorama.html#authors", + "title": "Scanorama", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (author)\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/integrate/scarches.html", + "href": "components/modules/integrate/scarches.html", + "title": "Scarches", + "section": "", + "text": "ID: scarches\nNamespace: integrate\n\n\n\nSource" + }, + { + "objectID": "components/modules/integrate/scarches.html#example-commands", + "href": "components/modules/integrate/scarches.html#example-commands", + "title": "Scarches", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/integrate/scarches/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"path/to/file\"\nmodality: \"rna\"\nreference: # please fill in - example: \"path/to/file\"\ndataset_name: \"test_dataset\"\n\n# Outputs\n# output: \"$id.$key.output.output\"\n# output_compression: \"gzip\"\n# model_output: \"$id.$key.model_output.model_output\"\nobsm_output: \"X_integrated_scanvi\"\n\n# Early stopping arguments\n# early_stopping: true\nearly_stopping_monitor: \"elbo_validation\"\nearly_stopping_patience: 45\nearly_stopping_min_delta: 0.0\n\n# Learning parameters\nmax_epochs: # please fill in - example: 123\nreduce_lr_on_plateau: true\nlr_factor: 0.6\nlr_patience: 30\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/integrate/scarches/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/integrate/scarches.html#argument-groups", + "href": "components/modules/integrate/scarches.html#argument-groups", + "title": "Scarches", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file to use as a query\nfile, required\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--reference\nPath to the directory with reference model or a web link. For HLCA use https://zenodo.org/record/6337966/files/HLCA_reference_model.zip\nfile, required\n\n\n--dataset_name\nName of query dataset to use as a batch name. If not set, name of the input file is used\nstring, default: \"test_dataset\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--model_output\nOutput directory for model\nfile, default: \"model\"\n\n\n--obsm_output\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_integrated_scanvi\"\n\n\n\n\n\nEarly stopping arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--early_stopping\nWhether to perform early stopping with respect to the validation set.\nboolean\n\n\n--early_stopping_monitor\nMetric logged during validation set epoch.\nstring, default: \"elbo_validation\"\n\n\n--early_stopping_patience\nNumber of validation epochs with no improvement after which training will be stopped.\ninteger, default: 45\n\n\n--early_stopping_min_delta\nMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.\ndouble, default: 0\n\n\n\n\n\nLearning parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--max_epochs\nNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.\ninteger, required\n\n\n--reduce_lr_on_plateau\nWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.\nboolean, default: TRUE\n\n\n--lr_factor\nFactor to reduce learning rate.\ndouble, default: 0.6\n\n\n--lr_patience\nNumber of epochs with no improvement after which learning rate will be reduced.\ndouble, default: 30" + }, + { + "objectID": "components/modules/integrate/scarches.html#authors", + "href": "components/modules/integrate/scarches.html#authors", + "title": "Scarches", + "section": "Authors", + "text": "Authors\n\nVladimir Shitov" + }, + { + "objectID": "components/modules/integrate/harmonypy.html", + "href": "components/modules/integrate/harmonypy.html", + "title": "Harmonypy", + "section": "", + "text": "ID: harmonypy\nNamespace: integrate\n\n\n\nSource\nBased on an implementation in python from https://github.com/slowkow/harmonypy" + }, + { + "objectID": "components/modules/integrate/harmonypy.html#example-commands", + "href": "components/modules/integrate/harmonypy.html#example-commands", + "title": "Harmonypy", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/integrate/harmonypy/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"path/to/file\"\n# output: \"$id.$key.output.output\"\n# output_compression: \"gzip\"\nmodality: \"rna\"\nobsm_input: \"X_pca\"\nobsm_output: \"X_pca_integrated\"\ntheta: [2]\nobs_covariates: # please fill in - example: [\"batch\", \"sample\"]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/integrate/harmonypy/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/integrate/harmonypy.html#argument-group", + "href": "components/modules/integrate/harmonypy.html#argument-group", + "title": "Harmonypy", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required\n\n\n--output\nOutput h5mu file.\nfile, required\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--obsm_input\nWhich .obsm slot to use as a starting PCA embedding.\nstring, default: \"X_pca\"\n\n\n--obsm_output\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_pca_integrated\"\n\n\n--theta\nDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.\ndouble, default: 2\n\n\n--obs_covariates\nThe .obs field(s) that define the covariate(s) to regress out.\nstring, required, example: \"batch\", example: \"sample\"" + }, + { + "objectID": "components/modules/integrate/harmonypy.html#authors", + "href": "components/modules/integrate/harmonypy.html#authors", + "title": "Harmonypy", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)\nRobrecht Cannoodt (contributor)" + }, + { + "objectID": "components/modules/mapping/multi_star_to_h5mu.html", + "href": "components/modules/mapping/multi_star_to_h5mu.html", + "title": "Multi star to h5mu", + "section": "", + "text": "ID: multi_star_to_h5mu\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/multi_star_to_h5mu.html#example-commands", + "href": "components/modules/mapping/multi_star_to_h5mu.html#example-commands", + "title": "Multi star to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/multi_star_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"/path/to/foo\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/multi_star_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/multi_star_to_h5mu.html#argument-group", + "href": "components/modules/mapping/multi_star_to_h5mu.html#argument-group", + "title": "Multi star to h5mu", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nThe directory created by multi_star\nfile, required, example: \"/path/to/foo\"\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/mapping/multi_star_to_h5mu.html#authors", + "href": "components/modules/mapping/multi_star_to_h5mu.html#authors", + "title": "Multi star to h5mu", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (author, maintainer)\nAngela Oliveira Pisco (author)" + }, + { + "objectID": "components/modules/mapping/multi_star.html", + "href": "components/modules/mapping/multi_star.html", + "title": "Multi star", + "section": "", + "text": "ID: multi_star\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/multi_star.html#example-commands", + "href": "components/modules/mapping/multi_star.html#example-commands", + "title": "Multi star", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/multi_star/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Input/Output\ninput_id: # please fill in - example: [\"mysample\", \"mysample\"]\ninput_r1: # please fill in - example: [\"mysample_S1_L001_R1_001.fastq.gz\", \"mysample_S1_L002_R1_001.fastq.gz\"]\n# input_r2: [\"mysample_S1_L001_R2_001.fastq.gz\", \"mysample_S1_L002_R2_001.fastq.gz\"]\nreference_index: # please fill in - example: \"/path/to/reference\"\nreference_gtf: # please fill in - example: \"genes.gtf\"\n# output: \"$id.$key.output.output\"\n\n# Processing arguments\nrun_htseq_count: true\nrun_multiqc: true\nmin_success_rate: 0.5\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/multi_star/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/multi_star.html#argument-groups", + "href": "components/modules/mapping/multi_star.html#argument-groups", + "title": "Multi star", + "section": "Argument groups", + "text": "Argument groups\n\nInput/Output\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input_id\nThe ID of the sample being processed. This vector should have the same length as the --input_r1 argument.\nstring, required, example: \"mysample\", example: \"mysample\"\n\n\n--input_r1\nPaths to the sequences to be mapped. If using Illumina paired-end reads, only the R1 files should be passed.\nfile, required, example: \"mysample_S1_L001_R1_001.fastq.gz\", example: \"mysample_S1_L002_R1_001.fastq.gz\"\n\n\n--input_r2\nPaths to the sequences to be mapped. If using Illumina paired-end reads, only the R2 files should be passed.\nfile, example: \"mysample_S1_L001_R2_001.fastq.gz\", example: \"mysample_S1_L002_R2_001.fastq.gz\"\n\n\n--reference_index\nPath to the reference built by star_build_reference. Corresponds to the –genomeDir argument in the STAR command.\nfile, required, example: \"/path/to/reference\"\n\n\n--reference_gtf\nPath to the gtf reference file.\nfile, required, example: \"genes.gtf\"\n\n\n--output\nPath to output directory. Corresponds to the –outFileNamePrefix argument in the STAR command.\nfile, required, example: \"/path/to/foo\"\n\n\n\n\n\nProcessing arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--run_htseq_count\nWhether or not to also run htseq-count after STAR.\nboolean, default: TRUE\n\n\n--run_multiqc\nWhether or not to also run MultiQC at the end.\nboolean, default: TRUE\n\n\n--min_success_rate\nFail when the success rate is below this threshold.\ndouble, default: 0.5\n\n\n\n\n\nRun Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--runRNGseed\nrandom number generator seed.\ninteger, example: 777\n\n\n\n\n\nGenome Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genomeFastaFiles\npath(s) to the fasta files with the genome sequences, separated by spaces. These files should be plain text FASTA files, they cannot be zipped. Required for the genome generation (–runMode genomeGenerate). Can also be used in the mapping (–runMode alignReads) to add extra (new) sequences to the genome (e.g. spike-ins).\nfile\n\n\n\n\n\nSplice Junctions Database\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--sjdbFileChrStartEnd\npath to the files with genomic coordinates (chr start end strand) for the splice junction introns. Multiple files can be supplied and will be concatenated.\nstring\n\n\n--sjdbGTFfile\npath to the GTF file with annotations\nfile\n\n\n--sjdbGTFchrPrefix\nprefix for chromosome names in a GTF file (e.g. ‘chr’ for using ENSMEBL annotations with UCSC genomes)\nstring\n\n\n--sjdbGTFfeatureExon\nfeature type in GTF file to be used as exons for building transcripts\nstring, example: \"exon\"\n\n\n--sjdbGTFtagExonParentTranscript\nGTF attribute name for parent transcript ID (default “transcript_id” works for GTF files)\nstring, example: \"transcript_id\"\n\n\n--sjdbGTFtagExonParentGene\nGTF attribute name for parent gene ID (default “gene_id” works for GTF files)\nstring, example: \"gene_id\"\n\n\n--sjdbGTFtagExonParentGeneName\nGTF attribute name for parent gene name\nstring, example: \"gene_name\"\n\n\n--sjdbGTFtagExonParentGeneType\nGTF attribute name for parent gene type\nstring, example: \"gene_type\", example: \"gene_biotype\"\n\n\n--sjdbOverhang\nlength of the donor/acceptor sequence on each side of the junctions, ideally = (mate_length - 1)\ninteger, example: 100\n\n\n--sjdbScore\nextra alignment score for alignments that cross database junctions\ninteger, example: 2\n\n\n--sjdbInsertSave\nwhich files to save when sjdb junctions are inserted on the fly at the mapping step - Basic … only small junction / transcript files - All … all files including big Genome, SA and SAindex - this will create a complete genome directory\nstring, example: \"Basic\"\n\n\n\n\n\nVariation parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--varVCFfile\npath to the VCF file that contains variation data. The 10th column should contain the genotype information, e.g. 0/1\nstring\n\n\n\n\n\nRead Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--readFilesType\nformat of input read files - Fastx … FASTA or FASTQ - SAM SE … SAM or BAM single-end reads; for BAM use –readFilesCommand samtools view - SAM PE … SAM or BAM paired-end reads; for BAM use –readFilesCommand samtools view\nstring, example: \"Fastx\"\n\n\n--readFilesSAMattrKeep\nfor –readFilesType SAM SE/PE, which SAM tags to keep in the output BAM, e.g.: –readFilesSAMtagsKeep RG PL - All … keep all tags - None … do not keep any tags\nstring, example: \"All\"\n\n\n--readFilesManifest\npath to the “manifest” file with the names of read files. The manifest file should contain 3 tab-separated columns: paired-end reads: read1_file_name \\(tab\\) read2_file_name \\(tab\\) read_group_line. single-end reads: read1_file_name \\(tab\\) - \\(tab\\) read_group_line. Spaces, but not tabs are allowed in file names. If read_group_line does not start with ID:, it can only contain one ID field, and ID: will be added to it. If read_group_line starts with ID:, it can contain several fields separated by \\(tab\\), and all fields will be be copied verbatim into SAM @RG header line.\nfile\n\n\n--readFilesPrefix\nprefix for the read files names, i.e. it will be added in front of the strings in –readFilesIn\nstring\n\n\n--readFilesCommand\ncommand line to execute for each of the input file. This command should generate FASTA or FASTQ text and send it to stdout For example: zcat - to uncompress .gz files, bzcat - to uncompress .bz2 files, etc.\nstring\n\n\n--readMapNumber\nnumber of reads to map from the beginning of the file -1: map all reads\ninteger, example: -1\n\n\n--readMatesLengthsIn\nEqual/NotEqual - lengths of names,sequences,qualities for both mates are the same / not the same. NotEqual is safe in all situations.\nstring, example: \"NotEqual\"\n\n\n--readNameSeparator\ncharacter(s) separating the part of the read names that will be trimmed in output (read name after space is always trimmed)\nstring, example: \"/\"\n\n\n--readQualityScoreBase\nnumber to be subtracted from the ASCII code to get Phred quality score\ninteger, example: 33\n\n\n\n\n\nRead Clipping\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--clipAdapterType\nadapter clipping type - Hamming … adapter clipping based on Hamming distance, with the number of mismatches controlled by –clip5pAdapterMMp - CellRanger4 … 5p and 3p adapter clipping similar to CellRanger4. Utilizes Opal package by Martin Sosic: https://github.com/Martinsos/opal - None … no adapter clipping, all other clip* parameters are disregarded\nstring, example: \"Hamming\"\n\n\n--clip3pNbases\nnumber(s) of bases to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n--clip3pAdapterSeq\nadapter sequences to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates. - polyA … polyA sequence with the length equal to read length\nstring\n\n\n--clip3pAdapterMMp\nmax proportion of mismatches for 3p adapter clipping for each mate. If one value is given, it will be assumed the same for both mates.\ndouble, example: 0.1\n\n\n--clip3pAfterAdapterNbases\nnumber of bases to clip from 3p of each mate after the adapter clipping. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n--clip5pNbases\nnumber(s) of bases to clip from 5p of each mate. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n\n\n\nLimits\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--limitGenomeGenerateRAM\nmaximum available RAM (bytes) for genome generation\nlong, example: NA\n\n\n--limitIObufferSize\nmax available buffers size (bytes) for input/output, per thread\nlong, example: 30000000, example: 50000000\n\n\n--limitOutSAMoneReadBytes\nmax size of the SAM record (bytes) for one read. Recommended value: >(2(LengthMate1+LengthMate2+100)outFilterMultimapNmax\nlong, example: 100000\n\n\n--limitOutSJoneRead\nmax number of junctions for one read (including all multi-mappers)\ninteger, example: 1000\n\n\n--limitOutSJcollapsed\nmax number of collapsed junctions\ninteger, example: 1000000\n\n\n--limitBAMsortRAM\nmaximum available RAM (bytes) for sorting BAM. If =0, it will be set to the genome index size. 0 value can only be used with –genomeLoad NoSharedMemory option.\nlong, example: 0\n\n\n--limitSjdbInsertNsj\nmaximum number of junctions to be inserted to the genome on the fly at the mapping stage, including those from annotations and those detected in the 1st step of the 2-pass run\ninteger, example: 1000000\n\n\n--limitNreadsSoft\nsoft limit on the number of reads\ninteger, example: -1\n\n\n\n\n\nOutput: general\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outTmpKeep\nwhether to keep the temporary files after STAR runs is finished - None … remove all temporary files - All … keep all files\nstring\n\n\n--outStd\nwhich output will be directed to stdout (standard out) - Log … log messages - SAM … alignments in SAM format (which normally are output to Aligned.out.sam file), normal standard output will go into Log.std.out - BAM_Unsorted … alignments in BAM format, unsorted. Requires –outSAMtype BAM Unsorted - BAM_SortedByCoordinate … alignments in BAM format, sorted by coordinate. Requires –outSAMtype BAM SortedByCoordinate - BAM_Quant … alignments to transcriptome in BAM format, unsorted. Requires –quantMode TranscriptomeSAM\nstring, example: \"Log\"\n\n\n--outReadsUnmapped\noutput of unmapped and partially mapped (i.e. mapped only one mate of a paired end read) reads in separate file(s). - None … no output - Fastx … output in separate fasta/fastq files, Unmapped.out.mate1/2\nstring\n\n\n--outQSconversionAdd\nadd this number to the quality score (e.g. to convert from Illumina to Sanger, use -31)\ninteger, example: 0\n\n\n--outMultimapperOrder\norder of multimapping alignments in the output files - Old_2.4 … quasi-random order used before 2.5.0 - Random … random order of alignments for each multi-mapper. Read mates (pairs) are always adjacent, all alignment for each read stay together. This option will become default in the future releases.\nstring, example: \"Old_2.4\"\n\n\n\n\n\nOutput: SAM and BAM\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSAMmode\nmode of SAM output - None … no SAM output - Full … full SAM output - NoQS … full SAM but without quality scores\nstring, example: \"Full\"\n\n\n--outSAMstrandField\nCufflinks-like strand field flag - None … not used - intronMotif … strand derived from the intron motif. This option changes the output alignments: reads with inconsistent and/or non-canonical introns are filtered out.\nstring\n\n\n--outSAMattributes\na string of desired SAM attributes, in the order desired for the output SAM. Tags can be listed in any combination/order. Presets: - None … no attributes - Standard … NH HI AS nM - All … NH HI AS nM NM MD jM jI MC ch Alignment: - NH … number of loci the reads maps to: =1 for unique mappers, >1 for multimappers. Standard SAM tag. - HI … multiple alignment index, starts with –outSAMattrIHstart (=1 by default). Standard SAM tag. - AS … local alignment score, +1/-1 for matches/mismateches, score* penalties for indels and gaps. For PE reads, total score for two mates. Stadnard SAM tag. - nM … number of mismatches. For PE reads, sum over two mates. - NM … edit distance to the reference (number of mismatched + inserted + deleted bases) for each mate. Standard SAM tag. - MD … string encoding mismatched and deleted reference bases (see standard SAM specifications). Standard SAM tag. - jM … intron motifs for all junctions (i.e. N in CIGAR): 0: non-canonical; 1: GT/AG, 2: CT/AC, 3: GC/AG, 4: CT/GC, 5: AT/AC, 6: GT/AT. If splice junctions database is used, and a junction is annotated, 20 is added to its motif value. - jI … start and end of introns for all junctions (1-based). - XS … alignment strand according to –outSAMstrandField. - MC … mate’s CIGAR string. Standard SAM tag. - ch … marks all segment of all chimeric alingments for –chimOutType WithinBAM output. - cN … number of bases clipped from the read ends: 5’ and 3’ Variation: - vA … variant allele - vG … genomic coordinate of the variant overlapped by the read. - vW … 1 - alignment passes WASP filtering; 2,3,4,5,6,7 - alignment does not pass WASP filtering. Requires –waspOutputMode SAMtag. STARsolo: - CR CY UR UY … sequences and quality scores of cell barcodes and UMIs for the solo* demultiplexing. - GX GN … gene ID and gene name for unique-gene reads. - gx gn … gene IDs and gene names for unique- and multi-gene reads. - CB UB … error-corrected cell barcodes and UMIs for solo* demultiplexing. Requires –outSAMtype BAM SortedByCoordinate. - sM … assessment of CB and UMI. - sS … sequence of the entire barcode (CB,UMI,adapter). - sQ … quality of the entire barcode. ***Unsupported/undocumented: - ha … haplotype (1/2) when mapping to the diploid genome. Requires genome generated with –genomeTransformType Diploid . - rB … alignment block read/genomic coordinates. - vR … read coordinate of the variant.\nstring, example: \"Standard\"\n\n\n--outSAMattrIHstart\nstart value for the IH attribute. 0 may be required by some downstream software, such as Cufflinks or StringTie.\ninteger, example: 1\n\n\n--outSAMunmapped\noutput of unmapped reads in the SAM format 1st word: - None … no output - Within … output unmapped reads within the main SAM file (i.e. Aligned.out.sam) 2nd word: - KeepPairs … record unmapped mate for each alignment, and, in case of unsorted output, keep it adjacent to its mapped mate. Only affects multi-mapping reads.\nstring\n\n\n--outSAMorder\ntype of sorting for the SAM output Paired: one mate after the other for all paired alignments PairedKeepInputOrder: one mate after the other for all paired alignments, the order is kept the same as in the input FASTQ files\nstring, example: \"Paired\"\n\n\n--outSAMprimaryFlag\nwhich alignments are considered primary - all others will be marked with 0x100 bit in the FLAG - OneBestScore … only one alignment with the best score is primary - AllBestScore … all alignments with the best score are primary\nstring, example: \"OneBestScore\"\n\n\n--outSAMreadID\nread ID record type - Standard … first word (until space) from the FASTx read ID line, removing /1,/2 from the end - Number … read number (index) in the FASTx file\nstring, example: \"Standard\"\n\n\n--outSAMmapqUnique\n0 to 255: the MAPQ value for unique mappers\ninteger, example: 255\n\n\n--outSAMflagOR\n0 to 65535: sam FLAG will be bitwise OR’d with this value, i.e. FLAG=FLAG | outSAMflagOR. This is applied after all flags have been set by STAR, and after outSAMflagAND. Can be used to set specific bits that are not set otherwise.\ninteger, example: 0\n\n\n--outSAMflagAND\n0 to 65535: sam FLAG will be bitwise AND’d with this value, i.e. FLAG=FLAG & outSAMflagOR. This is applied after all flags have been set by STAR, but before outSAMflagOR. Can be used to unset specific bits that are not set otherwise.\ninteger, example: 65535\n\n\n--outSAMattrRGline\nSAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”. xxx will be added as RG tag to each output alignment. Any spaces in the tag values have to be double quoted. Comma separated RG lines correspons to different (comma separated) input files in –readFilesIn. Commas have to be surrounded by spaces, e.g. –outSAMattrRGline ID:xxx , ID:zzz “DS:z z” , ID:yyy DS:yyyy\nstring\n\n\n--outSAMheaderHD\n@HD (header) line of the SAM header\nstring\n\n\n--outSAMheaderPG\nextra @PG (software) line of the SAM header (in addition to STAR)\nstring\n\n\n--outSAMheaderCommentFile\npath to the file with @CO (comment) lines of the SAM header\nstring\n\n\n--outSAMfilter\nfilter the output into main SAM/BAM files - KeepOnlyAddedReferences … only keep the reads for which all alignments are to the extra reference sequences added with –genomeFastaFiles at the mapping stage. - KeepAllAddedReferences … keep all alignments to the extra reference sequences added with –genomeFastaFiles at the mapping stage.\nstring\n\n\n--outSAMmultNmax\nmax number of multiple alignments for a read that will be output to the SAM/BAM files. Note that if this value is not equal to -1, the top scoring alignment will be output first - -1 … all alignments (up to –outFilterMultimapNmax) will be output\ninteger, example: -1\n\n\n--outSAMtlen\ncalculation method for the TLEN field in the SAM/BAM files - 1 … leftmost base of the (+)strand mate to rightmost base of the (-)mate. (+)sign for the (+)strand mate - 2 … leftmost base of any mate to rightmost base of any mate. (+)sign for the mate with the leftmost base. This is different from 1 for overlapping mates with protruding ends\ninteger, example: 1\n\n\n--outBAMcompression\n-1 to 10 BAM compression level, -1=default compression (6?), 0=no compression, 10=maximum compression\ninteger, example: 1\n\n\n--outBAMsortingThreadN\n>=0: number of threads for BAM sorting. 0 will default to min(6,–runThreadN).\ninteger, example: 0\n\n\n--outBAMsortingBinsN\n>0: number of genome bins for coordinate-sorting\ninteger, example: 50\n\n\n\n\n\nBAM processing\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--bamRemoveDuplicatesType\nmark duplicates in the BAM file, for now only works with (i) sorted BAM fed with inputBAMfile, and (ii) for paired-end alignments only - - … no duplicate removal/marking - UniqueIdentical … mark all multimappers, and duplicate unique mappers. The coordinates, FLAG, CIGAR must be identical - UniqueIdenticalNotMulti … mark duplicate unique mappers but not multimappers.\nstring\n\n\n--bamRemoveDuplicatesMate2basesN\nnumber of bases from the 5’ of mate 2 to use in collapsing (e.g. for RAMPAGE)\ninteger, example: 0\n\n\n\n\n\nOutput Wiggle\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outWigType\ntype of signal output, e.g. “bedGraph” OR “bedGraph read1_5p”. Requires sorted BAM: –outSAMtype BAM SortedByCoordinate . 1st word: - None … no signal output - bedGraph … bedGraph format - wiggle … wiggle format 2nd word: - read1_5p … signal from only 5’ of the 1st read, useful for CAGE/RAMPAGE etc - read2 … signal from only 2nd read\nstring\n\n\n--outWigStrand\nstrandedness of wiggle/bedGraph output - Stranded … separate strands, str1 and str2 - Unstranded … collapsed strands\nstring, example: \"Stranded\"\n\n\n--outWigReferencesPrefix\nprefix matching reference names to include in the output wiggle file, e.g. “chr”, default “-” - include all references\nstring\n\n\n--outWigNorm\ntype of normalization for the signal - RPM … reads per million of mapped reads - None … no normalization, “raw” counts\nstring, example: \"RPM\"\n\n\n\n\n\nOutput Filtering\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outFilterType\ntype of filtering - Normal … standard filtering using only current alignment - BySJout … keep only those reads that contain junctions that passed filtering into SJ.out.tab\nstring, example: \"Normal\"\n\n\n--outFilterMultimapScoreRange\nthe score range below the maximum score for multimapping alignments\ninteger, example: 1\n\n\n--outFilterMultimapNmax\nmaximum number of loci the read is allowed to map to. Alignments (all of them) will be output only if the read maps to no more loci than this value. Otherwise no alignments will be output, and the read will be counted as “mapped to too many loci” in the Log.final.out .\ninteger, example: 10\n\n\n--outFilterMismatchNmax\nalignment will be output only if it has no more mismatches than this value.\ninteger, example: 10\n\n\n--outFilterMismatchNoverLmax\nalignment will be output only if its ratio of mismatches to mapped length is less than or equal to this value.\ndouble, example: 0.3\n\n\n--outFilterMismatchNoverReadLmax\nalignment will be output only if its ratio of mismatches to read length is less than or equal to this value.\ndouble, example: 1\n\n\n--outFilterScoreMin\nalignment will be output only if its score is higher than or equal to this value.\ninteger, example: 0\n\n\n--outFilterScoreMinOverLread\nsame as outFilterScoreMin, but normalized to read length (sum of mates’ lengths for paired-end reads)\ndouble, example: 0.66\n\n\n--outFilterMatchNmin\nalignment will be output only if the number of matched bases is higher than or equal to this value.\ninteger, example: 0\n\n\n--outFilterMatchNminOverLread\nsam as outFilterMatchNmin, but normalized to the read length (sum of mates’ lengths for paired-end reads).\ndouble, example: 0.66\n\n\n--outFilterIntronMotifs\nfilter alignment using their motifs - None … no filtering - RemoveNoncanonical … filter out alignments that contain non-canonical junctions - RemoveNoncanonicalUnannotated … filter out alignments that contain non-canonical unannotated junctions when using annotated splice junctions database. The annotated non-canonical junctions will be kept.\nstring\n\n\n--outFilterIntronStrands\nfilter alignments - RemoveInconsistentStrands … remove alignments that have junctions with inconsistent strands - None … no filtering\nstring, example: \"RemoveInconsistentStrands\"\n\n\n\n\n\nOutput splice junctions (SJ.out.tab)\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSJtype\ntype of splice junction output - Standard … standard SJ.out.tab output - None … no splice junction output\nstring, example: \"Standard\"\n\n\n\n\n\nOutput Filtering: Splice Junctions\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSJfilterReads\nwhich reads to consider for collapsed splice junctions output - All … all reads, unique- and multi-mappers - Unique … uniquely mapping reads only\nstring, example: \"All\"\n\n\n--outSJfilterOverhangMin\nminimum overhang length for splice junctions on both sides for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif does not apply to annotated junctions\ninteger, example: 30, example: 12, example: 12, example: 12\n\n\n--outSJfilterCountUniqueMin\nminimum uniquely mapping read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctions\ninteger, example: 3, example: 1, example: 1, example: 1\n\n\n--outSJfilterCountTotalMin\nminimum total (multi-mapping+unique) read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctions\ninteger, example: 3, example: 1, example: 1, example: 1\n\n\n--outSJfilterDistToOtherSJmin\nminimum allowed distance to other junctions’ donor/acceptor does not apply to annotated junctions\ninteger, example: 10, example: 0, example: 5, example: 10\n\n\n--outSJfilterIntronMaxVsReadN\nmaximum gap allowed for junctions supported by 1,2,3,,,N reads i.e. by default junctions supported by 1 read can have gaps <=50000b, by 2 reads: <=100000b, by 3 reads: <=200000. by >=4 reads any gap <=alignIntronMax does not apply to annotated junctions\ninteger, example: 50000, example: 100000, example: 200000\n\n\n\n\n\nScoring\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--scoreGap\nsplice junction penalty (independent on intron motif)\ninteger, example: 0\n\n\n--scoreGapNoncan\nnon-canonical junction penalty (in addition to scoreGap)\ninteger, example: -8\n\n\n--scoreGapGCAG\nGC/AG and CT/GC junction penalty (in addition to scoreGap)\ninteger, example: -4\n\n\n--scoreGapATAC\nAT/AC and GT/AT junction penalty (in addition to scoreGap)\ninteger, example: -8\n\n\n--scoreGenomicLengthLog2scale\nextra score logarithmically scaled with genomic length of the alignment: scoreGenomicLengthLog2scale*log2(genomicLength)\ninteger, example: 0\n\n\n--scoreDelOpen\ndeletion open penalty\ninteger, example: -2\n\n\n--scoreDelBase\ndeletion extension penalty per base (in addition to scoreDelOpen)\ninteger, example: -2\n\n\n--scoreInsOpen\ninsertion open penalty\ninteger, example: -2\n\n\n--scoreInsBase\ninsertion extension penalty per base (in addition to scoreInsOpen)\ninteger, example: -2\n\n\n--scoreStitchSJshift\nmaximum score reduction while searching for SJ boundaries in the stitching step\ninteger, example: 1\n\n\n\n\n\nAlignments and Seeding\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--seedSearchStartLmax\ndefines the search start point through the read - the read is split into pieces no longer than this value\ninteger, example: 50\n\n\n--seedSearchStartLmaxOverLread\nseedSearchStartLmax normalized to read length (sum of mates’ lengths for paired-end reads)\ndouble, example: 1\n\n\n--seedSearchLmax\ndefines the maximum length of the seeds, if =0 seed length is not limited\ninteger, example: 0\n\n\n--seedMultimapNmax\nonly pieces that map fewer than this value are utilized in the stitching procedure\ninteger, example: 10000\n\n\n--seedPerReadNmax\nmax number of seeds per read\ninteger, example: 1000\n\n\n--seedPerWindowNmax\nmax number of seeds per window\ninteger, example: 50\n\n\n--seedNoneLociPerWindow\nmax number of one seed loci per window\ninteger, example: 10\n\n\n--seedSplitMin\nmin length of the seed sequences split by Ns or mate gap\ninteger, example: 12\n\n\n--seedMapMin\nmin length of seeds to be mapped\ninteger, example: 5\n\n\n--alignIntronMin\nminimum intron size, genomic gap is considered intron if its length>=alignIntronMin, otherwise it is considered Deletion\ninteger, example: 21\n\n\n--alignIntronMax\nmaximum intron size, if 0, max intron size will be determined by (2^winBinNbits)*winAnchorDistNbins\ninteger, example: 0\n\n\n--alignMatesGapMax\nmaximum gap between two mates, if 0, max intron gap will be determined by (2^winBinNbits)*winAnchorDistNbins\ninteger, example: 0\n\n\n--alignSJoverhangMin\nminimum overhang (i.e. block size) for spliced alignments\ninteger, example: 5\n\n\n--alignSJstitchMismatchNmax\nmaximum number of mismatches for stitching of the splice junctions (-1: no limit). (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif.\ninteger, example: 0, example: -1, example: 0, example: 0\n\n\n--alignSJDBoverhangMin\nminimum overhang (i.e. block size) for annotated (sjdb) spliced alignments\ninteger, example: 3\n\n\n--alignSplicedMateMapLmin\nminimum mapped length for a read mate that is spliced\ninteger, example: 0\n\n\n--alignSplicedMateMapLminOverLmate\nalignSplicedMateMapLmin normalized to mate length\ndouble, example: 0.66\n\n\n--alignWindowsPerReadNmax\nmax number of windows per read\ninteger, example: 10000\n\n\n--alignTranscriptsPerWindowNmax\nmax number of transcripts per window\ninteger, example: 100\n\n\n--alignTranscriptsPerReadNmax\nmax number of different alignments per read to consider\ninteger, example: 10000\n\n\n--alignEndsType\ntype of read ends alignment - Local … standard local alignment with soft-clipping allowed - EndToEnd … force end-to-end read alignment, do not soft-clip - Extend5pOfRead1 … fully extend only the 5p of the read1, all other ends: local alignment - Extend5pOfReads12 … fully extend only the 5p of the both read1 and read2, all other ends: local alignment\nstring, example: \"Local\"\n\n\n--alignEndsProtrude\nallow protrusion of alignment ends, i.e. start (end) of the +strand mate downstream of the start (end) of the -strand mate 1st word: int: maximum number of protrusion bases allowed 2nd word: string: - ConcordantPair … report alignments with non-zero protrusion as concordant pairs - DiscordantPair … report alignments with non-zero protrusion as discordant pairs\nstring, example: \"0 ConcordantPair\"\n\n\n--alignSoftClipAtReferenceEnds\nallow the soft-clipping of the alignments past the end of the chromosomes - Yes … allow - No … prohibit, useful for compatibility with Cufflinks\nstring, example: \"Yes\"\n\n\n--alignInsertionFlush\nhow to flush ambiguous insertion positions - None … insertions are not flushed - Right … insertions are flushed to the right\nstring\n\n\n\n\n\nPaired-End reads\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--peOverlapNbasesMin\nminimum number of overlapping bases to trigger mates merging and realignment. Specify >0 value to switch on the “merginf of overlapping mates” algorithm.\ninteger, example: 0\n\n\n--peOverlapMMp\nmaximum proportion of mismatched bases in the overlap area\ndouble, example: 0.01\n\n\n\n\n\nWindows, Anchors, Binning\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--winAnchorMultimapNmax\nmax number of loci anchors are allowed to map to\ninteger, example: 50\n\n\n--winBinNbits\n=log2(winBin), where winBin is the size of the bin for the windows/clustering, each window will occupy an integer number of bins.\ninteger, example: 16\n\n\n--winAnchorDistNbins\nmax number of bins between two anchors that allows aggregation of anchors into one window\ninteger, example: 9\n\n\n--winFlankNbins\nlog2(winFlank), where win Flank is the size of the left and right flanking regions for each window\ninteger, example: 4\n\n\n--winReadCoverageRelativeMin\nminimum relative coverage of the read sequence by the seeds in a window, for STARlong algorithm only.\ndouble, example: 0.5\n\n\n--winReadCoverageBasesMin\nminimum number of bases covered by the seeds in a window , for STARlong algorithm only.\ninteger, example: 0\n\n\n\n\n\nChimeric Alignments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--chimOutType\ntype of chimeric output - Junctions … Chimeric.out.junction - SeparateSAMold … output old SAM into separate Chimeric.out.sam file - WithinBAM … output into main aligned BAM files (Aligned.*.bam) - WithinBAM HardClip … (default) hard-clipping in the CIGAR for supplemental chimeric alignments (default if no 2nd word is present) - WithinBAM SoftClip … soft-clipping in the CIGAR for supplemental chimeric alignments\nstring, example: \"Junctions\"\n\n\n--chimSegmentMin\nminimum length of chimeric segment length, if ==0, no chimeric output\ninteger, example: 0\n\n\n--chimScoreMin\nminimum total (summed) score of the chimeric segments\ninteger, example: 0\n\n\n--chimScoreDropMax\nmax drop (difference) of chimeric score (the sum of scores of all chimeric segments) from the read length\ninteger, example: 20\n\n\n--chimScoreSeparation\nminimum difference (separation) between the best chimeric score and the next one\ninteger, example: 10\n\n\n--chimScoreJunctionNonGTAG\npenalty for a non-GT/AG chimeric junction\ninteger, example: -1\n\n\n--chimJunctionOverhangMin\nminimum overhang for a chimeric junction\ninteger, example: 20\n\n\n--chimSegmentReadGapMax\nmaximum gap in the read sequence between chimeric segments\ninteger, example: 0\n\n\n--chimFilter\ndifferent filters for chimeric alignments - None … no filtering - banGenomicN … Ns are not allowed in the genome sequence around the chimeric junction\nstring, example: \"banGenomicN\"\n\n\n--chimMainSegmentMultNmax\nmaximum number of multi-alignments for the main chimeric segment. =1 will prohibit multimapping main segments.\ninteger, example: 10\n\n\n--chimMultimapNmax\nmaximum number of chimeric multi-alignments - 0 … use the old scheme for chimeric detection which only considered unique alignments\ninteger, example: 0\n\n\n--chimMultimapScoreRange\nthe score range for multi-mapping chimeras below the best chimeric score. Only works with –chimMultimapNmax > 1\ninteger, example: 1\n\n\n--chimNonchimScoreDropMin\nto trigger chimeric detection, the drop in the best non-chimeric alignment score with respect to the read length has to be greater than this value\ninteger, example: 20\n\n\n--chimOutJunctionFormat\nformatting type for the Chimeric.out.junction file - 0 … no comment lines/headers - 1 … comment lines at the end of the file: command line and Nreads: total, unique/multi-mapping\ninteger, example: 0\n\n\n\n\n\nQuantification of Annotations\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--quantMode\ntypes of quantification requested - - … none - TranscriptomeSAM … output SAM/BAM alignments to transcriptome into a separate file - GeneCounts … count reads per gene\nstring\n\n\n--quantTranscriptomeBAMcompression\n-2 to 10 transcriptome BAM compression level - -2 … no BAM output - -1 … default compression (6?) - 0 … no compression - 10 … maximum compression\ninteger, example: 1\n\n\n--quantTranscriptomeBan\nprohibit various alignment type - IndelSoftclipSingleend … prohibit indels, soft clipping and single-end alignments - compatible with RSEM - Singleend … prohibit single-end alignments\nstring, example: \"IndelSoftclipSingleend\"\n\n\n\n\n\n2-pass Mapping\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--twopassMode\n2-pass mapping mode. - None … 1-pass mapping - Basic … basic 2-pass mapping, with all 1st pass junctions inserted into the genome indices on the fly\nstring\n\n\n--twopass1readsN\nnumber of reads to process for the 1st step. Use very large number (or default -1) to map all reads in the first step.\ninteger, example: -1\n\n\n\n\n\nWASP parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--waspOutputMode\nWASP allele-specific output type. This is re-implementation of the original WASP mappability filtering by Bryce van de Geijn, Graham McVicker, Yoav Gilad & Jonathan K Pritchard. Please cite the original WASP paper: Nature Methods 12, 1061-1063 (2015), https://www.nature.com/articles/nmeth.3582 . - SAMtag … add WASP tags to the alignments that pass WASP filtering\nstring\n\n\n\n\n\nSTARsolo (single cell RNA-seq) parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--soloType\ntype of single-cell RNA-seq - CB_UMI_Simple … (a.k.a. Droplet) one UMI and one Cell Barcode of fixed length in read2, e.g. Drop-seq and 10X Chromium. - CB_UMI_Complex … multiple Cell Barcodes of varying length, one UMI of fixed length and one adapter sequence of fixed length are allowed in read2 only (e.g. inDrop, ddSeq). - CB_samTagOut … output Cell Barcode as CR and/or CB SAm tag. No UMI counting. –readFilesIn cDNA_read1 [cDNA_read2 if paired-end] CellBarcode_read . Requires –outSAMtype BAM Unsorted [and/or SortedByCoordinate] - SmartSeq … Smart-seq: each cell in a separate FASTQ (paired- or single-end), barcodes are corresponding read-groups, no UMI sequences, alignments deduplicated according to alignment start and end (after extending soft-clipped bases)\nstring\n\n\n--soloCBwhitelist\nfile(s) with whitelist(s) of cell barcodes. Only –soloType CB_UMI_Complex allows more than one whitelist file. - None … no whitelist: all cell barcodes are allowed\nstring\n\n\n--soloCBstart\ncell barcode start base\ninteger, example: 1\n\n\n--soloCBlen\ncell barcode length\ninteger, example: 16\n\n\n--soloUMIstart\nUMI start base\ninteger, example: 17\n\n\n--soloUMIlen\nUMI length\ninteger, example: 10\n\n\n--soloBarcodeReadLength\nlength of the barcode read - 1 … equal to sum of soloCBlen+soloUMIlen - 0 … not defined, do not check\ninteger, example: 1\n\n\n--soloBarcodeMate\nidentifies which read mate contains the barcode (CB+UMI) sequence - 0 … barcode sequence is on separate read, which should always be the last file in the –readFilesIn listed - 1 … barcode sequence is a part of mate 1 - 2 … barcode sequence is a part of mate 2\ninteger, example: 0\n\n\n--soloCBposition\nposition of Cell Barcode(s) on the barcode read. Presently only works with –soloType CB_UMI_Complex, and barcodes are assumed to be on Read2. Format for each barcode: startAnchor_startPosition_endAnchor_endPosition start(end)Anchor defines the Anchor Base for the CB: 0: read start; 1: read end; 2: adapter start; 3: adapter end start(end)Position is the 0-based position with of the CB start(end) with respect to the Anchor Base String for different barcodes are separated by space. Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 0_0_2_-1 3_1_3_8\nstring\n\n\n--soloUMIposition\nposition of the UMI on the barcode read, same as soloCBposition Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 3_9_3_14\nstring\n\n\n--soloAdapterSequence\nadapter sequence to anchor barcodes. Only one adapter sequence is allowed.\nstring\n\n\n--soloAdapterMismatchesNmax\nmaximum number of mismatches allowed in adapter sequence.\ninteger, example: 1\n\n\n--soloCBmatchWLtype\nmatching the Cell Barcodes to the WhiteList - Exact … only exact matches allowed - 1MM … only one match in whitelist with 1 mismatched base allowed. Allowed CBs have to have at least one read with exact match. - 1MM_multi … multiple matches in whitelist with 1 mismatched base allowed, posterior probability calculation is used choose one of the matches. Allowed CBs have to have at least one read with exact match. This option matches best with CellRanger 2.2.0 - 1MM_multi_pseudocounts … same as 1MM_Multi, but pseudocounts of 1 are added to all whitelist barcodes. - 1MM_multi_Nbase_pseudocounts … same as 1MM_multi_pseudocounts, multimatching to WL is allowed for CBs with N-bases. This option matches best with CellRanger >= 3.0.0 - EditDist_2 … allow up to edit distance of 3 fpr each of the barcodes. May include one deletion + one insertion. Only works with –soloType CB_UMI_Complex. Matches to multiple passlist barcdoes are not allowed. Similar to ParseBio Split-seq pipeline.\nstring, example: \"1MM_multi\"\n\n\n--soloInputSAMattrBarcodeSeq\nwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode sequence (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeSeq CR UR . This parameter is required when running STARsolo with input from SAM.\nstring\n\n\n--soloInputSAMattrBarcodeQual\nwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode qualities (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeQual CY UY . If this parameter is ‘-’ (default), the quality ‘H’ will be assigned to all bases.\nstring\n\n\n--soloStrand\nstrandedness of the solo libraries: - Unstranded … no strand information - Forward … read strand same as the original RNA molecule - Reverse … read strand opposite to the original RNA molecule\nstring, example: \"Forward\"\n\n\n--soloFeatures\ngenomic features for which the UMI counts per Cell Barcode are collected - Gene … genes: reads match the gene transcript - SJ … splice junctions: reported in SJ.out.tab - GeneFull … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns - GeneFull_ExonOverIntron … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns: prioritize 100% overlap with exons - GeneFull_Ex50pAS … full gene (pre-RNA): count all reads overlapping genes’ exons and introns: prioritize >50% overlap with exons. Do not count reads with 100% exonic overlap in the antisense direction.\nstring, example: \"Gene\"\n\n\n--soloMultiMappers\ncounting method for reads mapping to multiple genes - Unique … count only reads that map to unique genes - Uniform … uniformly distribute multi-genic UMIs to all genes - Rescue … distribute UMIs proportionally to unique+uniform counts (~ first iteration of EM) - PropUnique … distribute UMIs proportionally to unique mappers, if present, and uniformly if not. - EM … multi-gene UMIs are distributed using Expectation Maximization algorithm\nstring, example: \"Unique\"\n\n\n--soloUMIdedup\ntype of UMI deduplication (collapsing) algorithm - 1MM_All … all UMIs with 1 mismatch distance to each other are collapsed (i.e. counted once). - 1MM_Directional_UMItools … follows the “directional” method from the UMI-tools by Smith, Heger and Sudbery (Genome Research 2017). - 1MM_Directional … same as 1MM_Directional_UMItools, but with more stringent criteria for duplicate UMIs - Exact … only exactly matching UMIs are collapsed. - NoDedup … no deduplication of UMIs, count all reads. - 1MM_CR … CellRanger2-4 algorithm for 1MM UMI collapsing.\nstring, example: \"1MM_All\"\n\n\n--soloUMIfiltering\ntype of UMI filtering (for reads uniquely mapping to genes) - - … basic filtering: remove UMIs with N and homopolymers (similar to CellRanger 2.2.0). - MultiGeneUMI … basic + remove lower-count UMIs that map to more than one gene. - MultiGeneUMI_All … basic + remove all UMIs that map to more than one gene. - MultiGeneUMI_CR … basic + remove lower-count UMIs that map to more than one gene, matching CellRanger > 3.0.0 . Only works with –soloUMIdedup 1MM_CR\nstring\n\n\n--soloOutFileNames\nfile names for STARsolo output: file_name_prefix gene_names barcode_sequences cell_feature_count_matrix\nstring, example: \"Solo.out/\", example: \"features.tsv\", example: \"barcodes.tsv\", example: \"matrix.mtx\"\n\n\n--soloCellFilter\ncell filtering type and parameters - None … do not output filtered cells - TopCells … only report top cells by UMI count, followed by the exact number of cells - CellRanger2.2 … simple filtering of CellRanger 2.2. Can be followed by numbers: number of expected cells, robust maximum percentile for UMI count, maximum to minimum ratio for UMI count The harcoded values are from CellRanger: nExpectedCells=3000; maxPercentile=0.99; maxMinRatio=10 - EmptyDrops_CR … EmptyDrops filtering in CellRanger flavor. Please cite the original EmptyDrops paper: A.T.L Lun et al, Genome Biology, 20, 63 (2019): https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1662-y Can be followed by 10 numeric parameters: nExpectedCells maxPercentile maxMinRatio indMin indMax umiMin umiMinFracMedian candMaxN FDR simN The harcoded values are from CellRanger: 3000 0.99 10 45000 90000 500 0.01 20000 0.01 10000\nstring, example: \"CellRanger2.2\", example: \"3000\", example: \"0.99\", example: \"10\"\n\n\n--soloOutFormatFeaturesGeneField3\nfield 3 in the Gene features.tsv file. If “-”, then no 3rd field is output.\nstring, example: \"Gene Expression\"\n\n\n--soloCellReadStats\nOutput reads statistics for each CB - Standard … standard output\nstring\n\n\n\n\n\nHTSeq arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--stranded\nWhether the data is from a strand-specific assay. ‘reverse’ means ‘yes’ with reversed strand interpretation.\nstring, default: \"yes\"\n\n\n--minimum_alignment_quality\nSkip all reads with MAPQ alignment quality lower than the given minimum value. MAPQ is the 5th column of a SAM/BAM file and its usage depends on the software used to map the reads.\ninteger, default: 10\n\n\n--type\nFeature type (3rd column in GTF file) to be used, all features of other type are ignored (default, suitable for Ensembl GTF files: exon)\nstring, example: \"exon\"\n\n\n--id_attribute\nGTF attribute to be used as feature ID (default, suitable for Ensembl GTF files: gene_id). All feature of the right type (see -t option) within the same GTF attribute will be added together. The typical way of using this option is to count all exonic reads from each gene and add the exons but other uses are possible as well. You can call this option multiple times: in that case, the combination of all attributes separated by colons (:) will be used as a unique identifier, e.g. for exons you might use -i gene_id -i exon_number.\nstring, example: \"gene_id\"\n\n\n--additional_attributes\nAdditional feature attributes (suitable for Ensembl GTF files: gene_name). Use multiple times for more than one additional attribute. These attributes are only used as annotations in the output, while the determination of how the counts are added together is done based on option -i.\nstring, example: \"gene_name\"\n\n\n--add_chromosome_info\nStore information about the chromosome of each feature as an additional attribute (e.g. colunm in the TSV output file).\nboolean_true\n\n\n--mode\nMode to handle reads overlapping more than one feature.\nstring, default: \"union\"\n\n\n--non_unique\nWhether and how to score reads that are not uniquely aligned or ambiguously assigned to features.\nstring, default: \"none\"\n\n\n--secondary_alignments\nWhether to score secondary alignments (0x100 flag).\nstring\n\n\n--supplementary_alignments\nWhether to score supplementary alignments (0x800 flag).\nstring\n\n\n--counts_output_sparse\nStore the counts as a sparse matrix (mtx, h5ad, loom).\nboolean_true" + }, + { + "objectID": "components/modules/mapping/multi_star.html#authors", + "href": "components/modules/mapping/multi_star.html#authors", + "title": "Multi star", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/mapping/cellranger_multi.html", + "href": "components/modules/mapping/cellranger_multi.html", + "title": "Cellranger multi", + "section": "", + "text": "ID: cellranger_multi\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/cellranger_multi.html#example-commands", + "href": "components/modules/mapping/cellranger_multi.html#example-commands", + "title": "Cellranger multi", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/cellranger_multi/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Outputs\n# output: \"$id.$key.output.output\"\n\n# Input files\ninput: # please fill in - example: [\"mysample_S1_L001_R1_001.fastq.gz\", \"mysample_S1_L001_R2_001.fastq.gz\"]\ngex_reference: # please fill in - example: \"reference_genome.tar.gz\"\n# vdj_reference: \"reference_vdj.tar.gz\"\n# vdj_inner_enrichment_primers: \"enrichment_primers.txt\"\n# feature_reference: \"feature_reference.csv\"\n\n# Library arguments\nlibrary_id: # please fill in - example: [\"mysample1\"]\nlibrary_type: # please fill in - example: [\"Gene Expression\"]\n# library_subsample: [\"0.5\"]\n# library_lanes: [\"1-4\"]\n\n# Gene expression arguments\n# gex_expect_cells: 3000\ngex_chemistry: \"auto\"\ngex_secondary_analysis: false\ngex_generate_bam: false\ngex_include_introns: true\n\n# Cell multiplexing parameters\n# cell_multiplex_sample_id: \"foo\"\n# cell_multiplex_oligo_ids: \"foo\"\n# cell_multiplex_description: \"foo\"\n\n# Executor arguments\ndryrun: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/cellranger_multi/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/cellranger_multi.html#argument-groups", + "href": "components/modules/mapping/cellranger_multi.html#argument-groups", + "title": "Cellranger multi", + "section": "Argument groups", + "text": "Argument groups\n\nInput files\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nThe FASTQ files to be analyzed. FASTQ files should conform to the naming conventions of bcl2fastq and mkfastq: [Sample Name]_S[Sample Index]_L00[Lane Number]_[Read Type]_001.fastq.gz\nfile, required, example: \"mysample_S1_L001_R1_001.fastq.gz\", example: \"mysample_S1_L001_R2_001.fastq.gz\"\n\n\n--gex_reference\nGenome refence index built by Cell Ranger mkref.\nfile, required, example: \"reference_genome.tar.gz\"\n\n\n--vdj_reference\nVDJ refence index built by Cell Ranger mkref.\nfile, example: \"reference_vdj.tar.gz\"\n\n\n--vdj_inner_enrichment_primers\nV(D)J Immune Profiling libraries: if inner enrichment primers other than those provided in the 10x Genomics kits are used, they need to be specified here as a text file with one primer per line.\nfile, example: \"enrichment_primers.txt\"\n\n\n--feature_reference\nPath to the Feature reference CSV file, declaring Feature Barcode constructs and associated barcodes. Required only for Antibody Capture or CRISPR Guide Capture libraries. See https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/feature-bc-analysis#feature-ref for more information.\nfile, example: \"feature_reference.csv\"\n\n\n\n\n\nLibrary arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--library_id\nThe Illumina sample name to analyze. This must exactly match the ‘Sample Name’ part of the FASTQ files specified in the --input argument.\nstring, required, example: \"mysample1\"\n\n\n--library_type\nThe underlying feature type of the library. Possible values: “Gene Expression”, “VDJ”, “VDJ-T”, “VDJ-B”, “Antibody Capture”, “CRISPR Guide Capture”, “Multiplexing Capture”\nstring, required, example: \"Gene Expression\"\n\n\n--library_subsample\nOptional. The rate at which reads from the provided FASTQ files are sampled. Must be strictly greater than 0 and less than or equal to 1.\nstring, example: \"0.5\"\n\n\n--library_lanes\nLanes associated with this sample. Defaults to using all lanes.\nstring, example: \"1-4\"\n\n\n\n\n\nGene expression arguments\nArguments relevant to the analysis of gene expression data.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--gex_expect_cells\nExpected number of recovered cells, used as input to cell calling algorithm.\ninteger, example: 3000\n\n\n--gex_chemistry\nAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.\nstring, default: \"auto\"\n\n\n--gex_secondary_analysis\nWhether or not to run the secondary analysis e.g. clustering.\nboolean, default: FALSE\n\n\n--gex_generate_bam\nWhether to generate a BAM file.\nboolean, default: FALSE\n\n\n--gex_include_introns\nInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)\nboolean, default: TRUE\n\n\n\n\n\nCell multiplexing parameters\nArguments related to cell multiplexing.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--cell_multiplex_sample_id\nA name to identify a multiplexed sample. Must be alphanumeric with hyphens and/or underscores, and less than 64 characters. Required for Cell Multiplexing libraries.\nstring\n\n\n--cell_multiplex_oligo_ids\nThe Cell Multiplexing oligo IDs used to multiplex this sample. If multiple CMOs were used for a sample, separate IDs with a pipe (e.g., CMO301|CMO302). Required for Cell Multiplexing libraries.\nstring\n\n\n--cell_multiplex_description\nA description for the sample.\nstring\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nThe folder to store the alignment results.\nfile, required, example: \"/path/to/output\"\n\n\n\n\n\nExecutor arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--dryrun\nIf true, the output directory will only contain the CWL input files, but the pipeline itself will not be executed.\nboolean_true" + }, + { + "objectID": "components/modules/mapping/cellranger_multi.html#authors", + "href": "components/modules/mapping/cellranger_multi.html#authors", + "title": "Cellranger multi", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)\nDries De Maeyer (author)" + }, + { + "objectID": "components/modules/mapping/star_align.html", + "href": "components/modules/mapping/star_align.html", + "title": "Star align", + "section": "", + "text": "ID: star_align\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/star_align.html#example-commands", + "href": "components/modules/mapping/star_align.html#example-commands", + "title": "Star align", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/star_align/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Input/Output\ninput: # please fill in - example: [\"mysample_S1_L001_R1_001.fastq.gz\", \"mysample_S1_L001_R2_001.fastq.gz\"]\nreference: # please fill in - example: \"/path/to/reference\"\n# output: \"$id.$key.output.output\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/star_align/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/star_align.html#argument-groups", + "href": "components/modules/mapping/star_align.html#argument-groups", + "title": "Star align", + "section": "Argument groups", + "text": "Argument groups\n\nInput/Output\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nThe FASTQ files to be analyzed. Corresponds to the –readFilesIn argument in the STAR command.\nfile, required, example: \"mysample_S1_L001_R1_001.fastq.gz\", example: \"mysample_S1_L001_R2_001.fastq.gz\"\n\n\n--reference\nPath to the reference built by star_build_reference. Corresponds to the –genomeDir argument in the STAR command.\nfile, required, example: \"/path/to/reference\"\n\n\n--output\nPath to output directory. Corresponds to the –outFileNamePrefix argument in the STAR command.\nfile, required, example: \"/path/to/foo\"\n\n\n\n\n\nRun Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--runRNGseed\nrandom number generator seed.\ninteger, example: 777\n\n\n\n\n\nGenome Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genomeLoad\nmode of shared memory usage for the genome files. Only used with –runMode alignReads. - LoadAndKeep … load genome into shared and keep it in memory after run - LoadAndRemove … load genome into shared but remove it after run - LoadAndExit … load genome into shared memory and exit, keeping the genome in memory for future runs - Remove … do not map anything, just remove loaded genome from memory - NoSharedMemory … do not use shared memory, each job will have its own private copy of the genome\nstring, example: \"NoSharedMemory\"\n\n\n--genomeFastaFiles\npath(s) to the fasta files with the genome sequences, separated by spaces. These files should be plain text FASTA files, they cannot be zipped. Required for the genome generation (–runMode genomeGenerate). Can also be used in the mapping (–runMode alignReads) to add extra (new) sequences to the genome (e.g. spike-ins).\nfile\n\n\n--genomeFileSizes\ngenome files exact sizes in bytes. Typically, this should not be defined by the user.\ninteger, example: 0\n\n\n--genomeTransformOutput\nwhich output to transform back to original genome - SAM … SAM/BAM alignments - SJ … splice junctions (SJ.out.tab) - None … no transformation of the output\nstring\n\n\n--genomeChrSetMitochondrial\nnames of the mitochondrial chromosomes. Presently only used for STARsolo statistics output/\nstring, example: \"chrM\", example: \"M\", example: \"MT\"\n\n\n\n\n\nSplice Junctions Database\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--sjdbFileChrStartEnd\npath to the files with genomic coordinates (chr start end strand) for the splice junction introns. Multiple files can be supplied and will be concatenated.\nstring\n\n\n--sjdbGTFfile\npath to the GTF file with annotations\nfile\n\n\n--sjdbGTFchrPrefix\nprefix for chromosome names in a GTF file (e.g. ‘chr’ for using ENSMEBL annotations with UCSC genomes)\nstring\n\n\n--sjdbGTFfeatureExon\nfeature type in GTF file to be used as exons for building transcripts\nstring, example: \"exon\"\n\n\n--sjdbGTFtagExonParentTranscript\nGTF attribute name for parent transcript ID (default “transcript_id” works for GTF files)\nstring, example: \"transcript_id\"\n\n\n--sjdbGTFtagExonParentGene\nGTF attribute name for parent gene ID (default “gene_id” works for GTF files)\nstring, example: \"gene_id\"\n\n\n--sjdbGTFtagExonParentGeneName\nGTF attribute name for parent gene name\nstring, example: \"gene_name\"\n\n\n--sjdbGTFtagExonParentGeneType\nGTF attribute name for parent gene type\nstring, example: \"gene_type\", example: \"gene_biotype\"\n\n\n--sjdbOverhang\nlength of the donor/acceptor sequence on each side of the junctions, ideally = (mate_length - 1)\ninteger, example: 100\n\n\n--sjdbScore\nextra alignment score for alignments that cross database junctions\ninteger, example: 2\n\n\n--sjdbInsertSave\nwhich files to save when sjdb junctions are inserted on the fly at the mapping step - Basic … only small junction / transcript files - All … all files including big Genome, SA and SAindex - this will create a complete genome directory\nstring, example: \"Basic\"\n\n\n\n\n\nVariation parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--varVCFfile\npath to the VCF file that contains variation data. The 10th column should contain the genotype information, e.g. 0/1\nstring\n\n\n\n\n\nRead Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--readFilesType\nformat of input read files - Fastx … FASTA or FASTQ - SAM SE … SAM or BAM single-end reads; for BAM use –readFilesCommand samtools view - SAM PE … SAM or BAM paired-end reads; for BAM use –readFilesCommand samtools view\nstring, example: \"Fastx\"\n\n\n--readFilesSAMattrKeep\nfor –readFilesType SAM SE/PE, which SAM tags to keep in the output BAM, e.g.: –readFilesSAMtagsKeep RG PL - All … keep all tags - None … do not keep any tags\nstring, example: \"All\"\n\n\n--readFilesManifest\npath to the “manifest” file with the names of read files. The manifest file should contain 3 tab-separated columns: paired-end reads: read1_file_name \\(tab\\) read2_file_name \\(tab\\) read_group_line. single-end reads: read1_file_name \\(tab\\) - \\(tab\\) read_group_line. Spaces, but not tabs are allowed in file names. If read_group_line does not start with ID:, it can only contain one ID field, and ID: will be added to it. If read_group_line starts with ID:, it can contain several fields separated by \\(tab\\), and all fields will be be copied verbatim into SAM @RG header line.\nfile\n\n\n--readFilesPrefix\nprefix for the read files names, i.e. it will be added in front of the strings in –readFilesIn\nstring\n\n\n--readFilesCommand\ncommand line to execute for each of the input file. This command should generate FASTA or FASTQ text and send it to stdout For example: zcat - to uncompress .gz files, bzcat - to uncompress .bz2 files, etc.\nstring\n\n\n--readMapNumber\nnumber of reads to map from the beginning of the file -1: map all reads\ninteger, example: -1\n\n\n--readMatesLengthsIn\nEqual/NotEqual - lengths of names,sequences,qualities for both mates are the same / not the same. NotEqual is safe in all situations.\nstring, example: \"NotEqual\"\n\n\n--readNameSeparator\ncharacter(s) separating the part of the read names that will be trimmed in output (read name after space is always trimmed)\nstring, example: \"/\"\n\n\n--readQualityScoreBase\nnumber to be subtracted from the ASCII code to get Phred quality score\ninteger, example: 33\n\n\n\n\n\nRead Clipping\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--clipAdapterType\nadapter clipping type - Hamming … adapter clipping based on Hamming distance, with the number of mismatches controlled by –clip5pAdapterMMp - CellRanger4 … 5p and 3p adapter clipping similar to CellRanger4. Utilizes Opal package by Martin Sosic: https://github.com/Martinsos/opal - None … no adapter clipping, all other clip* parameters are disregarded\nstring, example: \"Hamming\"\n\n\n--clip3pNbases\nnumber(s) of bases to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n--clip3pAdapterSeq\nadapter sequences to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates. - polyA … polyA sequence with the length equal to read length\nstring\n\n\n--clip3pAdapterMMp\nmax proportion of mismatches for 3p adapter clipping for each mate. If one value is given, it will be assumed the same for both mates.\ndouble, example: 0.1\n\n\n--clip3pAfterAdapterNbases\nnumber of bases to clip from 3p of each mate after the adapter clipping. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n--clip5pNbases\nnumber(s) of bases to clip from 5p of each mate. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n\n\n\nLimits\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--limitGenomeGenerateRAM\nmaximum available RAM (bytes) for genome generation\nlong, example: NA\n\n\n--limitIObufferSize\nmax available buffers size (bytes) for input/output, per thread\nlong, example: 30000000, example: 50000000\n\n\n--limitOutSAMoneReadBytes\nmax size of the SAM record (bytes) for one read. Recommended value: >(2(LengthMate1+LengthMate2+100)outFilterMultimapNmax\nlong, example: 100000\n\n\n--limitOutSJoneRead\nmax number of junctions for one read (including all multi-mappers)\ninteger, example: 1000\n\n\n--limitOutSJcollapsed\nmax number of collapsed junctions\ninteger, example: 1000000\n\n\n--limitBAMsortRAM\nmaximum available RAM (bytes) for sorting BAM. If =0, it will be set to the genome index size. 0 value can only be used with –genomeLoad NoSharedMemory option.\nlong, example: 0\n\n\n--limitSjdbInsertNsj\nmaximum number of junctions to be inserted to the genome on the fly at the mapping stage, including those from annotations and those detected in the 1st step of the 2-pass run\ninteger, example: 1000000\n\n\n--limitNreadsSoft\nsoft limit on the number of reads\ninteger, example: -1\n\n\n\n\n\nOutput: general\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outTmpKeep\nwhether to keep the temporary files after STAR runs is finished - None … remove all temporary files - All … keep all files\nstring\n\n\n--outStd\nwhich output will be directed to stdout (standard out) - Log … log messages - SAM … alignments in SAM format (which normally are output to Aligned.out.sam file), normal standard output will go into Log.std.out - BAM_Unsorted … alignments in BAM format, unsorted. Requires –outSAMtype BAM Unsorted - BAM_SortedByCoordinate … alignments in BAM format, sorted by coordinate. Requires –outSAMtype BAM SortedByCoordinate - BAM_Quant … alignments to transcriptome in BAM format, unsorted. Requires –quantMode TranscriptomeSAM\nstring, example: \"Log\"\n\n\n--outReadsUnmapped\noutput of unmapped and partially mapped (i.e. mapped only one mate of a paired end read) reads in separate file(s). - None … no output - Fastx … output in separate fasta/fastq files, Unmapped.out.mate1/2\nstring\n\n\n--outQSconversionAdd\nadd this number to the quality score (e.g. to convert from Illumina to Sanger, use -31)\ninteger, example: 0\n\n\n--outMultimapperOrder\norder of multimapping alignments in the output files - Old_2.4 … quasi-random order used before 2.5.0 - Random … random order of alignments for each multi-mapper. Read mates (pairs) are always adjacent, all alignment for each read stay together. This option will become default in the future releases.\nstring, example: \"Old_2.4\"\n\n\n\n\n\nOutput: SAM and BAM\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSAMtype\ntype of SAM/BAM output 1st word: - BAM … output BAM without sorting - SAM … output SAM without sorting - None … no SAM/BAM output 2nd, 3rd: - Unsorted … standard unsorted - SortedByCoordinate … sorted by coordinate. This option will allocate extra memory for sorting which can be specified by –limitBAMsortRAM.\nstring, example: \"SAM\"\n\n\n--outSAMmode\nmode of SAM output - None … no SAM output - Full … full SAM output - NoQS … full SAM but without quality scores\nstring, example: \"Full\"\n\n\n--outSAMstrandField\nCufflinks-like strand field flag - None … not used - intronMotif … strand derived from the intron motif. This option changes the output alignments: reads with inconsistent and/or non-canonical introns are filtered out.\nstring\n\n\n--outSAMattributes\na string of desired SAM attributes, in the order desired for the output SAM. Tags can be listed in any combination/order. Presets: - None … no attributes - Standard … NH HI AS nM - All … NH HI AS nM NM MD jM jI MC ch Alignment: - NH … number of loci the reads maps to: =1 for unique mappers, >1 for multimappers. Standard SAM tag. - HI … multiple alignment index, starts with –outSAMattrIHstart (=1 by default). Standard SAM tag. - AS … local alignment score, +1/-1 for matches/mismateches, score* penalties for indels and gaps. For PE reads, total score for two mates. Stadnard SAM tag. - nM … number of mismatches. For PE reads, sum over two mates. - NM … edit distance to the reference (number of mismatched + inserted + deleted bases) for each mate. Standard SAM tag. - MD … string encoding mismatched and deleted reference bases (see standard SAM specifications). Standard SAM tag. - jM … intron motifs for all junctions (i.e. N in CIGAR): 0: non-canonical; 1: GT/AG, 2: CT/AC, 3: GC/AG, 4: CT/GC, 5: AT/AC, 6: GT/AT. If splice junctions database is used, and a junction is annotated, 20 is added to its motif value. - jI … start and end of introns for all junctions (1-based). - XS … alignment strand according to –outSAMstrandField. - MC … mate’s CIGAR string. Standard SAM tag. - ch … marks all segment of all chimeric alingments for –chimOutType WithinBAM output. - cN … number of bases clipped from the read ends: 5’ and 3’ Variation: - vA … variant allele - vG … genomic coordinate of the variant overlapped by the read. - vW … 1 - alignment passes WASP filtering; 2,3,4,5,6,7 - alignment does not pass WASP filtering. Requires –waspOutputMode SAMtag. STARsolo: - CR CY UR UY … sequences and quality scores of cell barcodes and UMIs for the solo* demultiplexing. - GX GN … gene ID and gene name for unique-gene reads. - gx gn … gene IDs and gene names for unique- and multi-gene reads. - CB UB … error-corrected cell barcodes and UMIs for solo* demultiplexing. Requires –outSAMtype BAM SortedByCoordinate. - sM … assessment of CB and UMI. - sS … sequence of the entire barcode (CB,UMI,adapter). - sQ … quality of the entire barcode. ***Unsupported/undocumented: - ha … haplotype (1/2) when mapping to the diploid genome. Requires genome generated with –genomeTransformType Diploid . - rB … alignment block read/genomic coordinates. - vR … read coordinate of the variant.\nstring, example: \"Standard\"\n\n\n--outSAMattrIHstart\nstart value for the IH attribute. 0 may be required by some downstream software, such as Cufflinks or StringTie.\ninteger, example: 1\n\n\n--outSAMunmapped\noutput of unmapped reads in the SAM format 1st word: - None … no output - Within … output unmapped reads within the main SAM file (i.e. Aligned.out.sam) 2nd word: - KeepPairs … record unmapped mate for each alignment, and, in case of unsorted output, keep it adjacent to its mapped mate. Only affects multi-mapping reads.\nstring\n\n\n--outSAMorder\ntype of sorting for the SAM output Paired: one mate after the other for all paired alignments PairedKeepInputOrder: one mate after the other for all paired alignments, the order is kept the same as in the input FASTQ files\nstring, example: \"Paired\"\n\n\n--outSAMprimaryFlag\nwhich alignments are considered primary - all others will be marked with 0x100 bit in the FLAG - OneBestScore … only one alignment with the best score is primary - AllBestScore … all alignments with the best score are primary\nstring, example: \"OneBestScore\"\n\n\n--outSAMreadID\nread ID record type - Standard … first word (until space) from the FASTx read ID line, removing /1,/2 from the end - Number … read number (index) in the FASTx file\nstring, example: \"Standard\"\n\n\n--outSAMmapqUnique\n0 to 255: the MAPQ value for unique mappers\ninteger, example: 255\n\n\n--outSAMflagOR\n0 to 65535: sam FLAG will be bitwise OR’d with this value, i.e. FLAG=FLAG | outSAMflagOR. This is applied after all flags have been set by STAR, and after outSAMflagAND. Can be used to set specific bits that are not set otherwise.\ninteger, example: 0\n\n\n--outSAMflagAND\n0 to 65535: sam FLAG will be bitwise AND’d with this value, i.e. FLAG=FLAG & outSAMflagOR. This is applied after all flags have been set by STAR, but before outSAMflagOR. Can be used to unset specific bits that are not set otherwise.\ninteger, example: 65535\n\n\n--outSAMattrRGline\nSAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”. xxx will be added as RG tag to each output alignment. Any spaces in the tag values have to be double quoted. Comma separated RG lines correspons to different (comma separated) input files in –readFilesIn. Commas have to be surrounded by spaces, e.g. –outSAMattrRGline ID:xxx , ID:zzz “DS:z z” , ID:yyy DS:yyyy\nstring\n\n\n--outSAMheaderHD\n@HD (header) line of the SAM header\nstring\n\n\n--outSAMheaderPG\nextra @PG (software) line of the SAM header (in addition to STAR)\nstring\n\n\n--outSAMheaderCommentFile\npath to the file with @CO (comment) lines of the SAM header\nstring\n\n\n--outSAMfilter\nfilter the output into main SAM/BAM files - KeepOnlyAddedReferences … only keep the reads for which all alignments are to the extra reference sequences added with –genomeFastaFiles at the mapping stage. - KeepAllAddedReferences … keep all alignments to the extra reference sequences added with –genomeFastaFiles at the mapping stage.\nstring\n\n\n--outSAMmultNmax\nmax number of multiple alignments for a read that will be output to the SAM/BAM files. Note that if this value is not equal to -1, the top scoring alignment will be output first - -1 … all alignments (up to –outFilterMultimapNmax) will be output\ninteger, example: -1\n\n\n--outSAMtlen\ncalculation method for the TLEN field in the SAM/BAM files - 1 … leftmost base of the (+)strand mate to rightmost base of the (-)mate. (+)sign for the (+)strand mate - 2 … leftmost base of any mate to rightmost base of any mate. (+)sign for the mate with the leftmost base. This is different from 1 for overlapping mates with protruding ends\ninteger, example: 1\n\n\n--outBAMcompression\n-1 to 10 BAM compression level, -1=default compression (6?), 0=no compression, 10=maximum compression\ninteger, example: 1\n\n\n--outBAMsortingThreadN\n>=0: number of threads for BAM sorting. 0 will default to min(6,–runThreadN).\ninteger, example: 0\n\n\n--outBAMsortingBinsN\n>0: number of genome bins for coordinate-sorting\ninteger, example: 50\n\n\n\n\n\nBAM processing\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--bamRemoveDuplicatesType\nmark duplicates in the BAM file, for now only works with (i) sorted BAM fed with inputBAMfile, and (ii) for paired-end alignments only - - … no duplicate removal/marking - UniqueIdentical … mark all multimappers, and duplicate unique mappers. The coordinates, FLAG, CIGAR must be identical - UniqueIdenticalNotMulti … mark duplicate unique mappers but not multimappers.\nstring\n\n\n--bamRemoveDuplicatesMate2basesN\nnumber of bases from the 5’ of mate 2 to use in collapsing (e.g. for RAMPAGE)\ninteger, example: 0\n\n\n\n\n\nOutput Wiggle\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outWigType\ntype of signal output, e.g. “bedGraph” OR “bedGraph read1_5p”. Requires sorted BAM: –outSAMtype BAM SortedByCoordinate . 1st word: - None … no signal output - bedGraph … bedGraph format - wiggle … wiggle format 2nd word: - read1_5p … signal from only 5’ of the 1st read, useful for CAGE/RAMPAGE etc - read2 … signal from only 2nd read\nstring\n\n\n--outWigStrand\nstrandedness of wiggle/bedGraph output - Stranded … separate strands, str1 and str2 - Unstranded … collapsed strands\nstring, example: \"Stranded\"\n\n\n--outWigReferencesPrefix\nprefix matching reference names to include in the output wiggle file, e.g. “chr”, default “-” - include all references\nstring\n\n\n--outWigNorm\ntype of normalization for the signal - RPM … reads per million of mapped reads - None … no normalization, “raw” counts\nstring, example: \"RPM\"\n\n\n\n\n\nOutput Filtering\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outFilterType\ntype of filtering - Normal … standard filtering using only current alignment - BySJout … keep only those reads that contain junctions that passed filtering into SJ.out.tab\nstring, example: \"Normal\"\n\n\n--outFilterMultimapScoreRange\nthe score range below the maximum score for multimapping alignments\ninteger, example: 1\n\n\n--outFilterMultimapNmax\nmaximum number of loci the read is allowed to map to. Alignments (all of them) will be output only if the read maps to no more loci than this value. Otherwise no alignments will be output, and the read will be counted as “mapped to too many loci” in the Log.final.out .\ninteger, example: 10\n\n\n--outFilterMismatchNmax\nalignment will be output only if it has no more mismatches than this value.\ninteger, example: 10\n\n\n--outFilterMismatchNoverLmax\nalignment will be output only if its ratio of mismatches to mapped length is less than or equal to this value.\ndouble, example: 0.3\n\n\n--outFilterMismatchNoverReadLmax\nalignment will be output only if its ratio of mismatches to read length is less than or equal to this value.\ndouble, example: 1\n\n\n--outFilterScoreMin\nalignment will be output only if its score is higher than or equal to this value.\ninteger, example: 0\n\n\n--outFilterScoreMinOverLread\nsame as outFilterScoreMin, but normalized to read length (sum of mates’ lengths for paired-end reads)\ndouble, example: 0.66\n\n\n--outFilterMatchNmin\nalignment will be output only if the number of matched bases is higher than or equal to this value.\ninteger, example: 0\n\n\n--outFilterMatchNminOverLread\nsam as outFilterMatchNmin, but normalized to the read length (sum of mates’ lengths for paired-end reads).\ndouble, example: 0.66\n\n\n--outFilterIntronMotifs\nfilter alignment using their motifs - None … no filtering - RemoveNoncanonical … filter out alignments that contain non-canonical junctions - RemoveNoncanonicalUnannotated … filter out alignments that contain non-canonical unannotated junctions when using annotated splice junctions database. The annotated non-canonical junctions will be kept.\nstring\n\n\n--outFilterIntronStrands\nfilter alignments - RemoveInconsistentStrands … remove alignments that have junctions with inconsistent strands - None … no filtering\nstring, example: \"RemoveInconsistentStrands\"\n\n\n\n\n\nOutput splice junctions (SJ.out.tab)\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSJtype\ntype of splice junction output - Standard … standard SJ.out.tab output - None … no splice junction output\nstring, example: \"Standard\"\n\n\n\n\n\nOutput Filtering: Splice Junctions\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSJfilterReads\nwhich reads to consider for collapsed splice junctions output - All … all reads, unique- and multi-mappers - Unique … uniquely mapping reads only\nstring, example: \"All\"\n\n\n--outSJfilterOverhangMin\nminimum overhang length for splice junctions on both sides for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif does not apply to annotated junctions\ninteger, example: 30, example: 12, example: 12, example: 12\n\n\n--outSJfilterCountUniqueMin\nminimum uniquely mapping read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctions\ninteger, example: 3, example: 1, example: 1, example: 1\n\n\n--outSJfilterCountTotalMin\nminimum total (multi-mapping+unique) read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctions\ninteger, example: 3, example: 1, example: 1, example: 1\n\n\n--outSJfilterDistToOtherSJmin\nminimum allowed distance to other junctions’ donor/acceptor does not apply to annotated junctions\ninteger, example: 10, example: 0, example: 5, example: 10\n\n\n--outSJfilterIntronMaxVsReadN\nmaximum gap allowed for junctions supported by 1,2,3,,,N reads i.e. by default junctions supported by 1 read can have gaps <=50000b, by 2 reads: <=100000b, by 3 reads: <=200000. by >=4 reads any gap <=alignIntronMax does not apply to annotated junctions\ninteger, example: 50000, example: 100000, example: 200000\n\n\n\n\n\nScoring\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--scoreGap\nsplice junction penalty (independent on intron motif)\ninteger, example: 0\n\n\n--scoreGapNoncan\nnon-canonical junction penalty (in addition to scoreGap)\ninteger, example: -8\n\n\n--scoreGapGCAG\nGC/AG and CT/GC junction penalty (in addition to scoreGap)\ninteger, example: -4\n\n\n--scoreGapATAC\nAT/AC and GT/AT junction penalty (in addition to scoreGap)\ninteger, example: -8\n\n\n--scoreGenomicLengthLog2scale\nextra score logarithmically scaled with genomic length of the alignment: scoreGenomicLengthLog2scale*log2(genomicLength)\ninteger, example: 0\n\n\n--scoreDelOpen\ndeletion open penalty\ninteger, example: -2\n\n\n--scoreDelBase\ndeletion extension penalty per base (in addition to scoreDelOpen)\ninteger, example: -2\n\n\n--scoreInsOpen\ninsertion open penalty\ninteger, example: -2\n\n\n--scoreInsBase\ninsertion extension penalty per base (in addition to scoreInsOpen)\ninteger, example: -2\n\n\n--scoreStitchSJshift\nmaximum score reduction while searching for SJ boundaries in the stitching step\ninteger, example: 1\n\n\n\n\n\nAlignments and Seeding\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--seedSearchStartLmax\ndefines the search start point through the read - the read is split into pieces no longer than this value\ninteger, example: 50\n\n\n--seedSearchStartLmaxOverLread\nseedSearchStartLmax normalized to read length (sum of mates’ lengths for paired-end reads)\ndouble, example: 1\n\n\n--seedSearchLmax\ndefines the maximum length of the seeds, if =0 seed length is not limited\ninteger, example: 0\n\n\n--seedMultimapNmax\nonly pieces that map fewer than this value are utilized in the stitching procedure\ninteger, example: 10000\n\n\n--seedPerReadNmax\nmax number of seeds per read\ninteger, example: 1000\n\n\n--seedPerWindowNmax\nmax number of seeds per window\ninteger, example: 50\n\n\n--seedNoneLociPerWindow\nmax number of one seed loci per window\ninteger, example: 10\n\n\n--seedSplitMin\nmin length of the seed sequences split by Ns or mate gap\ninteger, example: 12\n\n\n--seedMapMin\nmin length of seeds to be mapped\ninteger, example: 5\n\n\n--alignIntronMin\nminimum intron size, genomic gap is considered intron if its length>=alignIntronMin, otherwise it is considered Deletion\ninteger, example: 21\n\n\n--alignIntronMax\nmaximum intron size, if 0, max intron size will be determined by (2^winBinNbits)*winAnchorDistNbins\ninteger, example: 0\n\n\n--alignMatesGapMax\nmaximum gap between two mates, if 0, max intron gap will be determined by (2^winBinNbits)*winAnchorDistNbins\ninteger, example: 0\n\n\n--alignSJoverhangMin\nminimum overhang (i.e. block size) for spliced alignments\ninteger, example: 5\n\n\n--alignSJstitchMismatchNmax\nmaximum number of mismatches for stitching of the splice junctions (-1: no limit). (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif.\ninteger, example: 0, example: -1, example: 0, example: 0\n\n\n--alignSJDBoverhangMin\nminimum overhang (i.e. block size) for annotated (sjdb) spliced alignments\ninteger, example: 3\n\n\n--alignSplicedMateMapLmin\nminimum mapped length for a read mate that is spliced\ninteger, example: 0\n\n\n--alignSplicedMateMapLminOverLmate\nalignSplicedMateMapLmin normalized to mate length\ndouble, example: 0.66\n\n\n--alignWindowsPerReadNmax\nmax number of windows per read\ninteger, example: 10000\n\n\n--alignTranscriptsPerWindowNmax\nmax number of transcripts per window\ninteger, example: 100\n\n\n--alignTranscriptsPerReadNmax\nmax number of different alignments per read to consider\ninteger, example: 10000\n\n\n--alignEndsType\ntype of read ends alignment - Local … standard local alignment with soft-clipping allowed - EndToEnd … force end-to-end read alignment, do not soft-clip - Extend5pOfRead1 … fully extend only the 5p of the read1, all other ends: local alignment - Extend5pOfReads12 … fully extend only the 5p of the both read1 and read2, all other ends: local alignment\nstring, example: \"Local\"\n\n\n--alignEndsProtrude\nallow protrusion of alignment ends, i.e. start (end) of the +strand mate downstream of the start (end) of the -strand mate 1st word: int: maximum number of protrusion bases allowed 2nd word: string: - ConcordantPair … report alignments with non-zero protrusion as concordant pairs - DiscordantPair … report alignments with non-zero protrusion as discordant pairs\nstring, example: \"0 ConcordantPair\"\n\n\n--alignSoftClipAtReferenceEnds\nallow the soft-clipping of the alignments past the end of the chromosomes - Yes … allow - No … prohibit, useful for compatibility with Cufflinks\nstring, example: \"Yes\"\n\n\n--alignInsertionFlush\nhow to flush ambiguous insertion positions - None … insertions are not flushed - Right … insertions are flushed to the right\nstring\n\n\n\n\n\nPaired-End reads\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--peOverlapNbasesMin\nminimum number of overlapping bases to trigger mates merging and realignment. Specify >0 value to switch on the “merginf of overlapping mates” algorithm.\ninteger, example: 0\n\n\n--peOverlapMMp\nmaximum proportion of mismatched bases in the overlap area\ndouble, example: 0.01\n\n\n\n\n\nWindows, Anchors, Binning\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--winAnchorMultimapNmax\nmax number of loci anchors are allowed to map to\ninteger, example: 50\n\n\n--winBinNbits\n=log2(winBin), where winBin is the size of the bin for the windows/clustering, each window will occupy an integer number of bins.\ninteger, example: 16\n\n\n--winAnchorDistNbins\nmax number of bins between two anchors that allows aggregation of anchors into one window\ninteger, example: 9\n\n\n--winFlankNbins\nlog2(winFlank), where win Flank is the size of the left and right flanking regions for each window\ninteger, example: 4\n\n\n--winReadCoverageRelativeMin\nminimum relative coverage of the read sequence by the seeds in a window, for STARlong algorithm only.\ndouble, example: 0.5\n\n\n--winReadCoverageBasesMin\nminimum number of bases covered by the seeds in a window , for STARlong algorithm only.\ninteger, example: 0\n\n\n\n\n\nChimeric Alignments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--chimOutType\ntype of chimeric output - Junctions … Chimeric.out.junction - SeparateSAMold … output old SAM into separate Chimeric.out.sam file - WithinBAM … output into main aligned BAM files (Aligned.*.bam) - WithinBAM HardClip … (default) hard-clipping in the CIGAR for supplemental chimeric alignments (default if no 2nd word is present) - WithinBAM SoftClip … soft-clipping in the CIGAR for supplemental chimeric alignments\nstring, example: \"Junctions\"\n\n\n--chimSegmentMin\nminimum length of chimeric segment length, if ==0, no chimeric output\ninteger, example: 0\n\n\n--chimScoreMin\nminimum total (summed) score of the chimeric segments\ninteger, example: 0\n\n\n--chimScoreDropMax\nmax drop (difference) of chimeric score (the sum of scores of all chimeric segments) from the read length\ninteger, example: 20\n\n\n--chimScoreSeparation\nminimum difference (separation) between the best chimeric score and the next one\ninteger, example: 10\n\n\n--chimScoreJunctionNonGTAG\npenalty for a non-GT/AG chimeric junction\ninteger, example: -1\n\n\n--chimJunctionOverhangMin\nminimum overhang for a chimeric junction\ninteger, example: 20\n\n\n--chimSegmentReadGapMax\nmaximum gap in the read sequence between chimeric segments\ninteger, example: 0\n\n\n--chimFilter\ndifferent filters for chimeric alignments - None … no filtering - banGenomicN … Ns are not allowed in the genome sequence around the chimeric junction\nstring, example: \"banGenomicN\"\n\n\n--chimMainSegmentMultNmax\nmaximum number of multi-alignments for the main chimeric segment. =1 will prohibit multimapping main segments.\ninteger, example: 10\n\n\n--chimMultimapNmax\nmaximum number of chimeric multi-alignments - 0 … use the old scheme for chimeric detection which only considered unique alignments\ninteger, example: 0\n\n\n--chimMultimapScoreRange\nthe score range for multi-mapping chimeras below the best chimeric score. Only works with –chimMultimapNmax > 1\ninteger, example: 1\n\n\n--chimNonchimScoreDropMin\nto trigger chimeric detection, the drop in the best non-chimeric alignment score with respect to the read length has to be greater than this value\ninteger, example: 20\n\n\n--chimOutJunctionFormat\nformatting type for the Chimeric.out.junction file - 0 … no comment lines/headers - 1 … comment lines at the end of the file: command line and Nreads: total, unique/multi-mapping\ninteger, example: 0\n\n\n\n\n\nQuantification of Annotations\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--quantMode\ntypes of quantification requested - - … none - TranscriptomeSAM … output SAM/BAM alignments to transcriptome into a separate file - GeneCounts … count reads per gene\nstring\n\n\n--quantTranscriptomeBAMcompression\n-2 to 10 transcriptome BAM compression level - -2 … no BAM output - -1 … default compression (6?) - 0 … no compression - 10 … maximum compression\ninteger, example: 1\n\n\n--quantTranscriptomeBan\nprohibit various alignment type - IndelSoftclipSingleend … prohibit indels, soft clipping and single-end alignments - compatible with RSEM - Singleend … prohibit single-end alignments\nstring, example: \"IndelSoftclipSingleend\"\n\n\n\n\n\n2-pass Mapping\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--twopassMode\n2-pass mapping mode. - None … 1-pass mapping - Basic … basic 2-pass mapping, with all 1st pass junctions inserted into the genome indices on the fly\nstring\n\n\n--twopass1readsN\nnumber of reads to process for the 1st step. Use very large number (or default -1) to map all reads in the first step.\ninteger, example: -1\n\n\n\n\n\nWASP parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--waspOutputMode\nWASP allele-specific output type. This is re-implementation of the original WASP mappability filtering by Bryce van de Geijn, Graham McVicker, Yoav Gilad & Jonathan K Pritchard. Please cite the original WASP paper: Nature Methods 12, 1061-1063 (2015), https://www.nature.com/articles/nmeth.3582 . - SAMtag … add WASP tags to the alignments that pass WASP filtering\nstring\n\n\n\n\n\nSTARsolo (single cell RNA-seq) parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--soloType\ntype of single-cell RNA-seq - CB_UMI_Simple … (a.k.a. Droplet) one UMI and one Cell Barcode of fixed length in read2, e.g. Drop-seq and 10X Chromium. - CB_UMI_Complex … multiple Cell Barcodes of varying length, one UMI of fixed length and one adapter sequence of fixed length are allowed in read2 only (e.g. inDrop, ddSeq). - CB_samTagOut … output Cell Barcode as CR and/or CB SAm tag. No UMI counting. –readFilesIn cDNA_read1 [cDNA_read2 if paired-end] CellBarcode_read . Requires –outSAMtype BAM Unsorted [and/or SortedByCoordinate] - SmartSeq … Smart-seq: each cell in a separate FASTQ (paired- or single-end), barcodes are corresponding read-groups, no UMI sequences, alignments deduplicated according to alignment start and end (after extending soft-clipped bases)\nstring\n\n\n--soloCBwhitelist\nfile(s) with whitelist(s) of cell barcodes. Only –soloType CB_UMI_Complex allows more than one whitelist file. - None … no whitelist: all cell barcodes are allowed\nstring\n\n\n--soloCBstart\ncell barcode start base\ninteger, example: 1\n\n\n--soloCBlen\ncell barcode length\ninteger, example: 16\n\n\n--soloUMIstart\nUMI start base\ninteger, example: 17\n\n\n--soloUMIlen\nUMI length\ninteger, example: 10\n\n\n--soloBarcodeReadLength\nlength of the barcode read - 1 … equal to sum of soloCBlen+soloUMIlen - 0 … not defined, do not check\ninteger, example: 1\n\n\n--soloBarcodeMate\nidentifies which read mate contains the barcode (CB+UMI) sequence - 0 … barcode sequence is on separate read, which should always be the last file in the –readFilesIn listed - 1 … barcode sequence is a part of mate 1 - 2 … barcode sequence is a part of mate 2\ninteger, example: 0\n\n\n--soloCBposition\nposition of Cell Barcode(s) on the barcode read. Presently only works with –soloType CB_UMI_Complex, and barcodes are assumed to be on Read2. Format for each barcode: startAnchor_startPosition_endAnchor_endPosition start(end)Anchor defines the Anchor Base for the CB: 0: read start; 1: read end; 2: adapter start; 3: adapter end start(end)Position is the 0-based position with of the CB start(end) with respect to the Anchor Base String for different barcodes are separated by space. Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 0_0_2_-1 3_1_3_8\nstring\n\n\n--soloUMIposition\nposition of the UMI on the barcode read, same as soloCBposition Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 3_9_3_14\nstring\n\n\n--soloAdapterSequence\nadapter sequence to anchor barcodes. Only one adapter sequence is allowed.\nstring\n\n\n--soloAdapterMismatchesNmax\nmaximum number of mismatches allowed in adapter sequence.\ninteger, example: 1\n\n\n--soloCBmatchWLtype\nmatching the Cell Barcodes to the WhiteList - Exact … only exact matches allowed - 1MM … only one match in whitelist with 1 mismatched base allowed. Allowed CBs have to have at least one read with exact match. - 1MM_multi … multiple matches in whitelist with 1 mismatched base allowed, posterior probability calculation is used choose one of the matches. Allowed CBs have to have at least one read with exact match. This option matches best with CellRanger 2.2.0 - 1MM_multi_pseudocounts … same as 1MM_Multi, but pseudocounts of 1 are added to all whitelist barcodes. - 1MM_multi_Nbase_pseudocounts … same as 1MM_multi_pseudocounts, multimatching to WL is allowed for CBs with N-bases. This option matches best with CellRanger >= 3.0.0 - EditDist_2 … allow up to edit distance of 3 fpr each of the barcodes. May include one deletion + one insertion. Only works with –soloType CB_UMI_Complex. Matches to multiple passlist barcdoes are not allowed. Similar to ParseBio Split-seq pipeline.\nstring, example: \"1MM_multi\"\n\n\n--soloInputSAMattrBarcodeSeq\nwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode sequence (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeSeq CR UR . This parameter is required when running STARsolo with input from SAM.\nstring\n\n\n--soloInputSAMattrBarcodeQual\nwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode qualities (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeQual CY UY . If this parameter is ‘-’ (default), the quality ‘H’ will be assigned to all bases.\nstring\n\n\n--soloStrand\nstrandedness of the solo libraries: - Unstranded … no strand information - Forward … read strand same as the original RNA molecule - Reverse … read strand opposite to the original RNA molecule\nstring, example: \"Forward\"\n\n\n--soloFeatures\ngenomic features for which the UMI counts per Cell Barcode are collected - Gene … genes: reads match the gene transcript - SJ … splice junctions: reported in SJ.out.tab - GeneFull … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns - GeneFull_ExonOverIntron … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns: prioritize 100% overlap with exons - GeneFull_Ex50pAS … full gene (pre-RNA): count all reads overlapping genes’ exons and introns: prioritize >50% overlap with exons. Do not count reads with 100% exonic overlap in the antisense direction.\nstring, example: \"Gene\"\n\n\n--soloMultiMappers\ncounting method for reads mapping to multiple genes - Unique … count only reads that map to unique genes - Uniform … uniformly distribute multi-genic UMIs to all genes - Rescue … distribute UMIs proportionally to unique+uniform counts (~ first iteration of EM) - PropUnique … distribute UMIs proportionally to unique mappers, if present, and uniformly if not. - EM … multi-gene UMIs are distributed using Expectation Maximization algorithm\nstring, example: \"Unique\"\n\n\n--soloUMIdedup\ntype of UMI deduplication (collapsing) algorithm - 1MM_All … all UMIs with 1 mismatch distance to each other are collapsed (i.e. counted once). - 1MM_Directional_UMItools … follows the “directional” method from the UMI-tools by Smith, Heger and Sudbery (Genome Research 2017). - 1MM_Directional … same as 1MM_Directional_UMItools, but with more stringent criteria for duplicate UMIs - Exact … only exactly matching UMIs are collapsed. - NoDedup … no deduplication of UMIs, count all reads. - 1MM_CR … CellRanger2-4 algorithm for 1MM UMI collapsing.\nstring, example: \"1MM_All\"\n\n\n--soloUMIfiltering\ntype of UMI filtering (for reads uniquely mapping to genes) - - … basic filtering: remove UMIs with N and homopolymers (similar to CellRanger 2.2.0). - MultiGeneUMI … basic + remove lower-count UMIs that map to more than one gene. - MultiGeneUMI_All … basic + remove all UMIs that map to more than one gene. - MultiGeneUMI_CR … basic + remove lower-count UMIs that map to more than one gene, matching CellRanger > 3.0.0 . Only works with –soloUMIdedup 1MM_CR\nstring\n\n\n--soloOutFileNames\nfile names for STARsolo output: file_name_prefix gene_names barcode_sequences cell_feature_count_matrix\nstring, example: \"Solo.out/\", example: \"features.tsv\", example: \"barcodes.tsv\", example: \"matrix.mtx\"\n\n\n--soloCellFilter\ncell filtering type and parameters - None … do not output filtered cells - TopCells … only report top cells by UMI count, followed by the exact number of cells - CellRanger2.2 … simple filtering of CellRanger 2.2. Can be followed by numbers: number of expected cells, robust maximum percentile for UMI count, maximum to minimum ratio for UMI count The harcoded values are from CellRanger: nExpectedCells=3000; maxPercentile=0.99; maxMinRatio=10 - EmptyDrops_CR … EmptyDrops filtering in CellRanger flavor. Please cite the original EmptyDrops paper: A.T.L Lun et al, Genome Biology, 20, 63 (2019): https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1662-y Can be followed by 10 numeric parameters: nExpectedCells maxPercentile maxMinRatio indMin indMax umiMin umiMinFracMedian candMaxN FDR simN The harcoded values are from CellRanger: 3000 0.99 10 45000 90000 500 0.01 20000 0.01 10000\nstring, example: \"CellRanger2.2\", example: \"3000\", example: \"0.99\", example: \"10\"\n\n\n--soloOutFormatFeaturesGeneField3\nfield 3 in the Gene features.tsv file. If “-”, then no 3rd field is output.\nstring, example: \"Gene Expression\"\n\n\n--soloCellReadStats\nOutput reads statistics for each CB - Standard … standard output\nstring" + }, + { + "objectID": "components/modules/mapping/star_align.html#authors", + "href": "components/modules/mapping/star_align.html#authors", + "title": "Star align", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/mapping/samtools_sort.html", + "href": "components/modules/mapping/samtools_sort.html", + "title": "Samtools sort", + "section": "", + "text": "ID: samtools_sort\nNamespace: mapping\n\n\n\nSource\nReads are sorted by leftmost coordinates, or by read name when --sort_by_read_names is used.\nAn appropriate @HD-SO sort order header tag will be added or an existing one updated if necessary.\nNote that to generate an index file (by specifying --output_bai), the default coordinate sort must be used. Thus the --sort_by_read_names and --sort_by <TAG> options are incompatible with --output_bai." + }, + { + "objectID": "components/modules/mapping/samtools_sort.html#example-commands", + "href": "components/modules/mapping/samtools_sort.html#example-commands", + "title": "Samtools sort", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/samtools_sort/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\nminimizer_cluster: false\n# minimizer_kmer: 20\nsort_by_read_names: false\n# sort_by: \"foo\"\nno_pg: false\n\n# Input\ninput: # please fill in - example: \"input.bam\"\n\n# Output\n# output_bam: \"$id.$key.output_bam.bam\"\n# output_bai: \"$id.$key.output_bai.bai\"\n# output_format: \"bam\"\n# compression: 5\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/samtools_sort/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/samtools_sort.html#argument-groups", + "href": "components/modules/mapping/samtools_sort.html#argument-groups", + "title": "Samtools sort", + "section": "Argument groups", + "text": "Argument groups\n\nInput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to the SAM/BAM/CRAM files containing the mapped reads.\nfile, required, example: \"input.bam\"\n\n\n\n\n\nOutput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output_bam\nFilename to output the counts to.\nfile, required, example: \"output.bam\"\n\n\n--output_bai\nBAI-format index for BAM file.\nfile, example: \"output.bam.bai\"\n\n\n--output_format\nThe output format. By default, samtools tries to select a format based on the -o filename extension; if output is to standard output or no format can be deduced, bam is selected.\nstring, example: \"bam\"\n\n\n--compression\nCompression level, from 0 (uncompressed) to 9 (best\ninteger, example: 5\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--minimizer_cluster\nSort unmapped reads (those in chromosome “*“) by their sequence minimiser (Schleimer et al., 2003; Roberts et al., 2004), also reverse complementing as appropriate. This has the effect of collating some similar data together, improving the compressibility of the unmapped sequence. The minimiser kmer size is adjusted using the -K option. Note data compressed in this manner may need to be name collated prior to conversion back to fastq. Mapped sequences are sorted by chromosome and position.\nboolean_true\n\n\n--minimizer_kmer\nSets the kmer size to be used in the -M option.\ninteger, example: 20\n\n\n--sort_by_read_names\nSort by read names (i.e., the QNAME field) rather than by chromosomal coordinates.\nboolean_true\n\n\n--sort_by\nSort first by this value in the alignment tag, then by position or name (if also using -n).\nstring\n\n\n--no_pg\nDo not add a @PG line to the header of the output file.\nboolean_true" + }, + { + "objectID": "components/modules/mapping/samtools_sort.html#authors", + "href": "components/modules/mapping/samtools_sort.html#authors", + "title": "Samtools sort", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (author, maintainer)\nAngela Oliveira Pisco (author)" + }, + { + "objectID": "components/modules/mapping/cellranger_count_split.html", + "href": "components/modules/mapping/cellranger_count_split.html", + "title": "Cellranger count split", + "section": "", + "text": "ID: cellranger_count_split\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/cellranger_count_split.html#example-commands", + "href": "components/modules/mapping/cellranger_count_split.html#example-commands", + "title": "Cellranger count split", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/cellranger_count_split/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input_dir\"\n# filtered_h5: \"$id.$key.filtered_h5.h5\"\n# metrics_summary: \"$id.$key.metrics_summary.csv\"\n# molecule_info: \"$id.$key.molecule_info.h5\"\n# bam: \"$id.$key.bam.bam\"\n# bai: \"$id.$key.bai.bai\"\n# raw_h5: \"$id.$key.raw_h5.h5\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/cellranger_count_split/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/cellranger_count_split.html#argument-group", + "href": "components/modules/mapping/cellranger_count_split.html#argument-group", + "title": "Cellranger count split", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nOutput directory from a Cell Ranger count run.\nfile, required, example: \"input_dir\"\n\n\n--filtered_h5\n\nfile, example: \"filtered_feature_bc_matrix.h5\"\n\n\n--metrics_summary\n\nfile, example: \"metrics_summary.csv\"\n\n\n--molecule_info\n\nfile, example: \"molecule_info.h5\"\n\n\n--bam\n\nfile, example: \"possorted_genome_bam.bam\"\n\n\n--bai\n\nfile, example: \"possorted_genome_bam.bam.bai\"\n\n\n--raw_h5\n\nfile, example: \"raw_feature_bc_matrix.h5\"" + }, + { + "objectID": "components/modules/mapping/cellranger_count_split.html#authors", + "href": "components/modules/mapping/cellranger_count_split.html#authors", + "title": "Cellranger count split", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nSamuel D’Souza (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/velocity/velocyto.html", + "href": "components/modules/velocity/velocyto.html", + "title": "Velocyto", + "section": "", + "text": "ID: velocyto\nNamespace: velocity\n\n\n\nSource" + }, + { + "objectID": "components/modules/velocity/velocyto.html#example-commands", + "href": "components/modules/velocity/velocyto.html#example-commands", + "title": "Velocyto", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/velocity/velocyto/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"path/to/file\"\ntranscriptome: # please fill in - example: \"path/to/file\"\n# barcode: \"path/to/file\"\nwithout_umi: false\n# output: \"$id.$key.output.output\"\nlogic: \"Default\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/velocity/velocyto/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/velocity/velocyto.html#argument-group", + "href": "components/modules/velocity/velocyto.html#argument-group", + "title": "Velocyto", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to BAM file\nfile, required\n\n\n--transcriptome\nPath to GTF file\nfile, required\n\n\n--barcode\nValid barcodes file, to filter the bam. If –bcfile is not specified all the cell barcodes will be included. Cell barcodes should be specified in the bcfile as the ‘CB’ tag for each read\nfile\n\n\n--without_umi\nfoo\nboolean_true\n\n\n--output\nVelocyto loom file\nfile, required\n\n\n--logic\nThe logic to use for the filtering.\nstring, default: \"Default\"" + }, + { + "objectID": "components/modules/velocity/velocyto.html#authors", + "href": "components/modules/velocity/velocyto.html#authors", + "title": "Velocyto", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/workflows/integration/common/harmony_leiden.html", + "href": "components/workflows/integration/common/harmony_leiden.html", + "title": "Harmony leiden", + "section": "", + "text": "ID: harmony_leiden\nNamespace: integration/common\n\n\n\nSource" + }, + { + "objectID": "components/workflows/integration/common/harmony_leiden.html#example-commands", + "href": "components/workflows/integration/common/harmony_leiden.html#example-commands", + "title": "Harmony leiden", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -main-script workflows/multiomics/integration/harmony_leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Neighbour calculation\nuns_neighbors: \"harmonypy_integration_neighbors\"\nobsp_neighbor_distances: \"harmonypy_integration_distances\"\nobsp_neighbor_connectivities: \"harmonypy_integration_connectivities\"\n\n# Harmony integration options\nembedding: \"X_pca\"\nobsm_integrated: \"X_pca_integrated\"\nobs_covariates: # please fill in - example: [\"batch\", \"sample\"]\ntheta: [2]\n\n# Clustering options\nobs_cluster: \"harmony_integration_leiden\"\nleiden_resolution: [1]\n\n# Umap options\nobsm_umap: \"X_leiden_harmony_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -profile docker \\\n -main-script workflows/multiomics/integration/harmony_leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/integration/common/harmony_leiden.html#argument-groups", + "href": "components/workflows/integration/common/harmony_leiden.html#argument-groups", + "title": "Harmony leiden", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"harmonypy_integration_neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"harmonypy_integration_distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"harmonypy_integration_connectivities\"\n\n\n\n\n\nHarmony integration options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--embedding\nEmbedding to use as input\nstring, default: \"X_pca\"\n\n\n--obsm_integrated\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_pca_integrated\"\n\n\n--obs_covariates\nThe .obs field(s) that define the covariate(s) to regress out.\nstring, required, example: \"batch\", example: \"sample\"\n\n\n--theta\nDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.”\ndouble, default: 2\n\n\n\n\n\nClustering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_cluster\nName of the .obs key under which to add the cluster labels.\nstring, default: \"harmony_integration_leiden\"\n\n\n--leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_leiden_harmony_umap\"" + }, + { + "objectID": "components/workflows/integration/common/harmony_leiden.html#authors", + "href": "components/workflows/integration/common/harmony_leiden.html#authors", + "title": "Harmony leiden", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/integration/common/harmony_leiden.html#visualisation", + "href": "components/workflows/integration/common/harmony_leiden.html#visualisation", + "title": "Harmony leiden", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p12(harmonypy)\n p22(find_neighbors)\n p32(leiden)\n p42(umap)\n p52(move_obsm_to_obs)\n p60(Output)\n p0-->p2\n p2-->p4\n p4-->p12\n p12-->p22\n p22-->p32\n p32-->p42\n p42-->p52\n p52-->p60" + }, + { + "objectID": "components/workflows/integration/initialize_integration/initialize_integration.html", + "href": "components/workflows/integration/initialize_integration/initialize_integration.html", + "title": "Initialize integration", + "section": "", + "text": "ID: initialize_integration\nNamespace: integration/initialize_integration\n\n\n\nSource" + }, + { + "objectID": "components/workflows/integration/initialize_integration/initialize_integration.html#example-commands", + "href": "components/workflows/integration/initialize_integration/initialize_integration.html#example-commands", + "title": "Initialize integration", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -main-script workflows/multiomics/integration/initialize_integration/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# PCA options\nobsm_pca: \"X_pca\"\n# var_pca_feature_selection: \"foo\"\n\n# Neighbour calculation\nuns_neighbors: \"neighbors\"\nobsp_neighbor_distances: \"distances\"\nobsp_neighbor_connectivities: \"connectivities\"\n\n# Umap options\nobsm_umap: \"X_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -profile docker \\\n -main-script workflows/multiomics/integration/initialize_integration/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/integration/initialize_integration/initialize_integration.html#argument-groups", + "href": "components/workflows/integration/initialize_integration/initialize_integration.html#argument-groups", + "title": "Initialize integration", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nPCA options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_pca\nIn which .obsm slot to store the resulting PCA embedding.\nstring, default: \"X_pca\"\n\n\n--var_pca_feature_selection\nColumn name in .var matrix that will be used to select which genes to run the PCA on.\nstring\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"connectivities\"\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_umap\"" + }, + { + "objectID": "components/workflows/integration/initialize_integration/initialize_integration.html#authors", + "href": "components/workflows/integration/initialize_integration/initialize_integration.html#authors", + "title": "Initialize integration", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/integration/initialize_integration/initialize_integration.html#visualisation", + "href": "components/workflows/integration/initialize_integration/initialize_integration.html#visualisation", + "title": "Initialize integration", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p12(pca)\n p22(find_neighbors)\n p32(umap)\n p40(Output)\n p0-->p2\n p2-->p4\n p4-->p12\n p12-->p22\n p22-->p32\n p32-->p40" + }, + { + "objectID": "components/workflows/ingestion/bd_rhapsody.html", + "href": "components/workflows/ingestion/bd_rhapsody.html", + "title": "BD Rhapsody", + "section": "", + "text": "ID: bd_rhapsody\nNamespace: ingestion\n\n\n\nSource\nA wrapper for the BD Rhapsody Analysis CWL v1.10.1 pipeline.\nThis pipeline can be used for a targeted analysis (with --mode targeted) or for a whole transcriptome analysis (with --mode wta).\nThe reference_genome and transcriptome_annotation files can be generated with the make_reference pipeline. Alternatively, BD also provides standard references which can be downloaded from these locations:" + }, + { + "objectID": "components/workflows/ingestion/bd_rhapsody.html#example-commands", + "href": "components/workflows/ingestion/bd_rhapsody.html#example-commands", + "title": "BD Rhapsody", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/ingestion/bd_rhapsody/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nmode: # please fill in - example: \"wta\"\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: [\"input.fastq.gz\"]\nreference: # please fill in - example: [\"reference_genome.tar.gz|reference.fasta\"]\n# transcriptome_annotation: \"transcriptome.gtf\"\n# abseq_reference: [\"abseq_reference.fasta\"]\n# supplemental_reference: [\"supplemental_reference.fasta\"]\nsample_prefix: \"sample\"\n\n# Outputs\n# output_raw: \"$id.$key.output_raw.output_raw\"\n# output_h5mu: \"$id.$key.output_h5mu.h5mu\"\n\n# Putative cell calling settings\n# putative_cell_call: \"mRNA\"\n# exact_cell_count: 10000\ndisable_putative_calling: false\n\n# Subsample arguments\n# subsample: 0.01\n# subsample_seed: 3445\n\n# Multiplex arguments\n# sample_tags_version: \"human\"\n# tag_names: [\"4-mySample\", \"9-myOtherSample\", \"6-alsoThisSample\"]\n\n# VDJ arguments\n# vdj_version: \"human\"\n\n# CWL-runner arguments\nparallel: true\ntimestamps: false\ndryrun: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/ingestion/bd_rhapsody/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/ingestion/bd_rhapsody.html#argument-groups", + "href": "components/workflows/ingestion/bd_rhapsody.html#argument-groups", + "title": "BD Rhapsody", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--mode\nWhether to run a whole transcriptome analysis (WTA) or a targeted analysis.\nstring, required, example: \"wta\"\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to your read files in the FASTQ.GZ format. You may specify as many R1/R2 read pairs as you want.\nfile, required, example: \"input.fastq.gz\"\n\n\n--reference\nRefence to map to. For --mode wta, this is the path to STAR index as a tar.gz file. For --mode targeted, this is the path to mRNA reference file for pre-designed, supplemental, or custom panel, in FASTA format\nfile, required, example: \"reference_genome.tar.gz|reference.fasta\"\n\n\n--transcriptome_annotation\nPath to GTF annotation file (only for --mode wta).\nfile, example: \"transcriptome.gtf\"\n\n\n--abseq_reference\nPath to the AbSeq reference file in FASTA format. Only needed if BD AbSeq Ab-Oligos are used.\nfile, example: \"abseq_reference.fasta\"\n\n\n--supplemental_reference\nPath to the supplemental reference file in FASTA format. Only needed if there are additional transgene sequences used in the experiment (only for --mode wta).\nfile, example: \"supplemental_reference.fasta\"\n\n\n--sample_prefix\nSpecify a run name to use as the output file base name. Use only letters, numbers, or hyphens. Do not use special characters or spaces.\nstring, default: \"sample\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output_raw\nThe BD Rhapsody output folder as it comes out of the BD Rhapsody pipeline\nfile, required, example: \"output_dir\"\n\n\n--output_h5mu\nThe converted h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nPutative cell calling settings\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--putative_cell_call\nSpecify the dataset to be used for putative cell calling. For putative cell calling using an AbSeq dataset, please provide an AbSeq_Reference fasta file above.\nstring, example: \"mRNA\"\n\n\n--exact_cell_count\nExact cell count - Set a specific number (>=1) of cells as putative, based on those with the highest error-corrected read count\ninteger, example: 10000\n\n\n--disable_putative_calling\nDisable Refined Putative Cell Calling - Determine putative cells using only the basic algorithm (minimum second derivative along the cumulative reads curve). The refined algorithm attempts to remove false positives and recover false negatives, but may not be ideal for certain complex mixtures of cell types. Does not apply if Exact Cell Count is set.\nboolean_true\n\n\n\n\n\nSubsample arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--subsample\nA number >1 or fraction (0 < n < 1) to indicate the number or percentage of reads to subsample.\ndouble, example: 0.01\n\n\n--subsample_seed\nA seed for replicating a previous subsampled run.\ninteger, example: 3445\n\n\n\n\n\nMultiplex arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--sample_tags_version\nSpecify if multiplexed run.\nstring, example: \"human\"\n\n\n--tag_names\nTag_Names (optional) - Specify the tag number followed by ‘-’ and the desired sample name to appear in Sample_Tag_Metrics.csv. Do not use the special characters: &, (), [], {}, <>, ?, |\nstring, example: \"4-mySample\", example: \"9-myOtherSample\", example: \"6-alsoThisSample\"\n\n\n\n\n\nVDJ arguments\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--vdj_version\nSpecify if VDJ run.\nstring, example: \"human\"\n\n\n\n\n\nCWL-runner arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--parallel\nRun jobs in parallel.\nboolean, default: TRUE\n\n\n--timestamps\nAdd timestamps to the errors, warnings, and notifications.\nboolean_true\n\n\n--dryrun\nIf true, the output directory will only contain the CWL input files, but the pipeline itself will not be executed.\nboolean_true" + }, + { + "objectID": "components/workflows/ingestion/bd_rhapsody.html#authors", + "href": "components/workflows/ingestion/bd_rhapsody.html#authors", + "title": "BD Rhapsody", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/workflows/ingestion/bd_rhapsody.html#visualisation", + "href": "components/workflows/ingestion/bd_rhapsody.html#visualisation", + "title": "BD Rhapsody", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p10(bd_rhapsody)\n p12(join)\n p20(from_bdrhap_to_h5mu)\n p22(join)\n p28(Output)\n p0-->p2\n p2-->p4\n p4-->p12\n p4-->p10\n p10-->p12\n p12-->p22\n p12-->p20\n p20-->p22\n p22-->p28" + }, + { + "objectID": "components/workflows/ingestion/conversion.html", + "href": "components/workflows/ingestion/conversion.html", + "title": "Conversion", + "section": "", + "text": "ID: conversion\nNamespace: ingestion\n\n\n\nSource" + }, + { + "objectID": "components/workflows/ingestion/conversion.html#example-commands", + "href": "components/workflows/ingestion/conversion.html#example-commands", + "title": "Conversion", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/ingestion/conversion/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: [\"input.h5mu\"]\ninput_type: # please fill in - example: \"foo\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Conversion from h5ad\n# modality: [\"foo\"]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/ingestion/conversion/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/ingestion/conversion.html#argument-groups", + "href": "components/workflows/ingestion/conversion.html#argument-groups", + "title": "Conversion", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"input.h5mu\"\n\n\n--input_type\nType of the input file\nstring, required\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nName or template for the output files.\nfile, example: \"output.h5mu\"\n\n\n\n\n\nConversion from h5ad\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--modality\nName of the modality where the h5ad is stored in the h5mu object.\nstring" + }, + { + "objectID": "components/workflows/ingestion/conversion.html#authors", + "href": "components/workflows/ingestion/conversion.html#authors", + "title": "Conversion", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author, maintainer)\nDries De Maeyer (author)" + }, + { + "objectID": "components/workflows/ingestion/conversion.html#visualisation", + "href": "components/workflows/ingestion/conversion.html#visualisation", + "title": "Conversion", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p5(filter)\n p10(from_10xh5_to_h5mu)\n p12(join)\n p35(mix)\n p15(filter)\n p20(from_10xmtx_to_h5mu)\n p22(join)\n p25(filter)\n p30(from_h5ad_to_h5mu)\n p32(join)\n p37(toSortedList)\n p39(Output)\n p4-->p5\n p4-->p15\n p4-->p25\n p0-->p2\n p2-->p4\n p5-->p12\n p5-->p10\n p10-->p12\n p12-->p35\n p15-->p22\n p15-->p20\n p20-->p22\n p22-->p35\n p25-->p32\n p25-->p30\n p30-->p32\n p32-->p35\n p35-->p37\n p37-->p39" + }, + { + "objectID": "components/workflows/ingestion/cellranger_postprocessing.html", + "href": "components/workflows/ingestion/cellranger_postprocessing.html", + "title": "Cell Ranger post-processing", + "section": "", + "text": "ID: cellranger_postprocessing\nNamespace: ingestion\n\n\n\nSource" + }, + { + "objectID": "components/workflows/ingestion/cellranger_postprocessing.html#example-commands", + "href": "components/workflows/ingestion/cellranger_postprocessing.html#example-commands", + "title": "Cell Ranger post-processing", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/ingestion/cellranger_postprocessing/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"input.h5mu\"\n\n# Outputs\n# output: \"$id.$key.output.output\"\n\n# Correction arguments\nperform_correction: false\ncellbender_epochs: 150\n\n# Filtering arguments\n# min_genes: 100\n# min_counts: 1000\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/ingestion/cellranger_postprocessing/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/ingestion/cellranger_postprocessing.html#argument-groups", + "href": "components/workflows/ingestion/cellranger_postprocessing.html#argument-groups", + "title": "Cell Ranger post-processing", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nInput h5mu file created by running Cell Ranger and converting its output to h5mu.\nfile, required, example: \"input.h5mu\"\n\n\n\n\n\nOutputs\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nThe converted h5mu file.\nfile\n\n\n\n\n\nCorrection arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--perform_correction\nWhether or not to run CellBender to perform count correction.\nboolean_true\n\n\n--cellbender_epochs\nNumber of epochs to run CellBender for.\ninteger, default: 150\n\n\n\n\n\nFiltering arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--min_genes\nMinimum number of counts required for a cell to pass filtering.\ninteger, example: 100\n\n\n--min_counts\nMinimum number of genes expressed required for a cell to pass filtering.\ninteger, example: 1000" + }, + { + "objectID": "components/workflows/ingestion/cellranger_postprocessing.html#authors", + "href": "components/workflows/ingestion/cellranger_postprocessing.html#authors", + "title": "Cell Ranger post-processing", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/workflows/ingestion/cellranger_postprocessing.html#visualisation", + "href": "components/workflows/ingestion/cellranger_postprocessing.html#visualisation", + "title": "Cell Ranger post-processing", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p6(from_10xh5_to_h5mu)\n p8(join)\n p12(toSortedList)\n p14(flatMap)\n p15(filter)\n p21(cellbender_remove_background)\n p23(join)\n p27(mix)\n p26(filter)\n p28(filter)\n p34(filter_with_counts)\n p36(join)\n p40(mix)\n p39(filter)\n p46(publish)\n p48(join)\n p54(Output)\n p14-->p15\n p14-->p26\n p26-->p27\n p27-->p28\n p27-->p39\n p39-->p40\n p0-->p8\n p0-->p6\n p6-->p8\n p8-->p12\n p12-->p14\n p15-->p23\n p15-->p21\n p21-->p23\n p23-->p27\n p28-->p36\n p28-->p34\n p34-->p36\n p36-->p40\n p40-->p48\n p40-->p46\n p46-->p48\n p48-->p54" + }, + { + "objectID": "components/workflows/multiomics/rna_multisample.html", + "href": "components/workflows/multiomics/rna_multisample.html", + "title": "Rna multisample", + "section": "", + "text": "ID: rna_multisample\nNamespace: multiomics\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/rna_multisample.html#example-commands", + "href": "components/workflows/multiomics/rna_multisample.html#example-commands", + "title": "Rna multisample", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/rna_multisample/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"concatenated\"\ninput: # please fill in - example: \"dataset.h5mu\"\n\n# Output\n# output: \"$id.$key.output.h5mu\"\n\n# Filtering highly variable genes\nfilter_with_hvg_var_output: \"filter_with_hvg\"\nfilter_with_hvg_obs_batch_key: \"sample_id\"\nfilter_with_hvg_flavor: \"seurat\"\n# filter_with_hvg_n_top_genes: 123\n\n# QC metrics calculation options\nvar_qc_metrics: [\"filter_with_hvg\"]\ntop_n_vars: [50, 100, 200, 500]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/rna_multisample/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/rna_multisample.html#argument-groups", + "href": "components/workflows/multiomics/rna_multisample.html#argument-groups", + "title": "Rna multisample", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the concatenated file\nstring, required, example: \"concatenated\"\n\n\n--input\nPath to the samples.\nfile, required, example: \"dataset.h5mu\"\n\n\n\n\n\nOutput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nFiltering highly variable genes\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--filter_with_hvg_var_output\nIn which .var slot to store a boolean array corresponding to the highly variable genes.\nstring, default: \"filter_with_hvg\"\n\n\n--filter_with_hvg_obs_batch_key\nIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method. For all flavors, genes are first sorted by how many batches they are a HVG. For dispersion-based flavors ties are broken by normalized dispersion. If flavor = ‘seurat_v3’, ties are broken by the median (across batches) rank based on within-batch normalized variance.\nstring, default: \"sample_id\"\n\n\n--filter_with_hvg_flavor\nChoose the flavor for identifying highly variable genes. For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_genes.\nstring, default: \"seurat\"\n\n\n--filter_with_hvg_n_top_genes\nNumber of highly-variable genes to keep. Mandatory if filter_with_hvg_flavor is set to ‘seurat_v3’.\ninteger\n\n\n\n\n\nQC metrics calculation options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--var_qc_metrics\nKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes.\nstring, default: \"filter_with_hvg\", example: \"ercc,highly_variable\"\n\n\n--top_n_vars\nNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.\ninteger, default: 50, default: 100, default: 200, default: 500" + }, + { + "objectID": "components/workflows/multiomics/rna_multisample.html#authors", + "href": "components/workflows/multiomics/rna_multisample.html#authors", + "title": "Rna multisample", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (author)\nRobrecht Cannoodt (author, maintainer)\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/rna_multisample.html#visualisation", + "href": "components/workflows/multiomics/rna_multisample.html#visualisation", + "title": "Rna multisample", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p3(toSortedList)\n p5(flatMap)\n p7(toSortedList)\n p9(Output)\n p15(normalize_total)\n p17(join)\n p25(log1p)\n p27(join)\n p35(delete_layer)\n p37(join)\n p45(filter_with_hvg)\n p47(join)\n p55(rna_calculate_qc_metrics)\n p57(join)\n p64(Output)\n p0-->p3\n p3-->p5\n p5-->p7\n p7-->p9\n p5-->p17\n p5-->p15\n p15-->p17\n p17-->p27\n p17-->p25\n p25-->p27\n p27-->p37\n p27-->p35\n p35-->p37\n p37-->p47\n p37-->p45\n p45-->p47\n p47-->p57\n p47-->p55\n p55-->p57\n p57-->p64" + }, + { + "objectID": "components/workflows/multiomics/prot_singlesample.html", + "href": "components/workflows/multiomics/prot_singlesample.html", + "title": "Prot singlesample", + "section": "", + "text": "ID: prot_singlesample\nNamespace: multiomics\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/prot_singlesample.html#example-commands", + "href": "components/workflows/multiomics/prot_singlesample.html#example-commands", + "title": "Prot singlesample", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/prot_singlesample/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Input\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\n\n# Output\n# output: \"$id.$key.output.h5mu\"\n\n# Filtering options\n# min_counts: 200\n# max_counts: 5000000\n# min_proteins_per_cell: 200\n# max_proteins_per_cell: 1500000\n# min_cells_per_protein: 3\n# min_fraction_mito: 0\n# max_fraction_mito: 0.2\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/prot_singlesample/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/prot_singlesample.html#argument-groups", + "href": "components/workflows/multiomics/prot_singlesample.html#argument-groups", + "title": "Prot singlesample", + "section": "Argument groups", + "text": "Argument groups\n\nInput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n\n\n\nOutput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nFiltering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--min_counts\nMinimum number of counts captured per cell.\ninteger, example: 200\n\n\n--max_counts\nMaximum number of counts captured per cell.\ninteger, example: 5000000\n\n\n--min_proteins_per_cell\nMinimum of non-zero values per cell.\ninteger, example: 200\n\n\n--max_proteins_per_cell\nMaximum of non-zero values per cell.\ninteger, example: 1500000\n\n\n--min_cells_per_protein\nMinimum of non-zero values per gene.\ninteger, example: 3\n\n\n--min_fraction_mito\nMinimum fraction of proteins that are mitochondrial.\ndouble, example: 0\n\n\n--max_fraction_mito\nMaximum fraction of proteins that are mitochondrial.\ndouble, example: 0.2" + }, + { + "objectID": "components/workflows/multiomics/prot_singlesample.html#authors", + "href": "components/workflows/multiomics/prot_singlesample.html#authors", + "title": "Prot singlesample", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (author)\nRobrecht Cannoodt (author, maintainer)\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/prot_singlesample.html#visualisation", + "href": "components/workflows/multiomics/prot_singlesample.html#visualisation", + "title": "Prot singlesample", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p3(toSortedList)\n p5(flatMap)\n p12(filter_with_counts)\n p14(join)\n p22(do_filter)\n p24(join)\n p30(toSortedList)\n p32(Output)\n p0-->p3\n p3-->p5\n p5-->p14\n p5-->p12\n p12-->p14\n p14-->p24\n p14-->p22\n p22-->p24\n p24-->p30\n p30-->p32" + }, + { + "objectID": "components/workflows/multiomics/integration/initialize_integration.html", + "href": "components/workflows/multiomics/integration/initialize_integration.html", + "title": "Initialize integration", + "section": "", + "text": "ID: initialize_integration\nNamespace: multiomics/integration\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/integration/initialize_integration.html#example-commands", + "href": "components/workflows/multiomics/integration/initialize_integration.html#example-commands", + "title": "Initialize integration", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/integration/initialize_integration/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# PCA options\nobsm_pca: \"X_pca\"\n# var_pca_feature_selection: \"foo\"\npca_overwrite: false\n\n# Neighbour calculation\nuns_neighbors: \"neighbors\"\nobsp_neighbor_distances: \"distances\"\nobsp_neighbor_connectivities: \"connectivities\"\n\n# Umap options\nobsm_umap: \"X_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/integration/initialize_integration/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/integration/initialize_integration.html#argument-groups", + "href": "components/workflows/multiomics/integration/initialize_integration.html#argument-groups", + "title": "Initialize integration", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nPCA options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_pca\nIn which .obsm slot to store the resulting PCA embedding.\nstring, default: \"X_pca\"\n\n\n--var_pca_feature_selection\nColumn name in .var matrix that will be used to select which genes to run the PCA on.\nstring\n\n\n--pca_overwrite\nAllow overwriting slots for PCA output.\nboolean_true\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"connectivities\"\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_umap\"" + }, + { + "objectID": "components/workflows/multiomics/integration/initialize_integration.html#authors", + "href": "components/workflows/multiomics/integration/initialize_integration.html#authors", + "title": "Initialize integration", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/integration/initialize_integration.html#visualisation", + "href": "components/workflows/multiomics/integration/initialize_integration.html#visualisation", + "title": "Initialize integration", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p11(pca)\n p13(join)\n p21(find_neighbors)\n p23(join)\n p31(umap)\n p33(join)\n p38(toSortedList)\n p40(Output)\n p0-->p2\n p2-->p4\n p4-->p13\n p4-->p11\n p11-->p13\n p13-->p23\n p13-->p21\n p21-->p23\n p23-->p33\n p23-->p31\n p31-->p33\n p33-->p38\n p38-->p40" + }, + { + "objectID": "components/workflows/multiomics/integration/bbknn_leiden.html", + "href": "components/workflows/multiomics/integration/bbknn_leiden.html", + "title": "Bbknn leiden", + "section": "", + "text": "ID: bbknn_leiden\nNamespace: multiomics/integration\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/integration/bbknn_leiden.html#example-commands", + "href": "components/workflows/multiomics/integration/bbknn_leiden.html#example-commands", + "title": "Bbknn leiden", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/integration/bbknn_leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Bbknn\nobsm_input: \"X_pca\"\nobs_batch: \"sample_id\"\nuns_output: \"bbknn_integration_neighbors\"\nobsp_distances: \"bbknn_integration_distances\"\nobsp_connectivities: \"bbknn_integration_connectivities\"\nn_neighbors_within_batch: 3\nn_pcs: 50\n# n_trim: 123\n\n# Clustering options\nobs_cluster: \"bbknn_integration_leiden\"\nleiden_resolution: 1\n\n# UMAP options\nobsm_umap: \"X_leiden_bbknn_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/integration/bbknn_leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/integration/bbknn_leiden.html#argument-groups", + "href": "components/workflows/multiomics/integration/bbknn_leiden.html#argument-groups", + "title": "Bbknn leiden", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nBbknn\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_input\nThe dimensionality reduction in .obsm to use for neighbour detection. Defaults to X_pca.\nstring, default: \"X_pca\"\n\n\n--obs_batch\n.obs column name discriminating between your batches.\nstring, default: \"sample_id\"\n\n\n--uns_output\nMandatory .uns slot to store various neighbor output objects.\nstring, default: \"bbknn_integration_neighbors\"\n\n\n--obsp_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"bbknn_integration_distances\"\n\n\n--obsp_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"bbknn_integration_connectivities\"\n\n\n--n_neighbors_within_batch\nHow many top neighbours to report for each batch; total number of neighbours in the initial k-nearest-neighbours computation will be this number times the number of batches.\ninteger, default: 3\n\n\n--n_pcs\nHow many dimensions (in case of PCA, principal components) to use in the analysis.\ninteger, default: 50\n\n\n--n_trim\nTrim the neighbours of each cell to these many top connectivities. May help with population independence and improve the tidiness of clustering. The lower the value the more independent the individual populations, at the cost of more conserved batch effect. If None (default), sets the parameter value automatically to 10 times neighbors_within_batch times the number of batches. Set to 0 to skip.\ninteger\n\n\n\n\n\nClustering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_cluster\nPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.\nstring, default: \"bbknn_integration_leiden\"\n\n\n--leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUMAP options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_leiden_bbknn_umap\"" + }, + { + "objectID": "components/workflows/multiomics/integration/bbknn_leiden.html#authors", + "href": "components/workflows/multiomics/integration/bbknn_leiden.html#authors", + "title": "Bbknn leiden", + "section": "Authors", + "text": "Authors\n\nMauro Saporita (author)\nPovilas Gibas (author)" + }, + { + "objectID": "components/workflows/multiomics/integration/bbknn_leiden.html#visualisation", + "href": "components/workflows/multiomics/integration/bbknn_leiden.html#visualisation", + "title": "Bbknn leiden", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p10(bbknn)\n p12(join)\n p20(leiden)\n p22(join)\n p30(umap)\n p32(join)\n p40(move_obsm_to_obs)\n p42(join)\n p48(Output)\n p0-->p2\n p2-->p4\n p4-->p12\n p4-->p10\n p10-->p12\n p12-->p22\n p12-->p20\n p20-->p22\n p22-->p32\n p22-->p30\n p30-->p32\n p32-->p42\n p32-->p40\n p40-->p42\n p42-->p48" + }, + { + "objectID": "components/workflows/multiomics/integration/leiden_scvi.html", + "href": "components/workflows/multiomics/integration/leiden_scvi.html", + "title": "Leiden scvi", + "section": "", + "text": "ID: leiden_scvi\nNamespace: multiomics/integration\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/integration/leiden_scvi.html#example-commands", + "href": "components/workflows/multiomics/integration/leiden_scvi.html#example-commands", + "title": "Leiden scvi", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/integration/scvi_leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_model: \"$id.$key.output_model.output_model\"\n\n# Neighbour calculation\nuns_neighbors: \"scvi_integration_neighbors\"\nobsp_neighbor_distances: \"scvi_integration_distances\"\nobsp_neighbor_connectivities: \"scvi_integration_connectivities\"\n\n# Scvi integration options\nobs_batch: # please fill in - example: \"foo\"\nobsm_output: \"X_scvi_integrated\"\n# early_stopping: true\nearly_stopping_monitor: \"elbo_validation\"\nearly_stopping_patience: 45\nearly_stopping_min_delta: 0.0\n# max_epochs: 123\nreduce_lr_on_plateau: true\nlr_factor: 0.6\nlr_patience: 30\n\n# Clustering options\nobs_cluster: \"scvi_integration_leiden\"\nleiden_resolution: [1]\n\n# Umap options\nobsm_umap: \"X_scvi_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/integration/scvi_leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/integration/leiden_scvi.html#argument-groups", + "href": "components/workflows/multiomics/integration/leiden_scvi.html#argument-groups", + "title": "Leiden scvi", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n--output_model\nFolder where the state of the trained model will be saved to.\nfile, required, example: \"output_dir\"\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"scvi_integration_neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"scvi_integration_distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"scvi_integration_connectivities\"\n\n\n\n\n\nScvi integration options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_batch\nColumn name discriminating between your batches.\nstring, required\n\n\n--obsm_output\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_scvi_integrated\"\n\n\n--early_stopping\nWhether to perform early stopping with respect to the validation set.\nboolean\n\n\n--early_stopping_monitor\nMetric logged during validation set epoch.\nstring, default: \"elbo_validation\"\n\n\n--early_stopping_patience\nNumber of validation epochs with no improvement after which training will be stopped.\ninteger, default: 45\n\n\n--early_stopping_min_delta\nMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.\ndouble, default: 0\n\n\n--max_epochs\nNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.\ninteger\n\n\n--reduce_lr_on_plateau\nWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.\nboolean, default: TRUE\n\n\n--lr_factor\nFactor to reduce learning rate.\ndouble, default: 0.6\n\n\n--lr_patience\nNumber of epochs with no improvement after which learning rate will be reduced.\ndouble, default: 30\n\n\n\n\n\nClustering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_cluster\nPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.\nstring, default: \"scvi_integration_leiden\"\n\n\n--leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_scvi_umap\"" + }, + { + "objectID": "components/workflows/multiomics/integration/leiden_scvi.html#authors", + "href": "components/workflows/multiomics/integration/leiden_scvi.html#authors", + "title": "Leiden scvi", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/integration/leiden_scvi.html#visualisation", + "href": "components/workflows/multiomics/integration/leiden_scvi.html#visualisation", + "title": "Leiden scvi", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p3(toSortedList)\n p5(flatMap)\n p12(scvi)\n p14(join)\n p23(find_neighbors)\n p25(join)\n p33(leiden)\n p35(join)\n p43(umap)\n p45(join)\n p53(move_obsm_to_obs)\n p55(join)\n p62(Output)\n p0-->p3\n p3-->p5\n p5-->p14\n p5-->p12\n p12-->p14\n p14-->p25\n p14-->p23\n p23-->p25\n p25-->p35\n p25-->p33\n p33-->p35\n p35-->p45\n p35-->p43\n p43-->p45\n p45-->p55\n p45-->p53\n p53-->p55\n p55-->p62" + }, + { + "objectID": "components/workflows/multiomics/prot_multisample.html", + "href": "components/workflows/multiomics/prot_multisample.html", + "title": "Prot multisample", + "section": "", + "text": "ID: prot_multisample\nNamespace: multiomics\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/prot_multisample.html#example-commands", + "href": "components/workflows/multiomics/prot_multisample.html#example-commands", + "title": "Prot multisample", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/prot_multisample/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"concatenated\"\ninput: # please fill in - example: \"dataset.h5mu\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# QC metrics calculation options\ntop_n_vars: [50, 100, 200, 500]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/prot_multisample/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/prot_multisample.html#argument-groups", + "href": "components/workflows/multiomics/prot_multisample.html#argument-groups", + "title": "Prot multisample", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the concatenated file\nstring, required, example: \"concatenated\"\n\n\n--input\nPath to the samples.\nfile, required, example: \"dataset.h5mu\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nQC metrics calculation options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--top_n_vars\nNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.\ninteger, default: 50, default: 100, default: 200, default: 500" + }, + { + "objectID": "components/workflows/multiomics/prot_multisample.html#authors", + "href": "components/workflows/multiomics/prot_multisample.html#authors", + "title": "Prot multisample", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/prot_multisample.html#visualisation", + "href": "components/workflows/multiomics/prot_multisample.html#visualisation", + "title": "Prot multisample", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p3(toSortedList)\n p5(flatMap)\n p7(toSortedList)\n p9(Output)\n p15(clr)\n p17(join)\n p25(prot_calculate_qc_metrics)\n p27(join)\n p34(Output)\n p0-->p3\n p3-->p5\n p5-->p7\n p7-->p9\n p5-->p17\n p5-->p15\n p15-->p17\n p17-->p27\n p17-->p25\n p25-->p27\n p27-->p34" + }, + { + "objectID": "components/workflows/multiomics/rna_singlesample.html", + "href": "components/workflows/multiomics/rna_singlesample.html", + "title": "Rna singlesample", + "section": "", + "text": "ID: rna_singlesample\nNamespace: multiomics\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/rna_singlesample.html#example-commands", + "href": "components/workflows/multiomics/rna_singlesample.html#example-commands", + "title": "Rna singlesample", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/rna_singlesample/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Input\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\n\n# Output\n# output: \"$id.$key.output.h5mu\"\n\n# Filtering options\n# min_counts: 200\n# max_counts: 5000000\n# min_genes_per_cell: 200\n# max_genes_per_cell: 1500000\n# min_cells_per_gene: 3\n# min_fraction_mito: 0\n# max_fraction_mito: 0.2\n\n# Mitochondrial gene detection\n# var_name_mitochondrial_genes: \"foo\"\n# var_gene_names: \"gene_symbol\"\nmitochondrial_gene_regex: \"^[mM][tT]-\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/rna_singlesample/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/rna_singlesample.html#argument-groups", + "href": "components/workflows/multiomics/rna_singlesample.html#argument-groups", + "title": "Rna singlesample", + "section": "Argument groups", + "text": "Argument groups\n\nInput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n\n\n\nOutput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nFiltering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--min_counts\nMinimum number of counts captured per cell.\ninteger, example: 200\n\n\n--max_counts\nMaximum number of counts captured per cell.\ninteger, example: 5000000\n\n\n--min_genes_per_cell\nMinimum of non-zero values per cell.\ninteger, example: 200\n\n\n--max_genes_per_cell\nMaximum of non-zero values per cell.\ninteger, example: 1500000\n\n\n--min_cells_per_gene\nMinimum of non-zero values per gene.\ninteger, example: 3\n\n\n--min_fraction_mito\nMinimum fraction of UMIs that are mitochondrial.\ndouble, example: 0\n\n\n--max_fraction_mito\nMaximum fraction of UMIs that are mitochondrial.\ndouble, example: 0.2\n\n\n\n\n\nMitochondrial gene detection\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--var_name_mitochondrial_genes\nIn which .var slot to store a boolean array corresponding the mitochondrial genes.\nstring\n\n\n--var_gene_names\n.var column name to be used to detect mitochondrial genes instead of .var_names (default if not set). Gene names matching with the regex value from –mitochondrial_gene_regex will be identified as a mitochondrial gene.\nstring, example: \"gene_symbol\"\n\n\n--mitochondrial_gene_regex\nRegex string that identifies mitochondrial genes from –var_gene_names. By default will detect human and mouse mitochondrial genes from a gene symbol.\nstring, default: \"^[mM][tT]-\"" + }, + { + "objectID": "components/workflows/multiomics/rna_singlesample.html#authors", + "href": "components/workflows/multiomics/rna_singlesample.html#authors", + "title": "Rna singlesample", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (author)\nRobrecht Cannoodt (author, maintainer)\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/rna_singlesample.html#visualisation", + "href": "components/workflows/multiomics/rna_singlesample.html#visualisation", + "title": "Rna singlesample", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p3(toSortedList)\n p5(flatMap)\n p12(filter_with_counts)\n p14(join)\n p22(do_filter)\n p24(join)\n p32(filter_with_scrublet)\n p34(join)\n p42(Output)\n p0-->p3\n p3-->p5\n p5-->p14\n p5-->p12\n p12-->p14\n p14-->p24\n p14-->p22\n p22-->p24\n p24-->p34\n p24-->p32\n p32-->p34\n p34-->p42" + }, + { + "objectID": "user_guide/bug_reports.html", + "href": "user_guide/bug_reports.html", + "title": "Bug reports", + "section": "", + "text": "Issues with Openpipelines are being tracked on Github. In order for an issue to be fixed in a timely manner, creating a complete and reproducable is essential." + }, + { + "objectID": "user_guide/running_pipelines.html", + "href": "user_guide/running_pipelines.html", + "title": "Running pipelines", + "section": "", + "text": "Note\n\n\n\nTODO: Fill in these sections.\n\nExamples should be using an OpenPipelines release or the main_build branch.\nPoint to the “Components” tab\n\n\n\n\nInstalling Viash and Nextflow\nBefore you try running OpenPipelines, please install Viash and Nextflow first.\n\nRunning pipelines from the CLI\nbin/nextflow run . \\\n -main-script workflows/integration/multimodal_integration/main.nf \\\n -profile docker \\\n -resume \n --publish_dir foo/\n --input \"bar\"\n --output \"test.txt\"\n\n\nRunning pipelines from Nextflow Tower\n\n\nUsing param_list to pass large parameter sets\nUsing Viash’s VDSL3 nextflow platform, an optional -param_list argument can be used to pass a large number of inputs to a workflow. Additionally, the pipeline parameter values can be set for each input to the workflow independently. A param_list can either be a list of maps, a csv file, a json file, a yaml file, or simply a yaml blob:\n\nA csv file should have column names which correspond to the different arguments of this pipeline. Example: --param_list data.csv with columns id,input.\nA json or a yaml file should be a list of maps, each of which has keys corresponding to the arguments of the pipeline. Example: --param_list data.json with contents [ {'id': 'foo', 'input': 'foo.txt'}, {'id': 'bar', 'input': 'bar.txt'} ].\nA yaml blob can also be passed directly as a string. Example: --param_list \"[ {'id': 'foo', 'input': 'foo.txt'}, {'id': 'bar', 'input': 'bar.txt'} ]\".\nA list of maps can be in a nextflow.config file, where the keys of each map corresponds to the arguments of the pipeline. Example in a nextflow.config file: param_list: [ ['id': 'foo', 'input': 'foo.txt'], ['id': 'bar', 'input': 'bar.txt'] ].\n\nWhen passing a csv, json or yaml file, relative path names are relativized to the location of the parameter file. No relativation is performed when param_list is a list of maps (as-is) or a yaml blob.\nUsing a param_list can be combined with setting parameters that are set for all parameter sets. These ‘gobal’ parameters will always be overwritten with their counterpart that was specified in a more specific manner for a single parameter set. For example, using --param_list \"[ {'id': 'foo', 'input': 'foo.txt'}, {'id': 'bar'} ]\" --input 'global.txt' will result in the following parameter sets being processed:\n\nid: foo, input: foo.txt\nid: bar, input: global.txt" + }, + { + "objectID": "user_guide/index.html#using-the-nf-tower-user-interface", + "href": "user_guide/index.html#using-the-nf-tower-user-interface", + "title": "User Guide", + "section": "Using the nf-tower user-interface", + "text": "Using the nf-tower user-interface" + }, + { + "objectID": "user_guide/index.html#using-the-nf-tower-cli-tw", + "href": "user_guide/index.html#using-the-nf-tower-cli-tw", + "title": "User Guide", + "section": "Using the nf-tower CLI (tw)", + "text": "Using the nf-tower CLI (tw)" + }, + { + "objectID": "user_guide/index.html#using-the-nextflow-cli", + "href": "user_guide/index.html#using-the-nextflow-cli", + "title": "User Guide", + "section": "Using the nextflow CLI", + "text": "Using the nextflow CLI" + }, + { + "objectID": "fundamentals/roadmap.html", + "href": "fundamentals/roadmap.html", + "title": "Roadmap", + "section": "", + "text": "flowchart LR\n classDef done fill:#a3f6cf,stroke:#000000;\n classDef wip fill:#f4cb93,stroke:#000000;\n classDef unprocessed fill:#afadff,stroke:#000000;\n\n Raw1[Sample 1] --> Split1[/Split\\nmodalities/]:::done --> ProcGEX1 & ProcRNAV1 & ProcADT1 & ProcATAC1 & ProcVDJ1\n ProcGEX1[/Process GEX\\nprofile/]:::done --> ConcatGEX[/Concatenate\\nprofiles/]:::done --> ProcGEX[/Process GEX\\nprofiles/]:::done\n ProcRNAV1[/Process RNAV\\nprofile/]:::wip --> ConcatRNAV[/Concatenate\\nprofiles/]:::done --> ProcRNAV[/Process RNAV\\nprofiles/]:::wip\n ProcADT1[/Process ADT\\nprofile/]:::done --> ConcatADT[/Concatenate\\nprofiles/]:::done --> ProcADT[/Process ADT\\nprofiles/]:::done\n ProcATAC1[/Process ATAC\\nprofile/]:::unprocessed --> ConcatATAC[/Concatenate\\nprofiles/]:::done --> ProcATAC[/Process ATAC\\nprofiles/]:::unprocessed\n ProcVDJ1[/Process VDJ\\nprofile/]:::unprocessed --> ConcatVDJ[/Concatenate\\nprofiles/]:::done --> ProcVDJ[/Process VDJ\\nprofiles/]:::unprocessed\n ProcGEX & ProcRNAV & ProcADT & ProcATAC & ProcVDJ --> Merge[/Merge\\nmodalities/]:::done --> SetupIntegration[/Setup\\nintegration/]:::done --> Integration[/Integration/]:::done\n\n\nFigure 1: Status of implemented components. Green: implemented, orange: work in progress, purple: modality included in output but unprocessed,\nGEX: Gene-expression. RNAV: RNA Velocity. ADT: Antibody-Derived Tags. ATAC: Assay for Transposase-Accessible Chromatin." + }, + { + "objectID": "fundamentals/architecture.html", + "href": "fundamentals/architecture.html", + "title": "Architecture", + "section": "", + "text": "OpenPipeline is a pipeline for the processing of multimodal single-cell data that scales to a great many of samples. Covering the architecture requires us to explain many angles, including: what the expected inputs and outputs are for each workflow are, how do the workflows relate to each other, and what the state of the data is at each step of the pipeline. Here is an overview of the general steps involved in processing sequencing data into a single integrated object. We will discuss each of the steps further below.\nflowchart TD \n ingest[\"Ingestion\"] --> split --> unimodalsinglesample[\"Unimodal Single Sample Processing\"] --> concat --> unimodalmultisample[\"Unimodal Multi Sample Processing\"] --> merging --> integation_setup[\"Integration Setup\"] --> integration[\"Integration\"] --> downstreamprocessing[\"Downstream Processing\"]\n\n\nFigure 1: Overview of the steps included in OpenPipeline for the analysis of single cell multiomics data." + }, + { + "objectID": "fundamentals/architecture.html#ingestion-workflows", + "href": "fundamentals/architecture.html#ingestion-workflows", + "title": "Architecture", + "section": "Ingestion workflows", + "text": "Ingestion workflows\nAll of the following workflows from the ingestion namespace have been discussed in more detail in the ingestion section:\n\ningestion/bd_rhapsody\ningestion/cellranger_mapping\ningestion/cellranger_multi\ningestion/demux\ningestion/make_reference" + }, + { + "objectID": "fundamentals/architecture.html#multiomics-workflows", + "href": "fundamentals/architecture.html#multiomics-workflows", + "title": "Architecture", + "section": "Multiomics workflows", + "text": "Multiomics workflows\nThere exists no singlesample workflow. However, the prot_singlesample and rna_singlesample pipelines do exist and they map identically to the functionality described in the single-sample antibody capture processing and single-sample gene expression processing sections respectively. If you would like to process your samples as described in the unimodal single sample processing section, you can execute both workflows in tandem for the two modalities.\nContrary to the workflows for single sample processing, there exists a multiomics/multisample workflow. However this workflow is not just the multiomics/prot_multisample and multiomics/rna_multisample workflows that have been combined. Instead, it combines the multiomics/prot_multisample, multiomics/rna_multisample and multiomics/integration/initialize_integration workflows. The purpose of this pipeline is to provide an extra ‘entrypoint’ into the full pipeline that skips the singlesample processing, allowing reprocessing samples that have already been processed before. A popular usecase is to manually select one or more celltypes which need to be processed again or the integration of observations from multiple experiments into a single dataset. Keep in mind that concatenation is not included in the multisample pipeline, so when multiple input files are specified they are processed in parallel. If you would like to integrate multiple experiments, you need to first concatenate them in a seperate step:" + }, + { + "objectID": "fundamentals/architecture.html#the-full-pipeline", + "href": "fundamentals/architecture.html#the-full-pipeline", + "title": "Architecture", + "section": "The “full” pipeline", + "text": "The “full” pipeline\nThe name of this pipeline is a bit of a misnomer, because it does not include all the steps from ingestion to integration. As will be discussed in the ingestion section, which ingestion strategy you need is dependant on your technology provider and the chosen platform. For integration, there exist many methods and combination of methods, and you may wish to choose which integration methods are applicable for your usecase. As a consequence, these two stages in the analysis of single-cell need to be executed seperatly and not as part of a single unified pipeline. All other steps outlined below on the other hand are included into the “full” pipeline, which can therefore be summarized in the following figure:\n\n\n\n\n\nflowchart TD \n split --> unimodalsinglesample[\"Unimodal Single Sample Processing\"] --> concat --> unimodalmultisample[\"Unimodal Multi Sample Processing\"] --> merging --> integation_setup\n\n\nFigure 2: Overview of the steps included in the full pipelines from OpenPipeline." + }, + { + "objectID": "fundamentals/architecture.html#integration-workflows", + "href": "fundamentals/architecture.html#integration-workflows", + "title": "Architecture", + "section": "Integration workflows", + "text": "Integration workflows\nFor each of the integration methods (and their optional combination with other tools), a seperate pipeline is defined. More information for each of the pipelines is available in the integration methods section.\n\nmultiomics/integration/bbknn_leiden\nmultiomics/integration/harmony_leiden\nmultiomics/integration/scanorama_leiden\nmultiomics/integration/scvi_leiden\nmultiomics/integration/totalvi_leiden\nmultiomics/integration/initialize_integration" + }, + { + "objectID": "fundamentals/architecture.html#sec-splitting", + "href": "fundamentals/architecture.html#sec-splitting", + "title": "Architecture", + "section": "Splitting modalities", + "text": "Splitting modalities\nWe refer to splitting modalities when multimodal MuData file is split into several unimodal MuData files. The number of output files is equal to the number of modalities present in the input file. Splitting the modalities works on MuData files containing data for multiple samples or for single-sample files." + }, + { + "objectID": "fundamentals/architecture.html#sec-merging", + "href": "fundamentals/architecture.html#sec-merging", + "title": "Architecture", + "section": "Merging of modalities", + "text": "Merging of modalities\nMerging refers to combining multiple files with data for one modality into a single output file that contains all input modalities. It is the inverse operation of splitting the modalities." + }, + { + "objectID": "fundamentals/architecture.html#concatenation-of-samples", + "href": "fundamentals/architecture.html#concatenation-of-samples", + "title": "Architecture", + "section": "Concatenation of samples", + "text": "Concatenation of samples\nJoining of observations for different samples, stored in their respective MuData file, into a single MuData file for all samples together is called sample concatenation. In practice, this operation is performed for each modality separately. An extra column (with default name sample_id) is added to the annotation of the observations (.obs) to indicate where each observation originated from.\n\n\n\n\n\n\nSpecial care must be taken when considering annotations for observations and features while concatenating the samples. Indeed, the data from different samples can contain conflicting information. Openpipeline’s concat component provides an argument other_axis_mode that allows a user to specify what happens when conflicting information is found. The move option for this argument is the default behavior. In this mode, each annotation column (from .obs and .var) is compared across samples. When no conflicts are found or the column is unique for a sample, the column is added output object. When a conflict does occur, all of the columns are gathered from the samples and stored into a dataframe. This dataframe is then stored into .obsm for annotations for the observations and .varm for feature annotations. This way, a user can have a look at the conflicts and decide what to do with them." + }, + { + "objectID": "fundamentals/architecture.html#creating-a-transcriptomics-reference", + "href": "fundamentals/architecture.html#creating-a-transcriptomics-reference", + "title": "Architecture", + "section": "Creating a transcriptomics reference", + "text": "Creating a transcriptomics reference\nMapping reads from the FASTQ files to features requires a reference that needs to be provided to the mapping component. Depending on the usecase, you might even need to provide references specific for the modalities that you are trying to analyze. For gene expression data, the reference is a reference genome, together with its appropriate gene annotation. A genome reference is often indexed in order to improve the mapping speed. Additionally, some mapping frameworks provided by the single-cell technology providers require extra preprocessing of the reference before they can be used with their worklow. OpenPipelines provides a make_reference that allows you to create references in many formats which can be used to map your reads to." + }, + { + "objectID": "fundamentals/architecture.html#sec-single-sample-gex", + "href": "fundamentals/architecture.html#sec-single-sample-gex", + "title": "Architecture", + "section": "Single-sample Gene Expression Processing", + "text": "Single-sample Gene Expression Processing\nSingle-sample gene expression processing involves two steps: removing cells based on count statistics and flagging observations originating from doublets.\nThe removal of cells based on basic count statistics is split up into two parts: first, cells are flagged for removal by filter_with_counts. It flags observations based on several thresholds:\n\nThe number of genes that have a least a single count. Both a maximum and minimum number of genes for a cell to be removed can be specified.\nThe percentage of read counts that originated from a mitochodrial genes. Cells can be filtered based on both a maximum or minimum fraction of mitochondrial genes.\nThe minimum or maximum total number of counts captured per cell. Cells with 0 total counts are always removed.\n\nFlagging cells for removal involved adding a boolean column to the .obs dataframe. After the cells have been flagged for removal, the cells are actually filtered using do_filter, which reads the values in .obs and removed the cells labeled True. This applies the general phylosophy of “separation of concerns”: one component is responsible for labeling the cells, another for removing them. This keeps the codebase for a single component small and its functionality testable.\nThe next and final step in the single-sample gene expression processing is doublet detection using filter_with_scrublet. Like filter_with_counts, it will not remove cells but add a column to .obs (which have the name filter_with_scrublet by default). The single-sample GEX workflow will not remove not be removed during the processing (hence no do_filter). However, you can choose to remove them yourself before doing your analyses by applying a filter with the column in .obs yourself." + }, + { + "objectID": "fundamentals/architecture.html#sec-single-sample-adt", + "href": "fundamentals/architecture.html#sec-single-sample-adt", + "title": "Architecture", + "section": "Single-sample Antibody Capture Processing", + "text": "Single-sample Antibody Capture Processing\nThe process of filtering antibody capture data is similar to the filtering in the single-sample gene-expression processing, but without doublet detection. In some particular cases you can use your ADT data to perform doublet detection using for example cell-type maskers. More information can be found in the single-cell best practices book." + }, + { + "objectID": "fundamentals/architecture.html#multisample-gene-expression-processing", + "href": "fundamentals/architecture.html#multisample-gene-expression-processing", + "title": "Architecture", + "section": "Multisample Gene Expression Processing", + "text": "Multisample Gene Expression Processing\nProcessing multisample gene expression involved the following steps:\n\nNormalization: Normalization aims to adjust the raw counts in the dataset for variable sampling effects by scaling the observable variance to a specified range. There are different ways to transform the data, but the normalization method is to make sure each observation (cell) has a total count equal to the median of total counts over all genes for observations (cells) before normalization.\nLog transformation: Calculates \\(X = ln(X + 1)\\), which converts multiplicative relative changes to additive differences. This allows for interpreting the gene expression in terms of relative, rather than absolute, abundances of genes.\nHighly variable gene detection: Detects genes that have a large change in expression between samples. By default, OpenPipeline uses the method from Seurat (Satija et al.). As with other “filtering” components, the filter_with_hvg component does not remove features, but rather annotates genes of interest by adding a boolean column to .var.\nQC metric calculations" + }, + { + "objectID": "fundamentals/architecture.html#multisample-antibody-capture-processing", + "href": "fundamentals/architecture.html#multisample-antibody-capture-processing", + "title": "Architecture", + "section": "Multisample Antibody Capture Processing", + "text": "Multisample Antibody Capture Processing\nProcessing the ADT modality for multiple samples" + }, + { + "objectID": "fundamentals/architecture.html#sec-dimensionality-reduction", + "href": "fundamentals/architecture.html#sec-dimensionality-reduction", + "title": "Architecture", + "section": "Dimensionality Reduction", + "text": "Dimensionality Reduction\nscRNA-seq is a high-throughput sequencing technology that produces datasets with high dimensions in the number of cells and genes. It is true that the data should provide more information, but it also contains more noise and redudant information, making it harder to distill the usefull information. The number of genes and cells can already reduced by gene filtering, but further reduction is a necessity for downstream analysis. Dimensionality reduction projects high-dimensional data into a lower dimensional space (like taking a photo (2D) of some 3D structure). The lower dimensional representation still captures the underlying information of the data, while having fewer dimensions.\nSeveral dimensionality reduction methods have been developed and applied to single-cell data analysis. Two of which are being applied in OpenPipeline:\n\nPrincipal Component Analysis (PCA): PCA reduces the dimension of a dataset by creating a new set of variables (principal components, PCs) from a linear combination of the original features in such a way that they are as uncorrelated as possible. The PCs can be ranked in the order by which they explain the largest variability in the original dataset. By keeping the top n PCs, the PCs with the lowest variance are discarded to effectively reduce the dimensionality of the data without losing information.\nUniform manifold approximation and projection (UMAP): a non-linear dimensionality technique. It constructs a high dimensional graph representation of the dataset and optimizes the low-dimensional graph representation to be structurally as similar as possible to the original graph. In a review by Xiang et al., 2021 it showed the highest stability and separates best the original cell populations.\nt-SNE is another popular non-linear, graph based dimensionality technique which is very similar to UMAP, but it has not yet been implemented in OpenPipeline." + }, + { + "objectID": "fundamentals/architecture.html#sec-initializing-integration", + "href": "fundamentals/architecture.html#sec-initializing-integration", + "title": "Architecture", + "section": "Initializing integration", + "text": "Initializing integration\nAs will be descibed in more details later on, many integration methods exist and therefore there is no single integration which is executed by default. However, there are common tasks which are run before integration either because they provide required input for many downstream integration methods or because they popular steps that would otherwise be done manually. These operations are executed by default when using the “full pipeline” as part of the initialize_integration subworkflow.\nPCA is used to reduce the dimensionality of the dataset as described previously. Find Neighbors and Leiden Clustering are useful for the identification of cell types or states in the data. Here we apply a popular method to accomplish this is to first calculate a neighborhood graph on a low dimensinonal representation of the data and then cluster the data based on similarity between data points. Finally, UMAP allows us to visualise the clusters by reducing the dimensionality of the data while still providing an accurate representation of the underlying cell population structure." + }, + { + "objectID": "fundamentals/architecture.html#sec-integration-methods", + "href": "fundamentals/architecture.html#sec-integration-methods", + "title": "Architecture", + "section": "Integration Methods", + "text": "Integration Methods\nIntegration is the alignment of cell types across samples. There exist three different types of integration methods, based on the degree of integration across modalities:\n\nUnimodal integration across batches. For example: scVI, scanorama, harmony\nMultimodal integration across batches and modalities. Can be used to integrate joint-profiling data where multiple modalities are measured. For example: totalVI\nMosaic integration: data integration across batches and modalities where not all cells are profiled in all modalities and it may be the case that no cells contain profiles in all integrated modalities. Mosaic integration methods have not been made available in OpenPipeline yet. An example of a tool that performs mosaic integration is StabMap.\n\nIn either of the three cases, concatenated samples are required, and merged modalities preferred. A plethora of integration methods exist, which in turn interact with other functionality (like clustering and dimensionality reduction methods) to generate a large number of possible usecases which one pipeline cannot cover in an easy manner. Therefore, there is no single integration step that is part of a global pipeline which is executed by default. Instead, a user can choose from the integration workflows provided, and ‘stack’ integration methods by adding the outputs to different output slots of the MuData object. The following sections will descibe the integration workflows that are available in OpenPipeline.\n\nUnimodal integration\nFor unimodal integration, scVI, scanorama and harmony have been added to the scvi_leiden, scanorama_leiden, and harmony_leiden workflows respectively. After executing the integration methods themselves, Find Neighbors and Leiden Clustering are run the results of the integration as wel as UMAP in order to be able to visualise the results. The functioning of these components has already been described here.\n\n\n\n\n\n\n\n\nMultimodal Integration\nA single multimodal integration method is currently avaiable in OpenPipeline: totalVI. It allows using information from both the gene-expression data and the antibody-capture data together to integrate the cell types. As with the other integration workflows, after running totalVI, Find Neighbors, Leiden Clustering and UMAP are run on the result. However in this case the three components are executed on both of the integrated modalities." + }, + { + "objectID": "fundamentals/concepts.html", + "href": "fundamentals/concepts.html", + "title": "Concepts", + "section": "", + "text": "Goals\nOpenPipelines strives to provide easy ways to interact with the pipeline and/or codebase for three types of users:\n\nPipeline executor: runs the pipeline from a GUI side\nPipeline editor: adapts pipelines with existing components for specific projects\nComponent developer: develops novel components and or pipelines\n\nThis means that openpipelines must be:\n\nUsable by non-experts\nEasy to deploy\nProvide reproducable results\nScalable\nEasy to maintain and adapt\n\n\n\nRequirements\nTo meet these demands, the following concepts have been implemented at the core of Openpipeline:\n\n🌍 A language independent framework\n💾 A versitile storage solution\n🔳 Modularity\n🔀 A best-practice pipeline layout\n⌛ Versioning\n✅ Automatic testing\n💬 Community input\n📺 A graphical interace\n\n\n\nA common file format: AnnData and MuData 💾\nOne of the core principals of OpenPipelines is to use MuData as a common data format throughout the whole pipeline. This means that the input and output for most components and workflows will be a MuData file and converters from and to other common data formats are provided to improve compatibility with up-and downstream applications. Choosing a common data format greatly diminishes the development complexity because it facilitates interfacing between different tools in a pipeline without needing to convert multiple times.\nMuData is a format to store annotated multimodal data. It is derived from the AnnData format. If you are unfamiliar with AnnData or MuData, it is recommended to read up on AnnData first as it is the unimodal counterpart of MuData. MuData can be roughly described as collection of several AnnData objects (stored as a associative array in the .mod attribute). MuData provides a hierarchical way to store the data:\nMuData\n├─ .mod\n│ ├─ modality_1 (AnnData Object)\n│ ├─ .X\n│ ├─ .layers\n│ ├─ layer_1 \n│ ├─ ...\n│ ├─ .var\n│ ├─ .obs\n│ ├─ .obsm\n│ ├─ .varm\n│ ├─ .uns\n│ ├─ modality_2 (AnnData Object)\n├─ .var\n├─ .obs\n├─ .obms\n├─ .varm\n├─ .uns\n\n.mod: an associative array of AnnData objects. Used in OpenPipelines to store the different modalities (CITE-seq, RNA abundance, …)\n.X and .layers: matrices storing the measurements with the columns being the variables measured and the rows being the observations (cells in most cases).\n.var: metadata for the variables (i.e. annotation for the columns of .X or any matrix in .layers). The number of rows in the .var datafame (or the length of each entry in the dictionairy) is equal to the number of columns in the measurement matrices.\n.obs: metadata for the observations (i.e. annotation for the rows of .X or any matrix in .layers). The number of rows in the .obs datafame (or the length of each entry in the dictionairy) is equal to the number of rows in the measurement matrices.\nvarm: the multi-dimensional variable annotation. A key-dataframe mapping where the number of rows in each dataframe is equal to the number of columns in the measurement matrices.\nobsm: the multi-dimensional observation annotation. A key-dataframe mapping where the number of rows in each dataframe is equal to the number of rows in the measurement matrices.\n.uns: A mapping where no restrictions are enforced on the dimensions of the data.\n\n\n\nModularity and a language independent framework 🔳\nTODO\n\n\nA graphical interface 📺\nTODO" + }, + { + "objectID": "index.html", + "href": "index.html", + "title": "OpenPipelines", + "section": "", + "text": "Fundamentals\n \n \n \n \n Philosophy\n \n \n \n \n Concepts\n \n \n \n \n Architecture\n \n \n \n \n Roadmap\n \n \n \n\nNo matching items\n\n\n\n\n\n \n User Guide\n \n \n \n \n Getting started\n \n \n \n \n Ingestion\n \n \n \n \n Processing\n \n \n \n \n Running pipelines\n \n \n \n \n Downstream\n \n \n \n \n Bug reports\n \n \n \n\nNo matching items\n\n\n\n\n\n \n Contributing\n \n \n \n \n Getting started\n \n \n \n \n Project structure\n \n \n \n \n Creating components\n \n \n \n \n Creating pipelines\n \n \n \n \n Running tests\n \n \n \n \n Publishing your changes\n \n \n \n\nNo matching items\n\n\n\n\n\n \n More information\n \n \n \n \n Cheat sheets\n \n \n \n \n Code of conduct\n \n \n \n \n Data API\n \n \n \n \n FAQ\n \n \n \n\nNo matching items" + }, + { + "objectID": "fundamentals/philosophy.html", + "href": "fundamentals/philosophy.html", + "title": "Philosophy", + "section": "", + "text": "Mission\nOpenPipelines are best-practice living workflows for single-cell uni- and multi-omics data. Building a best-practice pipeline requires knowledge and time that not one single person can provide, but rather requires input from a community. Additionally, a best-pratice pipeline needs constant maintenance to keep up to date with the latest standards, ideally sourcing input from a ‘living’ benchmark. Continuous improvement necessitates a robust system for sourcing and applying community input both from a technical and organisational standpoint.\n\n\n\n\ngraph TB\n ben[\"🌱📈 Living benchmarks\"]\n pra[\"🌱📖 Living best practices\"]\n pip[\"🌱⚙️ Living reproducible pipelines\"]\n ben --> pra --> pip" + }, + { + "objectID": "more_information/data_api.html", + "href": "more_information/data_api.html", + "title": "Data API", + "section": "", + "text": "Note\n\n\n\nFile formats are being discussed in openpipelines-bio/openpipeline#102" + }, + { + "objectID": "more_information/data_api.html#dataset", + "href": "more_information/data_api.html#dataset", + "title": "Data API", + "section": "Dataset", + "text": "Dataset\nobs:\n index # cell id\n sample\n cell_type\n organism\n tissue\n\nmod:\n rna:\n rnav:\n prot:\n atac:\n vdj:" + }, + { + "objectID": "more_information/data_api.html#rna-modality", + "href": "more_information/data_api.html#rna-modality", + "title": "Data API", + "section": "RNA modality", + "text": "RNA modality\nmod:\n rna:\n layers:\n counts\n normalized\n obs:\n <qc metrics>\n doublet_score\n doublet_bool\n cluster\n var:\n index # feature_id, preferably an ensembl id\n feature_name\n <qc metrics>\n highly_variable\n highly_variable_score\n obsm:\n X_pca\n X_integrated\n X_umap\n annotation # scvi, bbknn, ...\n obsp:\n connectivities\n distances" + }, + { + "objectID": "more_information/data_api.html#adt-modality", + "href": "more_information/data_api.html#adt-modality", + "title": "Data API", + "section": "ADT modality", + "text": "ADT modality\nmod:\n prot:\n layers:\n counts\n var:\n index # feature_id\n feature_name # Associated protein names" + }, + { + "objectID": "more_information/data_api.html#vdj-modality", + "href": "more_information/data_api.html#vdj-modality", + "title": "Data API", + "section": "VDJ modality", + "text": "VDJ modality\nmod:\n vdj:\n obsm:\n vdj_t\n vdj_b" + }, + { + "objectID": "more_information/data_api.html#atac-modality", + "href": "more_information/data_api.html#atac-modality", + "title": "Data API", + "section": "ATAC modality", + "text": "ATAC modality\nmod:\n atac:\n layers:\n counts\n var:\n interval" + }, + { + "objectID": "more_information/data_api.html#rna-velocity-modality", + "href": "more_information/data_api.html#rna-velocity-modality", + "title": "Data API", + "section": "RNA velocity modality", + "text": "RNA velocity modality\nmod:\n rnav:\n layers:\n spliced\n unspliced" + }, + { + "objectID": "components/index.html", + "href": "components/index.html", + "title": "Components", + "section": "", + "text": "Order By\n Default\n \n Name\n \n \n \n \n \n \n \n\n\n\n\n\nName\n\n\nNamespace\n\n\nDescription\n\n\n\n\n\n\nWorkflows\n\n\n \n\n\n\n\n\n\n\nBD Rhapsody\n\n\nIngestion\n\n\nA generic pipeline for running BD Rhapsody WTA or Targeted mapping, with support for AbSeq, VDJ and/or SMK.\n\n\n\n\nBbknn leiden\n\n\nMultiomics/integration\n\n\nRun bbknn followed by leiden clustering and run umap on the result.\n\n\n\n\nCell Ranger mapping\n\n\nIngestion\n\n\nA pipeline for running Cell Ranger mapping.\n\n\n\n\nCell Ranger multi\n\n\nIngestion\n\n\nA pipeline for running Cell Ranger multi.\n\n\n\n\nCell Ranger post-processing\n\n\nIngestion\n\n\nPost-processing Cell Ranger datasets.\n\n\n\n\nConversion\n\n\nIngestion\n\n\nA pipeline to convert different file formats to .h5mu.\n\n\n\n\nDemux\n\n\nIngestion\n\n\nA generic pipeline for running bcl2fastq, bcl-convert or Cell Ranger mkfastq.\n\n\n\n\nFull pipeline\n\n\nMultiomics\n\n\nA pipeline to analyse multiple multiomics samples.\n\n\n\n\nHarmony leiden\n\n\nIntegration/common\n\n\nRun harmony integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nHarmony leiden\n\n\nMultiomics/integration\n\n\nRun harmony integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nInitialize integration\n\n\nIntegration/initialize integration\n\n\nRun calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP.\n\n\n\n\nInitialize integration\n\n\nMultiomics/integration\n\n\nRun calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP.\n\n\n\n\nIntegration\n\n\nMultiomics\n\n\nA pipeline for demultiplexing multimodal multi-sample RNA transcriptomics data.\n\n\n\n\nLeiden scvi\n\n\nMultiomics/integration\n\n\nRun scvi integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nMake reference\n\n\nIngestion\n\n\nBuild a transcriptomics reference into one of many formats\n\n\n\n\nMultisample\n\n\nMultiomics\n\n\nThis workflow serves as an entrypoint into the ‘full_pipeline’ in order to re-run the multisample processing and the integration setup.\n\n\n\n\nProt multisample\n\n\nMultiomics\n\n\nProcessing unimodal multi-sample ADT data.\n\n\n\n\nProt singlesample\n\n\nMultiomics\n\n\nProcessing unimodal single-sample CITE-seq data.\n\n\n\n\nRna multisample\n\n\nMultiomics\n\n\nProcessing unimodal multi-sample RNA transcriptomics data.\n\n\n\n\nRna singlesample\n\n\nMultiomics\n\n\nProcessing unimodal single-sample RNA transcriptomics data.\n\n\n\n\nScanorama leiden\n\n\nIntegration/scanorama leiden\n\n\nRun scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nScanorama leiden\n\n\nMultiomics/integration\n\n\nRun scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nScvi\n\n\nIntegration/scvi\n\n\nRun scvi integration followed by neighbour calculations and run umap on the result.\n\n\n\n\nTotalvi leiden\n\n\nMultiomics/integration\n\n\nRun totalVI integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\n\nNo matching items" + }, + { + "objectID": "components/index.html#workflows", + "href": "components/index.html#workflows", + "title": "Components", + "section": "", + "text": "Order By\n Default\n \n Name\n \n \n \n \n \n \n \n\n\n\n\n\nName\n\n\nNamespace\n\n\nDescription\n\n\n\n\n\n\nWorkflows\n\n\n \n\n\n\n\n\n\n\nBD Rhapsody\n\n\nIngestion\n\n\nA generic pipeline for running BD Rhapsody WTA or Targeted mapping, with support for AbSeq, VDJ and/or SMK.\n\n\n\n\nBbknn leiden\n\n\nMultiomics/integration\n\n\nRun bbknn followed by leiden clustering and run umap on the result.\n\n\n\n\nCell Ranger mapping\n\n\nIngestion\n\n\nA pipeline for running Cell Ranger mapping.\n\n\n\n\nCell Ranger multi\n\n\nIngestion\n\n\nA pipeline for running Cell Ranger multi.\n\n\n\n\nCell Ranger post-processing\n\n\nIngestion\n\n\nPost-processing Cell Ranger datasets.\n\n\n\n\nConversion\n\n\nIngestion\n\n\nA pipeline to convert different file formats to .h5mu.\n\n\n\n\nDemux\n\n\nIngestion\n\n\nA generic pipeline for running bcl2fastq, bcl-convert or Cell Ranger mkfastq.\n\n\n\n\nFull pipeline\n\n\nMultiomics\n\n\nA pipeline to analyse multiple multiomics samples.\n\n\n\n\nHarmony leiden\n\n\nIntegration/common\n\n\nRun harmony integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nHarmony leiden\n\n\nMultiomics/integration\n\n\nRun harmony integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nInitialize integration\n\n\nIntegration/initialize integration\n\n\nRun calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP.\n\n\n\n\nInitialize integration\n\n\nMultiomics/integration\n\n\nRun calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP.\n\n\n\n\nIntegration\n\n\nMultiomics\n\n\nA pipeline for demultiplexing multimodal multi-sample RNA transcriptomics data.\n\n\n\n\nLeiden scvi\n\n\nMultiomics/integration\n\n\nRun scvi integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nMake reference\n\n\nIngestion\n\n\nBuild a transcriptomics reference into one of many formats\n\n\n\n\nMultisample\n\n\nMultiomics\n\n\nThis workflow serves as an entrypoint into the ‘full_pipeline’ in order to re-run the multisample processing and the integration setup.\n\n\n\n\nProt multisample\n\n\nMultiomics\n\n\nProcessing unimodal multi-sample ADT data.\n\n\n\n\nProt singlesample\n\n\nMultiomics\n\n\nProcessing unimodal single-sample CITE-seq data.\n\n\n\n\nRna multisample\n\n\nMultiomics\n\n\nProcessing unimodal multi-sample RNA transcriptomics data.\n\n\n\n\nRna singlesample\n\n\nMultiomics\n\n\nProcessing unimodal single-sample RNA transcriptomics data.\n\n\n\n\nScanorama leiden\n\n\nIntegration/scanorama leiden\n\n\nRun scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nScanorama leiden\n\n\nMultiomics/integration\n\n\nRun scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\nScvi\n\n\nIntegration/scvi\n\n\nRun scvi integration followed by neighbour calculations and run umap on the result.\n\n\n\n\nTotalvi leiden\n\n\nMultiomics/integration\n\n\nRun totalVI integration followed by neighbour calculations, leiden clustering and run umap on the result.\n\n\n\n\n\nNo matching items" + }, + { + "objectID": "components/index.html#modules", + "href": "components/index.html#modules", + "title": "Components", + "section": "Modules", + "text": "Modules\n\n\n \n \n \n Order By\n Default\n \n Name\n \n \n \n \n \n \n \n\n\n\n\n\nName\n\n\nNamespace\n\n\nDescription\n\n\n\n\n\n\nModules\n\n\n \n\n\n\n\n\n\n\nAdd id\n\n\nMetadata\n\n\nAdd id of .obs.\n\n\n\n\nBD Rhapsody\n\n\nMapping\n\n\nA wrapper for the BD Rhapsody Analysis CWL v1.10.1 pipeline\n\n\n\n\nBbknn\n\n\nNeighbors\n\n\nBBKNN network generation\n\n\n\n\nBcl convert\n\n\nDemux\n\n\nConvert bcl files to fastq files using bcl-convert.\n\n\n\n\nBcl2fastq\n\n\nDemux\n\n\nConvert bcl files to fastq files using bcl2fastq\n\n\n\n\nBuild bdrhap reference\n\n\nReference\n\n\nCompile a reference into a STAR index compatible with the BD Rhapsody pipeline.\n\n\n\n\nBuild cellranger reference\n\n\nReference\n\n\nBuild a Cell Ranger-compatible reference folder from user-supplied genome FASTA and gene GTF files.\n\n\n\n\nCalculate qc metrics\n\n\nQc\n\n\nAdd basic quality control metrics to an .h5mu file.\n\n\n\n\nCellbender remove background\n\n\nCorrection\n\n\nEliminating technical artifacts from high-throughput single-cell RNA sequencing data.\n\n\n\n\nCellbender remove background v0 2\n\n\nCorrection\n\n\nEliminating technical artifacts from high-throughput single-cell RNA sequencing data.\n\n\n\n\nCellranger count\n\n\nMapping\n\n\nAlign fastq files using Cell Ranger count.\n\n\n\n\nCellranger count split\n\n\nMapping\n\n\nSplit 10x Cell Ranger output directory into separate output fields.\n\n\n\n\nCellranger mkfastq\n\n\nDemux\n\n\nDemultiplex raw sequencing data\n\n\n\n\nCellranger multi\n\n\nMapping\n\n\nAlign fastq files using Cell Ranger multi.\n\n\n\n\nCellxgene census\n\n\nQuery\n\n\nQuery CellxGene Census or user-specified TileDBSoma object, and eventually fetch cell and gene metadata or/and expression counts.\n\n\n\n\nClr\n\n\nTransform\n\n\nPerform CLR normalization on CITE-seq data (Stoeckius et al., 2017)\n\n\n\n\nCompress h5mu\n\n\nCompression\n\n\nCompress a MuData file.\n\n\n\n\nConcat\n\n\nDataflow\n\n\nConcatenates several uni-modal samples in .h5mu files into a single file\n\n\n\n\nDelete layer\n\n\nTransform\n\n\nDelete an anndata layer from one or more modalities\n\n\n\n\nDo filter\n\n\nFilter\n\n\nRemove observations and variables based on specified .obs and .var columns\n\n\n\n\nDownload file\n\n\nDownload\n\n\nDownload a file\n\n\n\n\nFastqc\n\n\nQc\n\n\nFastqc component, please see https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.\n\n\n\n\nFilter 10xh5\n\n\nProcess 10xh5\n\n\nFilter a 10x h5 dataset\n\n\n\n\nFilter with counts\n\n\nFilter\n\n\nFilter scRNA-seq data based on the primary QC metrics.\n\n\n\n\nFilter with hvg\n\n\nFilter\n\n\nAnnotate highly variable genes [Satija15] [Zheng17] [Stuart19].\n\n\n\n\nFilter with scrublet\n\n\nFilter\n\n\nDoublet detection using the Scrublet method (Wolock, Lopez and Klein, 2019).\n\n\n\n\nFind neighbors\n\n\nNeighbors\n\n\nCompute a neighborhood graph of observations [McInnes18].\n\n\n\n\nFrom 10xh5 to h5mu\n\n\nConvert\n\n\nConverts a 10x h5 into an h5mu file\n\n\n\n\nFrom 10xmtx to h5mu\n\n\nConvert\n\n\nConverts a 10x mtx into an h5mu file\n\n\n\n\nFrom bd to 10x molecular barcode tags\n\n\nConvert\n\n\nConvert the molecular barcode sequence SAM tag from BD format (MA) to 10X format (UB)\n\n\n\n\nFrom bdrhap to h5mu\n\n\nConvert\n\n\nConvert the output of a BD Rhapsody WTA pipeline to a MuData h5 file\n\n\n\n\nFrom cellranger multi to h5mu\n\n\nConvert\n\n\nConverts the output from cellranger multi to a single .h5mu file.\n\n\n\n\nFrom h5ad to h5mu\n\n\nConvert\n\n\nConverts a single layer h5ad file into a single MuData object\n\n\n\n\nFrom h5mu to h5ad\n\n\nConvert\n\n\nConverts a h5mu file into a h5ad file\n\n\n\n\nHarmonypy\n\n\nIntegrate\n\n\nPerforms Harmony integration based as described in https://github.com/immunogenomics/harmony.\n\n\n\n\nHtseq count\n\n\nMapping\n\n\nQuantify gene expression for subsequent testing for differential expression.\n\n\n\n\nHtseq count to h5mu\n\n\nMapping\n\n\nConvert the htseq table to a h5mu\n\n\n\n\nJoin csv\n\n\nMetadata\n\n\nJoin a csv containing metadata to the .obs or .var field of a mudata file.\n\n\n\n\nJoin uns to obs\n\n\nMetadata\n\n\nJoin a data frame of length 1 (1 row index value) in .uns containing metadata to the .obs of a mudata file.\n\n\n\n\nKnn\n\n\nLabels transfer\n\n\nPerforms label transfer from reference to query using KNN classifier\n\n\n\n\nLeiden\n\n\nCluster\n\n\nCluster cells using the Leiden algorithm [Traag18] implemented in the Scanpy framework [Wolf18].\n\n\n\n\nLianapy\n\n\nInterpret\n\n\nPerforms LIANA integration based as described in https://github.com/saezlab/liana-py\n\n\n\n\nLog1p\n\n\nTransform\n\n\nLogarithmize the data matrix.\n\n\n\n\nMake params\n\n\nFiles\n\n\nLooks for files in a directory and turn it in a params file.\n\n\n\n\nMake reference\n\n\nReference\n\n\nPreprocess and build a transcriptome reference.\n\n\n\n\nMerge\n\n\nDataflow\n\n\nCombine one or more single-modality .h5mu files together into one .h5mu file\n\n\n\n\nMermaid\n\n\nReport\n\n\nGenerates a network from mermaid code\n\n\n\n\nMove obsm to obs\n\n\nMetadata\n\n\nMove a matrix from .obsm to .obs.\n\n\n\n\nMulti star\n\n\nMapping\n\n\nAlign fastq files using STAR.\n\n\n\n\nMulti star to h5mu\n\n\nMapping\n\n\nConvert the output of multi_star to a h5mu\n\n\n\n\nMultiqc\n\n\nQc\n\n\nMultiQC aggregates results from bioinformatics analyses across many samples into a single report.\n\n\n\n\nNormalize total\n\n\nTransform\n\n\nNormalize counts per cell.\n\n\n\n\nPca\n\n\nDimred\n\n\nComputes PCA coordinates, loadings and variance decomposition.\n\n\n\n\nPopv\n\n\nAnnotate\n\n\nPerforms popular major vote cell typing on single cell sequence data using multiple algorithms.\n\n\n\n\nPublish\n\n\nTransfer\n\n\nPublish an artifact and optionally rename with parameters\n\n\n\n\nRegress out\n\n\nTransform\n\n\nRegress out (mostly) unwanted sources of variation.\n\n\n\n\nRemove modality\n\n\nFilter\n\n\nRemove a modality from a .h5mu file\n\n\n\n\nSamtools sort\n\n\nMapping\n\n\nSort and (optionally) index alignments.\n\n\n\n\nScale\n\n\nTransform\n\n\nScale data to unit variance and zero mean\n\n\n\n\nScanorama\n\n\nIntegrate\n\n\nUse Scanorama to integrate different experiments\n\n\n\n\nScarches\n\n\nIntegrate\n\n\nPerforms reference mapping with scArches\n\n\n\n\nScvelo\n\n\nVelocity\n\n\n\n\n\n\n\nScvi\n\n\nIntegrate\n\n\nPerforms scvi integration as done in the human lung cell atlas https://github.com/LungCellAtlas/HLCA\n\n\n\n\nSplit modalities\n\n\nDataflow\n\n\nSplit the modalities from a single .h5mu multimodal sample into seperate .h5mu files.\n\n\n\n\nStar align\n\n\nMapping\n\n\nAlign fastq files using STAR.\n\n\n\n\nStar align v273a\n\n\nMapping\n\n\nAlign fastq files using STAR.\n\n\n\n\nStar build reference\n\n\nMapping\n\n\nCreate a reference for STAR from a set of fasta files.\n\n\n\n\nSubset h5mu\n\n\nFilter\n\n\nCreate a subset of a mudata file by selecting the first number of observations\n\n\n\n\nSync test resources\n\n\nDownload\n\n\nSynchronise the test resources from s3://openpipelines-data to resources_test\n\n\n\n\nTotalvi\n\n\nIntegrate\n\n\nPerforms mapping to the reference by totalvi model: https://docs.scvi-tools.org/en/stable/tutorials/notebooks/scarches_scvi_tools.html#Reference-mapping-with-TOTALVI\n\n\n\n\nUmap\n\n\nDimred\n\n\nUMAP (Uniform Manifold Approximation and Projection) is a manifold learning technique suitable for visualizing high-dimensional data.\n\n\n\n\nVelocyto\n\n\nVelocity\n\n\nRuns the velocity analysis on a BAM file, outputting a loom file.\n\n\n\n\nVelocyto to h5mu\n\n\nConvert\n\n\nConvert a velocyto loom file to a h5mu file.\n\n\n\n\nXgboost\n\n\nLabels transfer\n\n\nPerforms label transfer from reference to query using XGBoost classifier\n\n\n\n\n\nNo matching items" + }, + { + "objectID": "components/workflows/multiomics/integration.html", + "href": "components/workflows/multiomics/integration.html", + "title": "Integration", + "section": "", + "text": "ID: integration\nNamespace: multiomics\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/integration.html#example-commands", + "href": "components/workflows/multiomics/integration.html#example-commands", + "title": "Integration", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.8.0 -latest \\\n -main-script workflows/multiomics/integration/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# PCA options\nobsm_pca: \"X_pca\"\n# var_pca_feature_selection: \"foo\"\n\n# Harmony integration options\nobsm_integrated: \"X_pca_integrated\"\nobs_covariates: # please fill in - example: [\"batch\", \"sample\"]\nrna_theta: [2]\n\n# Neighbour calculation\nuns_neighbors: \"neighbors\"\nobsp_neighbor_distances: \"distances\"\nobsp_neighbor_connectivities: \"connectivities\"\n\n# Clustering options\nobs_cluster: \"leiden\"\nleiden_resolution: 1\n\n# Umap options\nobsm_umap: \"X_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.8.0 -latest \\\n -profile docker \\\n -main-script workflows/multiomics/integration/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/integration.html#argument-groups", + "href": "components/workflows/multiomics/integration.html#argument-groups", + "title": "Integration", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nPCA options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_pca\nIn which .obsm slot to store the resulting PCA embedding.\nstring, default: \"X_pca\"\n\n\n--var_pca_feature_selection\nColumn name in .var matrix that will be used to select which genes to run the PCA on.\nstring\n\n\n\n\n\nHarmony integration options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_integrated\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_pca_integrated\"\n\n\n--obs_covariates\nThe .obs field(s) that define the covariate(s) to regress out.\nstring, required, example: \"batch\", example: \"sample\"\n\n\n--rna_theta\nDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.”\ndouble, default: 2\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"connectivities\"\n\n\n\n\n\nClustering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_cluster\nName of the .obs key under which to add the cluster labels.\nstring, default: \"leiden\"\n\n\n--leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_umap\"" + }, + { + "objectID": "components/workflows/multiomics/integration.html#authors", + "href": "components/workflows/multiomics/integration.html#authors", + "title": "Integration", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (author)\nRobrecht Cannoodt (author, maintainer)\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/integration.html#visualisation", + "href": "components/workflows/multiomics/integration.html#visualisation", + "title": "Integration", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p15(join)\n p13(pca)\n p18(filter)\n p29(concat)\n p19(filter)\n p27(join)\n p25(harmonypy)\n p38(join)\n p36(find_neighbors)\n p48(join)\n p46(leiden)\n p58(join)\n p56(umap)\n p64(Output)\n p18-->p29\n p0-->p2\n p2-->p4\n p4-->p15\n p4-->p13\n p13-->p15\n p15-->p18\n p15-->p19\n p19-->p27\n p19-->p25\n p25-->p27\n p27-->p29\n p29-->p38\n p29-->p36\n p36-->p38\n p38-->p48\n p38-->p46\n p46-->p48\n p48-->p58\n p48-->p56\n p56-->p58\n p58-->p64" + }, + { + "objectID": "components/workflows/multiomics/full_pipeline.html", + "href": "components/workflows/multiomics/full_pipeline.html", + "title": "Full pipeline", + "section": "", + "text": "ID: full_pipeline\nNamespace: multiomics\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/full_pipeline.html#example-commands", + "href": "components/workflows/multiomics/full_pipeline.html#example-commands", + "title": "Full pipeline", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/full_pipeline/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"input.h5mu\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Sample ID options\nadd_id_to_obs: true\nadd_id_obs_output: \"sample_id\"\nadd_id_make_observation_keys_unique: true\n\n# RNA filtering options\n# rna_min_counts: 200\n# rna_max_counts: 5000000\n# rna_min_genes_per_cell: 200\n# rna_max_genes_per_cell: 1500000\n# rna_min_cells_per_gene: 3\n# rna_min_fraction_mito: 0\n# rna_max_fraction_mito: 0.2\n\n# CITE-seq filtering options\n# prot_min_counts: 3\n# prot_max_counts: 5000000\n# prot_min_proteins_per_cell: 200\n# prot_max_proteins_per_cell: 100000000\n# prot_min_cells_per_protein: 3\n\n# Highly variable gene detection\nfilter_with_hvg_var_output: \"filter_with_hvg\"\nfilter_with_hvg_obs_batch_key: \"sample_id\"\n\n# Mitochondrial Gene Detection\n# var_name_mitochondrial_genes: \"foo\"\n# var_gene_names: \"gene_symbol\"\nmitochondrial_gene_regex: \"^[mM][tT]-\"\n\n# QC metrics calculation options\n# var_qc_metrics: [\"ercc\", \"highly_variable\"]\ntop_n_vars: [50, 100, 200, 500]\n\n# PCA options\npca_overwrite: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/full_pipeline/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/full_pipeline.html#argument-groups", + "href": "components/workflows/multiomics/full_pipeline.html#argument-groups", + "title": "Full pipeline", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"input.h5mu\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nSample ID options\nOptions for adding the id to .obs on the MuData object. Having a sample id present in a requirement of several components for this pipeline.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--add_id_to_obs\nAdd the value passed with –id to .obs.\nboolean, default: TRUE\n\n\n--add_id_obs_output\n.Obs column to add the sample IDs to. Required and only used when –add_id_to_obs is set to ‘true’\nstring, default: \"sample_id\"\n\n\n--add_id_make_observation_keys_unique\nJoin the id to the .obs index (.obs_names). Only used when –add_id_to_obs is set to ‘true’.\nboolean, default: TRUE\n\n\n\n\n\nRNA filtering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--rna_min_counts\nMinimum number of counts captured per cell.\ninteger, example: 200\n\n\n--rna_max_counts\nMaximum number of counts captured per cell.\ninteger, example: 5000000\n\n\n--rna_min_genes_per_cell\nMinimum of non-zero values per cell.\ninteger, example: 200\n\n\n--rna_max_genes_per_cell\nMaximum of non-zero values per cell.\ninteger, example: 1500000\n\n\n--rna_min_cells_per_gene\nMinimum of non-zero values per gene.\ninteger, example: 3\n\n\n--rna_min_fraction_mito\nMinimum fraction of UMIs that are mitochondrial.\ndouble, example: 0\n\n\n--rna_max_fraction_mito\nMaximum fraction of UMIs that are mitochondrial.\ndouble, example: 0.2\n\n\n\n\n\nCITE-seq filtering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--prot_min_counts\nMinimum number of counts per cell.\ninteger, example: 3\n\n\n--prot_max_counts\nMinimum number of counts per cell.\ninteger, example: 5000000\n\n\n--prot_min_proteins_per_cell\nMinimum of non-zero values per cell.\ninteger, example: 200\n\n\n--prot_max_proteins_per_cell\nMaximum of non-zero values per cell.\ninteger, example: 100000000\n\n\n--prot_min_cells_per_protein\nMinimum of non-zero values per protein.\ninteger, example: 3\n\n\n\n\n\nHighly variable gene detection\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--filter_with_hvg_var_output\nIn which .var slot to store a boolean array corresponding to the highly variable genes.\nstring, default: \"filter_with_hvg\"\n\n\n--filter_with_hvg_obs_batch_key\nIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method.\nstring, default: \"sample_id\"\n\n\n\n\n\nMitochondrial Gene Detection\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--var_name_mitochondrial_genes\nIn which .var slot to store a boolean array corresponding the mitochondrial genes.\nstring\n\n\n--var_gene_names\n.var column name to be used to detect mitochondrial genes instead of .var_names (default if not set). Gene names matching with the regex value from –mitochondrial_gene_regex will be identified as a mitochondrial gene.\nstring, example: \"gene_symbol\"\n\n\n--mitochondrial_gene_regex\nRegex string that identifies mitochondrial genes from –var_gene_names. By default will detect human and mouse mitochondrial genes from a gene symbol.\nstring, default: \"^[mM][tT]-\"\n\n\n\n\n\nQC metrics calculation options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--var_qc_metrics\nKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes. Defaults to the combined values specified for –var_name_mitochondrial_genes and –filter_with_hvg_var_output.\nstring, example: \"ercc,highly_variable\"\n\n\n--top_n_vars\nNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.\ninteger, default: 50, default: 100, default: 200, default: 500\n\n\n\n\n\nPCA options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--pca_overwrite\nAllow overwriting slots for PCA output.\nboolean_true" + }, + { + "objectID": "components/workflows/multiomics/full_pipeline.html#authors", + "href": "components/workflows/multiomics/full_pipeline.html#authors", + "title": "Full pipeline", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author, maintainer)" + }, + { + "objectID": "components/workflows/multiomics/full_pipeline.html#visualisation", + "href": "components/workflows/multiomics/full_pipeline.html#visualisation", + "title": "Full pipeline", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p7(toSortedList)\n p9(Output)\n p11(filter)\n p17(add_id)\n p19(join)\n p23(mix)\n p22(filter)\n p25(filter)\n p30(split_modalities)\n p32(join)\n p39(concat)\n p35(filter)\n p37(test_wf:run_wf:split_modalities_workflow:splitStub)\n p40(flatMap)\n p41(filter)\n p44(toSortedList)\n p46(flatMap)\n p53(filter_with_counts)\n p55(join)\n p63(do_filter)\n p65(join)\n p73(filter_with_scrublet)\n p75(join)\n p110(concat)\n p79(filter)\n p82(toSortedList)\n p84(flatMap)\n p91(test_wf:run_wf:singlesample_processing_workflow:prot_singlesample:filter_with_counts:filter_with_counts_process1)\n p93(join)\n p101(test_wf:run_wf:singlesample_processing_workflow:prot_singlesample:do_filter:do_filter_process1)\n p103(join)\n p108(filter)\n p112(groupTuple)\n p118(concat)\n p120(join)\n p125(filter)\n p128(toSortedList)\n p130(flatMap)\n p132(toSortedList)\n p134(Output)\n p140(normalize_total)\n p142(join)\n p150(log1p)\n p152(join)\n p160(delete_layer)\n p162(join)\n p170(filter_with_hvg)\n p172(join)\n p180(rna_calculate_qc_metrics)\n p182(join)\n 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p25-->p32\n p25-->p30\n p30-->p32\n p32-->p39\n p35-->p37\n p37-->p39\n p41-->p44\n p44-->p46\n p46-->p55\n p46-->p53\n p53-->p55\n p55-->p65\n p55-->p63\n p63-->p65\n p65-->p75\n p65-->p73\n p73-->p75\n p75-->p110\n p79-->p82\n p82-->p84\n p84-->p93\n p84-->p91\n p91-->p93\n p93-->p103\n p93-->p101\n p101-->p103\n p103-->p110\n p108-->p110\n p110-->p112\n p112-->p120\n p112-->p118\n p118-->p120\n p120-->p125\n p120-->p188\n p120-->p221\n p125-->p128\n p128-->p130\n p130-->p132\n p132-->p134\n p130-->p142\n p130-->p140\n p140-->p142\n p142-->p152\n p142-->p150\n p150-->p152\n p152-->p162\n p152-->p160\n p160-->p162\n p162-->p172\n p162-->p170\n p170-->p172\n p172-->p182\n p172-->p180\n p180-->p182\n p182-->p223\n p188-->p191\n p191-->p193\n p193-->p195\n p195-->p197\n p193-->p205\n p193-->p203\n p203-->p205\n p205-->p215\n p205-->p213\n p213-->p215\n p215-->p223\n p221-->p223\n p224-->p232\n p224-->p230\n p230-->p232\n p232-->p235\n p232-->p274\n p235-->p239\n p239-->p241\n p241-->p250\n p241-->p248\n p248-->p250\n p250-->p260\n p250-->p258\n p258-->p260\n p260-->p270\n p260-->p268\n p268-->p270\n p270-->p275\n p276-->p280\n p280-->p282\n p282-->p291\n p282-->p289\n p289-->p291\n p291-->p301\n p291-->p299\n p299-->p301\n p301-->p311\n p301-->p309\n p309-->p311\n p311-->p316\n p316-->p324\n p316-->p322\n p322-->p324\n p324-->p329\n p329-->p331" + }, + { + "objectID": "components/workflows/multiomics/integration/harmony_leiden.html", + "href": "components/workflows/multiomics/integration/harmony_leiden.html", + "title": "Harmony leiden", + "section": "", + "text": "ID: harmony_leiden\nNamespace: multiomics/integration\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/integration/harmony_leiden.html#example-commands", + "href": "components/workflows/multiomics/integration/harmony_leiden.html#example-commands", + "title": "Harmony leiden", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/integration/harmony_leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Neighbour calculation\nuns_neighbors: \"harmonypy_integration_neighbors\"\nobsp_neighbor_distances: \"harmonypy_integration_distances\"\nobsp_neighbor_connectivities: \"harmonypy_integration_connectivities\"\n\n# Harmony integration options\nembedding: \"X_pca\"\nobsm_integrated: \"X_pca_integrated\"\nobs_covariates: # please fill in - example: [\"batch\", \"sample\"]\ntheta: [2]\n\n# Clustering options\nobs_cluster: \"harmony_integration_leiden\"\nleiden_resolution: [1]\n\n# Umap options\nobsm_umap: \"X_leiden_harmony_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/integration/harmony_leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/integration/harmony_leiden.html#argument-groups", + "href": "components/workflows/multiomics/integration/harmony_leiden.html#argument-groups", + "title": "Harmony leiden", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"harmonypy_integration_neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"harmonypy_integration_distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"harmonypy_integration_connectivities\"\n\n\n\n\n\nHarmony integration options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--embedding\nEmbedding to use as input\nstring, default: \"X_pca\"\n\n\n--obsm_integrated\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_pca_integrated\"\n\n\n--obs_covariates\nThe .obs field(s) that define the covariate(s) to regress out.\nstring, required, example: \"batch\", example: \"sample\"\n\n\n--theta\nDiversity clustering penalty parameter. Specify for each variable in group.by.vars. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.”\ndouble, default: 2\n\n\n\n\n\nClustering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_cluster\nPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.\nstring, default: \"harmony_integration_leiden\"\n\n\n--leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_leiden_harmony_umap\"" + }, + { + "objectID": "components/workflows/multiomics/integration/harmony_leiden.html#authors", + "href": "components/workflows/multiomics/integration/harmony_leiden.html#authors", + "title": "Harmony leiden", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/integration/harmony_leiden.html#visualisation", + "href": "components/workflows/multiomics/integration/harmony_leiden.html#visualisation", + "title": "Harmony leiden", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p10(harmonypy)\n p12(join)\n p20(find_neighbors)\n p22(join)\n p30(leiden)\n p32(join)\n p40(umap)\n p42(join)\n p50(move_obsm_to_obs)\n p52(join)\n p58(Output)\n p0-->p2\n p2-->p4\n p4-->p12\n p4-->p10\n p10-->p12\n p12-->p22\n p12-->p20\n p20-->p22\n p22-->p32\n p22-->p30\n p30-->p32\n p32-->p42\n p32-->p40\n p40-->p42\n p42-->p52\n p42-->p50\n p50-->p52\n p52-->p58" + }, + { + "objectID": "components/workflows/multiomics/integration/scanorama_leiden.html", + "href": "components/workflows/multiomics/integration/scanorama_leiden.html", + "title": "Scanorama leiden", + "section": "", + "text": "ID: scanorama_leiden\nNamespace: multiomics/integration\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/integration/scanorama_leiden.html#example-commands", + "href": "components/workflows/multiomics/integration/scanorama_leiden.html#example-commands", + "title": "Scanorama leiden", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/integration/scanorama_leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Neighbour calculation\nuns_neighbors: \"scanorama_integration_neighbors\"\nobsp_neighbor_distances: \"scanorama_integration_distances\"\nobsp_neighbor_connectivities: \"scanorama_integration_connectivities\"\n\n# Scanorama integration options\nobs_batch: \"sample_id\"\nobsm_input: \"X_pca\"\nobsm_output: \"X_scanorama\"\nknn: 20\nbatch_size: 5000\nsigma: 15\napprox: true\nalpha: 0.1\n\n# Clustering options\nobs_cluster: \"scanorama_integration_leiden\"\nleiden_resolution: [1]\n\n# Umap options\nobsm_umap: \"X_leiden_scanorama_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/integration/scanorama_leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/integration/scanorama_leiden.html#argument-groups", + "href": "components/workflows/multiomics/integration/scanorama_leiden.html#argument-groups", + "title": "Scanorama leiden", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"scanorama_integration_neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"scanorama_integration_distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"scanorama_integration_connectivities\"\n\n\n\n\n\nScanorama integration options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_batch\nColumn name discriminating between your batches.\nstring, default: \"sample_id\"\n\n\n--obsm_input\n.obsm slot that points to embedding to run scanorama on.\nstring, default: \"X_pca\"\n\n\n--obsm_output\nThe name of the field in adata.obsm where the integrated embeddings will be stored after running this function. Defaults to X_scanorama.\nstring, default: \"X_scanorama\"\n\n\n--knn\nNumber of nearest neighbors to use for matching.\ninteger, default: 20\n\n\n--batch_size\nThe batch size used in the alignment vector computation. Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory.\ninteger, default: 5000\n\n\n--sigma\nCorrection smoothing parameter on Gaussian kernel.\ndouble, default: 15\n\n\n--approx\nUse approximate nearest neighbors with Python annoy; greatly speeds up matching runtime.\nboolean, default: TRUE\n\n\n--alpha\nAlignment score minimum cutoff\ndouble, default: 0.1\n\n\n\n\n\nClustering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_cluster\nPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions specified in ‘–leiden_resolution’.\nstring, default: \"scanorama_integration_leiden\"\n\n\n--leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_leiden_scanorama_umap\"" + }, + { + "objectID": "components/workflows/multiomics/integration/scanorama_leiden.html#authors", + "href": "components/workflows/multiomics/integration/scanorama_leiden.html#authors", + "title": "Scanorama leiden", + "section": "Authors", + "text": "Authors\n\nMauro Saporita (author)\nPovilas Gibas (author)" + }, + { + "objectID": "components/workflows/multiomics/integration/scanorama_leiden.html#visualisation", + "href": "components/workflows/multiomics/integration/scanorama_leiden.html#visualisation", + "title": "Scanorama leiden", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p11(scanorama)\n p13(join)\n p21(find_neighbors)\n p23(join)\n p31(leiden)\n p33(join)\n p41(umap)\n p43(join)\n p51(move_obsm_to_obs)\n p53(join)\n p60(Output)\n p0-->p2\n p2-->p4\n p4-->p13\n p4-->p11\n p11-->p13\n p13-->p23\n p13-->p21\n p21-->p23\n p23-->p33\n p23-->p31\n p31-->p33\n p33-->p43\n p33-->p41\n p41-->p43\n p43-->p53\n p43-->p51\n p51-->p53\n p53-->p60" + }, + { + "objectID": "components/workflows/multiomics/integration/totalvi_leiden.html", + "href": "components/workflows/multiomics/integration/totalvi_leiden.html", + "title": "Totalvi leiden", + "section": "", + "text": "ID: totalvi_leiden\nNamespace: multiomics/integration\n\n\n\nSource" + }, + { + "objectID": "components/workflows/multiomics/integration/totalvi_leiden.html#example-commands", + "href": "components/workflows/multiomics/integration/totalvi_leiden.html#example-commands", + "title": "Totalvi leiden", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/integration/totalvi_leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\nprot_modality: \"prot\"\nreference: # please fill in - example: \"path/to/file\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# reference_model_path: \"$id.$key.reference_model_path.reference_model_path\"\n# query_model_path: \"$id.$key.query_model_path.query_model_path\"\n\n# General TotalVI Options\nobs_batch: \"sample_id\"\nmax_epochs: 400\nmax_query_epochs: 200\nweight_decay: 0.0\nforce_retrain: false\n# var_input: \"foo\"\n\n# TotalVI integration options RNA\nrna_reference_modality: \"rna\"\nrna_obsm_output: \"X_totalvi\"\n\n# TotalVI integration options ADT\nprot_reference_modality: \"prot\"\nprot_obsm_output: \"X_totalvi\"\n\n# Neighbour calculation RNA\nrna_uns_neighbors: \"totalvi_integration_neighbors\"\nrna_obsp_neighbor_distances: \"totalvi_integration_distances\"\nrna_obsp_neighbor_connectivities: \"totalvi_integration_connectivities\"\n\n# Neighbour calculation ADT\nprot_uns_neighbors: \"totalvi_integration_neighbors\"\nprot_obsp_neighbor_distances: \"totalvi_integration_distances\"\nprot_obsp_neighbor_connectivities: \"totalvi_integration_connectivities\"\n\n# Clustering options RNA\nrna_obs_cluster: \"totalvi_integration_leiden\"\nrna_leiden_resolution: [1]\n\n# Clustering options ADT\nprot_obs_cluster: \"totalvi_integration_leiden\"\nprot_leiden_resolution: [1]\n\n# Umap options\nobsm_umap: \"X_totalvi_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/integration/totalvi_leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/integration/totalvi_leiden.html#argument-groups", + "href": "components/workflows/multiomics/integration/totalvi_leiden.html#argument-groups", + "title": "Totalvi leiden", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n--prot_modality\nWhich modality to process.\nstring, default: \"prot\"\n\n\n--reference\nInput h5mu file with reference data to train the TOTALVI model.\nfile, required\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n--reference_model_path\nDirectory with the reference model. If not exists, trained model will be saved there\nfile, default: \"totalvi_model_reference\"\n\n\n--query_model_path\nDirectory, where the query model will be saved\nfile, default: \"totalvi_model_query\"\n\n\n\n\n\nGeneral TotalVI Options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_batch\n.Obs column name discriminating between your batches.\nstring, default: \"sample_id\"\n\n\n--max_epochs\nNumber of passes through the dataset\ninteger, default: 400\n\n\n--max_query_epochs\nNumber of passes through the dataset, when fine-tuning model for query\ninteger, default: 200\n\n\n--weight_decay\nWeight decay, when fine-tuning model for query\ndouble, default: 0\n\n\n--force_retrain\nIf true, retrain the model and save it to reference_model_path\nboolean_true\n\n\n--var_input\nBoolean .var column to subset data with (e.g. containing highly variable genes). By default, do not subset genes.\nstring\n\n\n\n\n\nTotalVI integration options RNA\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--rna_reference_modality\n\nstring, default: \"rna\"\n\n\n--rna_obsm_output\nIn which .obsm slot to store the normalized RNA from TOTALVI.\nstring, default: \"X_totalvi\"\n\n\n\n\n\nTotalVI integration options ADT\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--prot_reference_modality\nName of the modality containing proteins in the reference\nstring, default: \"prot\"\n\n\n--prot_obsm_output\nIn which .obsm slot to store the normalized protein data from TOTALVI.\nstring, default: \"X_totalvi\"\n\n\n\n\n\nNeighbour calculation RNA\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--rna_uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"totalvi_integration_neighbors\"\n\n\n--rna_obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"totalvi_integration_distances\"\n\n\n--rna_obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"totalvi_integration_connectivities\"\n\n\n\n\n\nNeighbour calculation ADT\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--prot_uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"totalvi_integration_neighbors\"\n\n\n--prot_obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"totalvi_integration_distances\"\n\n\n--prot_obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"totalvi_integration_connectivities\"\n\n\n\n\n\nClustering options RNA\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--rna_obs_cluster\nPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.\nstring, default: \"totalvi_integration_leiden\"\n\n\n--rna_leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nClustering options ADT\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--prot_obs_cluster\nPrefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for ‘–obs_cluster’ suffixed with an underscore and one of the resolutions resolutions specified in ‘–leiden_resolution’.\nstring, default: \"totalvi_integration_leiden\"\n\n\n--prot_leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_totalvi_umap\"" + }, + { + "objectID": "components/workflows/multiomics/integration/totalvi_leiden.html#authors", + "href": "components/workflows/multiomics/integration/totalvi_leiden.html#authors", + "title": "Totalvi leiden", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/multiomics/integration/totalvi_leiden.html#visualisation", + "href": "components/workflows/multiomics/integration/totalvi_leiden.html#visualisation", + "title": "Totalvi leiden", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p3(toSortedList)\n p5(flatMap)\n p12(totalvi)\n p14(join)\n p23(find_neighbors)\n p25(join)\n p33(leiden)\n p35(join)\n p43(umap)\n p45(join)\n p53(move_obsm_to_obs)\n p55(join)\n p64(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:find_neighbors:find_neighbors_process1)\n p66(join)\n p74(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:leiden:leiden_process1)\n p76(join)\n p84(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:umap:umap_process1)\n p86(join)\n p94(test_wf:run_wf:test_wf:run_wf:neighbors_leiden_umap:move_obsm_to_obs:move_obsm_to_obs_process1)\n p96(join)\n p104(publish)\n p106(join)\n p112(Output)\n p0-->p3\n p3-->p5\n p5-->p14\n p5-->p12\n p12-->p14\n p14-->p25\n p14-->p23\n p23-->p25\n p25-->p35\n p25-->p33\n p33-->p35\n p35-->p45\n p35-->p43\n p43-->p45\n p45-->p55\n p45-->p53\n p53-->p55\n p55-->p66\n p55-->p64\n p64-->p66\n p66-->p76\n p66-->p74\n p74-->p76\n p76-->p86\n p76-->p84\n p84-->p86\n p86-->p96\n p86-->p94\n p94-->p96\n p96-->p106\n p96-->p104\n p104-->p106\n p106-->p112" + }, + { + "objectID": "components/workflows/multiomics/multisample.html", + "href": "components/workflows/multiomics/multisample.html", + "title": "Multisample", + "section": "", + "text": "ID: multisample\nNamespace: multiomics\n\n\n\nSource\nAn input .h5mu file will first be split in order to run the multisample processing per modality. Next, the modalities are merged again and the integration setup pipeline is executed. Please note that this workflow assumes that samples from multiple pipelines are already concatenated." + }, + { + "objectID": "components/workflows/multiomics/multisample.html#example-commands", + "href": "components/workflows/multiomics/multisample.html#example-commands", + "title": "Multisample", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/multiomics/multisample/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"input.h5mu\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Highly variable gene detection\nfilter_with_hvg_var_output: \"filter_with_hvg\"\nfilter_with_hvg_obs_batch_key: \"sample_id\"\n\n# QC metrics calculation options\nvar_qc_metrics: [\"filter_with_hvg\"]\ntop_n_vars: [50, 100, 200, 500]\n\n# PCA options\npca_overwrite: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/multiomics/multisample/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/multiomics/multisample.html#argument-groups", + "href": "components/workflows/multiomics/multisample.html#argument-groups", + "title": "Multisample", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"input.h5mu\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nHighly variable gene detection\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--filter_with_hvg_var_output\nIn which .var slot to store a boolean array corresponding to the highly variable genes.\nstring, default: \"filter_with_hvg\"\n\n\n--filter_with_hvg_obs_batch_key\nIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method.\nstring, default: \"sample_id\"\n\n\n\n\n\nQC metrics calculation options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--var_qc_metrics\nKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes.\nstring, default: \"filter_with_hvg\", example: \"ercc,highly_variable\"\n\n\n--top_n_vars\nNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.\ninteger, default: 50, default: 100, default: 200, default: 500\n\n\n\n\n\nPCA options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--pca_overwrite\nAllow overwriting slots for PCA output.\nboolean_true" + }, + { + "objectID": "components/workflows/multiomics/multisample.html#authors", + "href": "components/workflows/multiomics/multisample.html#authors", + "title": "Multisample", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author, maintainer)" + }, + { + "objectID": "components/workflows/multiomics/multisample.html#visualisation", + "href": "components/workflows/multiomics/multisample.html#visualisation", + "title": "Multisample", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p7(filter)\n p12(split_modalities)\n p14(join)\n p21(concat)\n p17(filter)\n p19(test_wf:run_wf:split_modalities_workflow:splitStub)\n p22(flatMap)\n p23(filter)\n p26(toSortedList)\n p28(flatMap)\n p30(toSortedList)\n p32(Output)\n p38(normalize_total)\n p40(join)\n p48(log1p)\n p50(join)\n p58(delete_layer)\n p60(join)\n p68(filter_with_hvg)\n p70(join)\n p78(rna_calculate_qc_metrics)\n p80(join)\n p121(concat)\n p86(filter)\n p89(toSortedList)\n p91(flatMap)\n p93(toSortedList)\n p95(Output)\n p101(clr)\n p103(join)\n p111(prot_calculate_qc_metrics)\n p113(join)\n p119(filter)\n p122(groupTuple)\n p128(merge)\n p130(join)\n p133(filter)\n p137(toSortedList)\n p139(flatMap)\n p146(pca)\n p148(join)\n p156(find_neighbors)\n p158(join)\n p166(umap)\n p168(join)\n p173(concat)\n p172(filter)\n p174(filter)\n p178(toSortedList)\n p180(flatMap)\n p187(pca)\n p189(join)\n p197(find_neighbors)\n p199(join)\n p207(test_wf:run_wf:integration_setup_workflow:initialize_integration_prot:umap:umap_process1)\n p209(join)\n p214(concat)\n p213(filter)\n p220(publish)\n p222(join)\n p227(toSortedList)\n p229(Output)\n p21-->p22\n p22-->p23\n p22-->p86\n p22-->p119\n p121-->p122\n p172-->p173\n p173-->p174\n p173-->p213\n p213-->p214\n p0-->p2\n p2-->p4\n p4-->p7\n p4-->p17\n p7-->p14\n p7-->p12\n p12-->p14\n p14-->p21\n p17-->p19\n p19-->p21\n p23-->p26\n p26-->p28\n p28-->p30\n p30-->p32\n p28-->p40\n p28-->p38\n p38-->p40\n p40-->p50\n p40-->p48\n p48-->p50\n p50-->p60\n p50-->p58\n p58-->p60\n p60-->p70\n p60-->p68\n p68-->p70\n p70-->p80\n p70-->p78\n p78-->p80\n p80-->p121\n p86-->p89\n p89-->p91\n p91-->p93\n p93-->p95\n p91-->p103\n p91-->p101\n p101-->p103\n p103-->p113\n p103-->p111\n p111-->p113\n p113-->p121\n p119-->p121\n p122-->p130\n p122-->p128\n p128-->p130\n p130-->p133\n p130-->p172\n p133-->p137\n p137-->p139\n p139-->p148\n p139-->p146\n p146-->p148\n p148-->p158\n p148-->p156\n p156-->p158\n p158-->p168\n p158-->p166\n p166-->p168\n p168-->p173\n p174-->p178\n p178-->p180\n p180-->p189\n p180-->p187\n p187-->p189\n p189-->p199\n p189-->p197\n p197-->p199\n p199-->p209\n p199-->p207\n p207-->p209\n p209-->p214\n p214-->p222\n p214-->p220\n p220-->p222\n p222-->p227\n p227-->p229" + }, + { + "objectID": "components/workflows/ingestion/cellranger_mapping.html", + "href": "components/workflows/ingestion/cellranger_mapping.html", + "title": "Cell Ranger mapping", + "section": "", + "text": "ID: cellranger_mapping\nNamespace: ingestion\n\n\n\nSource" + }, + { + "objectID": "components/workflows/ingestion/cellranger_mapping.html#example-commands", + "href": "components/workflows/ingestion/cellranger_mapping.html#example-commands", + "title": "Cell Ranger mapping", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/ingestion/cellranger_mapping/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: [\"sample_S1_L001_R1_001.fastq.gz\", \"sample_S1_L001_R2_001.fastq.gz\"]\nreference: # please fill in - example: \"reference.tar.gz\"\n\n# Outputs\n# output_raw: \"$id.$key.output_raw.output_raw\"\n# output_h5mu: \"$id.$key.output_h5mu.h5mu\"\nobsm_metrics: \"metrics_summary\"\noutput_type: \"raw\"\n\n# Cell Ranger arguments\n# expect_cells: 3000\nchemistry: \"auto\"\nsecondary_analysis: false\ngenerate_bam: true\ninclude_introns: true\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/ingestion/cellranger_mapping/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/ingestion/cellranger_mapping.html#argument-groups", + "href": "components/workflows/ingestion/cellranger_mapping.html#argument-groups", + "title": "Cell Ranger mapping", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nThe fastq.gz files to align. Can also be a single directory containing fastq.gz files.\nfile, required, example: \"sample_S1_L001_R1_001.fastq.gz\", example: \"sample_S1_L001_R2_001.fastq.gz\"\n\n\n--reference\nThe path to Cell Ranger reference tar.gz file.\nfile, required, example: \"reference.tar.gz\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output_raw\nLocation where the output folder from Cell Ranger will be stored.\nfile, required, example: \"output_dir\"\n\n\n--output_h5mu\nThe output from Cell Ranger, converted to h5mu.\nfile, required, example: \"output.h5mu\"\n\n\n--obsm_metrics\nName of the .obsm slot under which to QC metrics (if any).\nstring, default: \"metrics_summary\"\n\n\n--output_type\nWhich Cell Ranger output to use for converting to h5mu.\nstring, default: \"raw\"\n\n\n\n\n\nCell Ranger arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--expect_cells\nExpected number of recovered cells, used as input to cell calling algorithm.\ninteger, example: 3000\n\n\n--chemistry\nAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.\nstring, default: \"auto\"\n\n\n--secondary_analysis\nWhether or not to run the secondary analysis e.g. clustering.\nboolean, default: FALSE\n\n\n--generate_bam\nWhether to generate a BAM file.\nboolean, default: TRUE\n\n\n--include_introns\nInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)\nboolean, default: TRUE" + }, + { + "objectID": "components/workflows/ingestion/cellranger_mapping.html#authors", + "href": "components/workflows/ingestion/cellranger_mapping.html#authors", + "title": "Cell Ranger mapping", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)\nDries De Maeyer (author)" + }, + { + "objectID": "components/workflows/ingestion/cellranger_mapping.html#visualisation", + "href": "components/workflows/ingestion/cellranger_mapping.html#visualisation", + "title": "Cell Ranger mapping", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p11(cellranger_count)\n p13(join)\n p20(cellranger_count_split)\n p22(join)\n p30(from_10xh5_to_h5mu)\n p32(join)\n p39(Output)\n p0-->p2\n p2-->p4\n p4-->p13\n p4-->p11\n p11-->p13\n p13-->p22\n p13-->p20\n p20-->p22\n p22-->p32\n p22-->p30\n p30-->p32\n p32-->p39" + }, + { + "objectID": "components/workflows/ingestion/cellranger_multi.html", + "href": "components/workflows/ingestion/cellranger_multi.html", + "title": "Cell Ranger multi", + "section": "", + "text": "ID: cellranger_multi\nNamespace: ingestion\n\n\n\nSource" + }, + { + "objectID": "components/workflows/ingestion/cellranger_multi.html#example-commands", + "href": "components/workflows/ingestion/cellranger_multi.html#example-commands", + "title": "Cell Ranger multi", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/ingestion/cellranger_multi/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: [\"sample_S1_L001_R1_001.fastq.gz\", \"sample_S1_L001_R2_001.fastq.gz\"]\ngex_reference: # please fill in - example: \"reference_genome.tar.gz\"\n# vdj_reference: \"reference_vdj.tar.gz\"\n# feature_reference: \"feature_reference.csv\"\n# vdj_inner_enrichment_primers: \"enrichment_primers.txt\"\n\n# Outputs\n# output_raw: \"$id.$key.output_raw.output_raw\"\n# output_h5mu: \"$id.$key.output_h5mu.h5mu\"\nuns_metrics: \"metrics_cellranger\"\n\n# Cell multiplexing parameters\n# cell_multiplex_sample_id: \"foo\"\n# cell_multiplex_oligo_ids: \"foo\"\n# cell_multiplex_description: \"foo\"\n\n# Gene expression arguments\n# gex_expect_cells: 3000\ngex_chemistry: \"auto\"\ngex_secondary_analysis: false\ngex_generate_bam: true\ngex_include_introns: true\n\n# Library arguments\nlibrary_id: # please fill in - example: [\"mysample1\"]\nlibrary_type: # please fill in - example: [\"Gene Expression\"]\n# library_subsample: [\"0.5\"]\n# library_lanes: [\"1-4\"]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/ingestion/cellranger_multi/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/ingestion/cellranger_multi.html#argument-groups", + "href": "components/workflows/ingestion/cellranger_multi.html#argument-groups", + "title": "Cell Ranger multi", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nThe fastq.gz files to align. Can also be a single directory containing fastq.gz files.\nfile, required, example: \"sample_S1_L001_R1_001.fastq.gz\", example: \"sample_S1_L001_R2_001.fastq.gz\"\n\n\n--gex_reference\nGenome refence index built by Cell Ranger mkref.\nfile, required, example: \"reference_genome.tar.gz\"\n\n\n--vdj_reference\nVDJ refence index built by Cell Ranger mkref.\nfile, example: \"reference_vdj.tar.gz\"\n\n\n--feature_reference\nPath to the Feature reference CSV file, declaring Feature Barcode constructs and associated barcodes. Required only for Antibody Capture or CRISPR Guide Capture libraries. See https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/feature-bc-analysis#feature-ref for more information.\nfile, example: \"feature_reference.csv\"\n\n\n--vdj_inner_enrichment_primers\nV(D)J Immune Profiling libraries: if inner enrichment primers other than those provided in the 10x Genomics kits are used, they need to be specified here as a text file with one primer per line.\nfile, example: \"enrichment_primers.txt\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output_raw\nThe raw output folder.\nfile, required, example: \"output_dir\"\n\n\n--output_h5mu\nThe converted h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--uns_metrics\nName of the .uns slot under which to QC metrics (if any).\nstring, default: \"metrics_cellranger\"\n\n\n\n\n\nCell multiplexing parameters\nArguments related to cell multiplexing.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--cell_multiplex_sample_id\nA name to identify a multiplexed sample. Must be alphanumeric with hyphens and/or underscores, and less than 64 characters. Required for Cell Multiplexing libraries.\nstring\n\n\n--cell_multiplex_oligo_ids\nThe Cell Multiplexing oligo IDs used to multiplex this sample. If multiple CMOs were used for a sample, separate IDs with a pipe (e.g., CMO301|CMO302). Required for Cell Multiplexing libraries.\nstring\n\n\n--cell_multiplex_description\nA description for the sample.\nstring\n\n\n\n\n\nGene expression arguments\nArguments relevant to the analysis of gene expression data.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--gex_expect_cells\nExpected number of recovered cells, used as input to cell calling algorithm.\ninteger, example: 3000\n\n\n--gex_chemistry\nAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.\nstring, default: \"auto\"\n\n\n--gex_secondary_analysis\nWhether or not to run the secondary analysis e.g. clustering.\nboolean, default: FALSE\n\n\n--gex_generate_bam\nWhether to generate a BAM file.\nboolean, default: TRUE\n\n\n--gex_include_introns\nInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)\nboolean, default: TRUE\n\n\n\n\n\nLibrary arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--library_id\nThe Illumina sample name to analyze. This must exactly match the ‘Sample Name’ part of the FASTQ files specified in the --input argument.\nstring, required, example: \"mysample1\"\n\n\n--library_type\nThe underlying feature type of the library. Possible values: “Gene Expression”, “VDJ”, “VDJ-T”, “VDJ-B”, “Antibody Capture”, “CRISPR Guide Capture”, “Multiplexing Capture”\nstring, required, example: \"Gene Expression\"\n\n\n--library_subsample\nOptional. The rate at which reads from the provided FASTQ files are sampled. Must be strictly greater than 0 and less than or equal to 1.\nstring, example: \"0.5\"\n\n\n--library_lanes\nLanes associated with this sample. Defaults to using all lanes.\nstring, example: \"1-4\"" + }, + { + "objectID": "components/workflows/ingestion/cellranger_multi.html#authors", + "href": "components/workflows/ingestion/cellranger_multi.html#authors", + "title": "Cell Ranger multi", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/ingestion/cellranger_multi.html#visualisation", + "href": "components/workflows/ingestion/cellranger_multi.html#visualisation", + "title": "Cell Ranger multi", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p11(cellranger_multi)\n p13(join)\n p20(from_cellranger_multi_to_h5mu)\n p22(join)\n p29(Output)\n p0-->p2\n p2-->p4\n p4-->p13\n p4-->p11\n p11-->p13\n p13-->p22\n p13-->p20\n p20-->p22\n p22-->p29" + }, + { + "objectID": "components/workflows/ingestion/make_reference.html", + "href": "components/workflows/ingestion/make_reference.html", + "title": "Make reference", + "section": "", + "text": "ID: make_reference\nNamespace: ingestion\n\n\n\nSource" + }, + { + "objectID": "components/workflows/ingestion/make_reference.html#example-commands", + "href": "components/workflows/ingestion/make_reference.html#example-commands", + "title": "Make reference", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/ingestion/make_reference/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ngenome_fasta: # please fill in - example: \"https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/GRCh38.primary_assembly.genome.fa.gz\"\ntranscriptome_gtf: # please fill in - example: \"https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/gencode.v41.annotation.gtf.gz\"\n# ercc: \"https://assets.thermofisher.com/TFS-Assets/LSG/manuals/ERCC92.zip\"\n\n# Outputs\ntarget: [\"star\"]\n# output_fasta: \"$id.$key.output_fasta.gz\"\n# output_gtf: \"$id.$key.output_gtf.gz\"\n# output_cellranger: \"$id.$key.output_cellranger.gz\"\n# output_bd_rhapsody: \"$id.$key.output_bd_rhapsody.gz\"\n# output_star: \"$id.$key.output_star.gz\"\n\n# Arguments\n# subset_regex: \"(ERCC-00002|chr1)\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/ingestion/make_reference/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/ingestion/make_reference.html#argument-groups", + "href": "components/workflows/ingestion/make_reference.html#argument-groups", + "title": "Make reference", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the reference.\nstring, required, example: \"foo\"\n\n\n--genome_fasta\nReference genome fasta.\nfile, required, example: \"https:/ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/GRCh38.primary_assembly.genome.fa.gz\"\n\n\n--transcriptome_gtf\nReference transcriptome annotation.\nfile, required, example: \"https:/ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_41/gencode.v41.annotation.gtf.gz\"\n\n\n--ercc\nERCC sequence and annotation file.\nfile, example: \"https:/assets.thermofisher.com/TFS-Assets/LSG/manuals/ERCC92.zip\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--target\nWhich reference indices to generate.\nstring, default: \"star\"\n\n\n--output_fasta\nOutput genome sequence fasta.\nfile, example: \"genome_sequence.fa.gz\"\n\n\n--output_gtf\nOutput transcriptome annotation gtf.\nfile, example: \"transcriptome_annotation.gtf.gz\"\n\n\n--output_cellranger\nOutput index\nfile, example: \"cellranger_index.tar.gz\"\n\n\n--output_bd_rhapsody\nOutput index\nfile, example: \"bdrhap_index.tar.gz\"\n\n\n--output_star\nOutput index\nfile, example: \"star_index.tar.gz\"\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--subset_regex\nWill subset the reference chromosomes using the given regex.\nstring, example: \"(ERCC-00002|chr1)\"" + }, + { + "objectID": "components/workflows/ingestion/make_reference.html#authors", + "href": "components/workflows/ingestion/make_reference.html#authors", + "title": "Make reference", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/workflows/ingestion/make_reference.html#visualisation", + "href": "components/workflows/ingestion/make_reference.html#visualisation", + "title": "Make reference", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p11(make_reference)\n p13(join)\n p17(filter)\n p22(build_cellranger_reference)\n p24(join)\n p54(join)\n p29(filter)\n p34(build_bdrhap_reference)\n p36(join)\n p55(join)\n p41(filter)\n p46(star_build_reference)\n p48(join)\n p56(join)\n p57(join)\n p62(Output)\n p54-->p55\n p55-->p56\n p56-->p57\n p0-->p2\n p2-->p4\n p4-->p13\n p4-->p11\n p11-->p13\n p13-->p17\n p17-->p24\n p17-->p22\n p22-->p24\n p24-->p54\n p13-->p29\n p29-->p36\n p29-->p34\n p34-->p36\n p36-->p55\n p13-->p41\n p41-->p48\n p41-->p46\n p46-->p48\n p48-->p56\n p0-->p57\n p13-->p54\n p57-->p62" + }, + { + "objectID": "components/workflows/ingestion/demux.html", + "href": "components/workflows/ingestion/demux.html", + "title": "Demux", + "section": "", + "text": "ID: demux\nNamespace: ingestion\n\n\n\nSource\nConvert .bcl files to .fastq files using bcl2fastq, bcl-convert or Cell Ranger mkfastq." + }, + { + "objectID": "components/workflows/ingestion/demux.html#example-commands", + "href": "components/workflows/ingestion/demux.html#example-commands", + "title": "Demux", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script ./workflows/ingestion/demux/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"bcl_dir\"\nsample_sheet: # please fill in - example: \"bcl_dir\"\ndemultiplexer: \"bcl2fastq\"\n# ignore_missing: true\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script ./workflows/ingestion/demux/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/ingestion/demux.html#argument-group", + "href": "components/workflows/ingestion/demux.html#argument-group", + "title": "Demux", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nInput run directory\nfile, required, example: \"bcl_dir\"\n\n\n--sample_sheet\nPointer to the sample sheet\nfile, required, example: \"bcl_dir\"\n\n\n--demultiplexer\nThe multiplexer to use, one of bclconvert or mkfastq\nstring, default: \"bcl2fastq\"\n\n\n--ignore_missing\nShould the demultiplexer ignore missing entities (filter, …)\nboolean" + }, + { + "objectID": "components/workflows/ingestion/demux.html#authors", + "href": "components/workflows/ingestion/demux.html#authors", + "title": "Demux", + "section": "Authors", + "text": "Authors\n\nToni Verbeiren (author, maintainer)\nMarijke Van Moerbeke (author)\nAngela Oliveira Pisco (author)\nSamuel D’Souza (author)\nRobrecht Cannoodt (author)" + }, + { + "objectID": "components/workflows/ingestion/demux.html#visualisation", + "href": "components/workflows/ingestion/demux.html#visualisation", + "title": "Demux", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p5(filter)\n p10(cellranger_mkfastq)\n p12(join)\n p35(mix)\n p15(filter)\n p20(bcl_convert)\n p22(join)\n p25(filter)\n p30(bcl2fastq)\n p32(join)\n p41(fastqc)\n p43(join)\n p46(Output)\n p48(toSortedList)\n p54(multiqc)\n p56(join)\n p59(Output)\n p63(Output)\n p4-->p5\n p4-->p15\n p4-->p25\n p0-->p2\n p2-->p4\n p5-->p12\n p5-->p10\n p10-->p12\n p12-->p35\n p15-->p22\n p15-->p20\n p20-->p22\n p22-->p35\n p25-->p32\n p25-->p30\n p30-->p32\n p32-->p35\n p35-->p43\n p35-->p41\n p41-->p43\n p43-->p46\n p35-->p48\n p48-->p56\n p48-->p54\n p54-->p56\n p56-->p59\n p35-->p63" + }, + { + "objectID": "components/workflows/integration/scvi/scvi.html", + "href": "components/workflows/integration/scvi/scvi.html", + "title": "Scvi", + "section": "", + "text": "ID: scvi\nNamespace: integration/scvi\n\n\n\nSource" + }, + { + "objectID": "components/workflows/integration/scvi/scvi.html#example-commands", + "href": "components/workflows/integration/scvi/scvi.html#example-commands", + "title": "Scvi", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -main-script workflows/multiomics/integration/scvi/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_model: \"$id.$key.output_model.output_model\"\n\n# Neighbour calculation\nuns_neighbors: \"scvi_integration_neighbors\"\nobsp_neighbor_distances: \"scvi_integration_distances\"\nobsp_neighbor_connectivities: \"scvi_integration_connectivities\"\n\n# Scvi integration options\nobs_batch: # please fill in - example: \"foo\"\nobsm_output: \"X_scvi_integrated\"\n# early_stopping: true\nearly_stopping_monitor: \"elbo_validation\"\nearly_stopping_patience: 45\nearly_stopping_min_delta: 0.0\n# max_epochs: 123\nreduce_lr_on_plateau: true\nlr_factor: 0.6\nlr_patience: 30\n\n# Umap options\nobsm_umap: \"X_scvi_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -profile docker \\\n -main-script workflows/multiomics/integration/scvi/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/integration/scvi/scvi.html#argument-groups", + "href": "components/workflows/integration/scvi/scvi.html#argument-groups", + "title": "Scvi", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n--output_model\nFolder where the state of the trained model will be saved to.\nfile, required, example: \"output_dir\"\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"scvi_integration_neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"scvi_integration_distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"scvi_integration_connectivities\"\n\n\n\n\n\nScvi integration options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_batch\nColumn name discriminating between your batches.\nstring, required\n\n\n--obsm_output\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_scvi_integrated\"\n\n\n--early_stopping\nWhether to perform early stopping with respect to the validation set.\nboolean\n\n\n--early_stopping_monitor\nMetric logged during validation set epoch.\nstring, default: \"elbo_validation\"\n\n\n--early_stopping_patience\nNumber of validation epochs with no improvement after which training will be stopped.\ninteger, default: 45\n\n\n--early_stopping_min_delta\nMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.\ndouble, default: 0\n\n\n--max_epochs\nNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.\ninteger\n\n\n--reduce_lr_on_plateau\nWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.\nboolean, default: TRUE\n\n\n--lr_factor\nFactor to reduce learning rate.\ndouble, default: 0.6\n\n\n--lr_patience\nNumber of epochs with no improvement after which learning rate will be reduced.\ndouble, default: 30\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_scvi_umap\"" + }, + { + "objectID": "components/workflows/integration/scvi/scvi.html#authors", + "href": "components/workflows/integration/scvi/scvi.html#authors", + "title": "Scvi", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/workflows/integration/scvi/scvi.html#visualisation", + "href": "components/workflows/integration/scvi/scvi.html#visualisation", + "title": "Scvi", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p3(toSortedList)\n p5(flatMap)\n p13(scvi)\n p24(find_neighbors)\n p34(umap)\n p42(Output)\n p0-->p3\n p3-->p5\n p5-->p13\n p13-->p24\n p24-->p34\n p34-->p42" + }, + { + "objectID": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html", + "href": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html", + "title": "Scanorama leiden", + "section": "", + "text": "ID: scanorama_leiden\nNamespace: integration/scanorama_leiden\n\n\n\nSource" + }, + { + "objectID": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#example-commands", + "href": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#example-commands", + "title": "Scanorama leiden", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -main-script workflows/multiomics/integration/scanorama_leiden/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nid: # please fill in - example: \"foo\"\ninput: # please fill in - example: \"dataset.h5mu\"\nlayer: \"log_normalized\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n\n# Neighbour calculation\nuns_neighbors: \"scanorama_integration_neighbors\"\nobsp_neighbor_distances: \"scanorama_integration_distances\"\nobsp_neighbor_connectivities: \"scanorama_integration_connectivities\"\n\n# Scanorama integration options\nobs_batch: \"sample_id\"\nobsm_input: \"X_pca\"\nobsm_output: \"X_scanorama\"\nknn: 20\nbatch_size: 5000\nsigma: 15\napprox: true\nalpha: 0.1\n\n# Clustering options\nobs_cluster: \"scanorama_integration_leiden\"\nleiden_resolution: [1]\n\n# Umap options\nobsm_umap: \"X_leiden_scanorama_umap\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.9.0 -latest \\\n -profile docker \\\n -main-script workflows/multiomics/integration/scanorama_leiden/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#argument-groups", + "href": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#argument-groups", + "title": "Scanorama leiden", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--id\nID of the sample.\nstring, required, example: \"foo\"\n\n\n--input\nPath to the sample.\nfile, required, example: \"dataset.h5mu\"\n\n\n--layer\nuse specified layer for expression values instead of the .X object from the modality.\nstring, default: \"log_normalized\"\n\n\n--modality\nWhich modality to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nDestination path to the output.\nfile, required, example: \"output.h5mu\"\n\n\n\n\n\nNeighbour calculation\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--uns_neighbors\nIn which .uns slot to store various neighbor output objects.\nstring, default: \"scanorama_integration_neighbors\"\n\n\n--obsp_neighbor_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"scanorama_integration_distances\"\n\n\n--obsp_neighbor_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"scanorama_integration_connectivities\"\n\n\n\n\n\nScanorama integration options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_batch\nColumn name discriminating between your batches.\nstring, default: \"sample_id\"\n\n\n--obsm_input\n.osbm slot that points to embedding to run scanorama on.\nstring, default: \"X_pca\"\n\n\n--obsm_output\nThe name of the field in adata.obsm where the integrated embeddings will be stored after running this function. Defaults to X_scanorama.\nstring, default: \"X_scanorama\"\n\n\n--knn\nNumber of nearest neighbors to use for matching.\ninteger, default: 20\n\n\n--batch_size\nThe batch size used in the alignment vector computation. Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory.\ninteger, default: 5000\n\n\n--sigma\nCorrection smoothing parameter on Gaussian kernel.\ndouble, default: 15\n\n\n--approx\nUse approximate nearest neighbors with Python annoy; greatly speeds up matching runtime.\nboolean, default: TRUE\n\n\n--alpha\nAlignment score minimum cutoff\ndouble, default: 0.1\n\n\n\n\n\nClustering options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obs_cluster\nName of the .obs key under which to add the cluster labels.\nstring, default: \"scanorama_integration_leiden\"\n\n\n--leiden_resolution\nControl the coarseness of the clustering. Higher values lead to more clusters.\ndouble, default: 1\n\n\n\n\n\nUmap options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--obsm_umap\nIn which .obsm slot to store the resulting UMAP embedding.\nstring, default: \"X_leiden_scanorama_umap\"" + }, + { + "objectID": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#authors", + "href": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#authors", + "title": "Scanorama leiden", + "section": "Authors", + "text": "Authors\n\nMauro Saporita (author)\nPovilas Gibas (author)" + }, + { + "objectID": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#visualisation", + "href": "components/workflows/integration/scanorama_leiden/scanorama_leiden.html#visualisation", + "title": "Scanorama leiden", + "section": "Visualisation", + "text": "Visualisation\n\n\n\n\nflowchart LR\n p0(Input)\n p2(toSortedList)\n p4(flatMap)\n p12(scanorama)\n p22(find_neighbors)\n p32(leiden)\n p42(umap)\n p52(move_obsm_to_obs)\n p60(Output)\n p0-->p2\n p2-->p4\n p4-->p12\n p12-->p22\n p22-->p32\n p32-->p42\n p42-->p52\n p52-->p60" + }, + { + "objectID": "components/modules/velocity/scvelo.html", + "href": "components/modules/velocity/scvelo.html", + "title": "Scvelo", + "section": "", + "text": "ID: scvelo\nNamespace: velocity\n\n\n\nSource" + }, + { + "objectID": "components/modules/velocity/scvelo.html#example-commands", + "href": "components/modules/velocity/scvelo.html#example-commands", + "title": "Scvelo", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/velocity/scvelo/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"path/to/file\"\n\n# Outputs\n# output: \"$id.$key.output.output\"\n# output_compression: \"gzip\"\n\n# Filtering and normalization\n# min_counts: 123\n# min_counts_u: 123\n# min_cells: 123\n# min_cells_u: 123\n# min_shared_counts: 123\n# min_shared_cells: 123\n# n_top_genes: 123\nlog_transform: true\n\n# Fitting parameters\n# n_principal_components: 123\nn_neighbors: 30\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/velocity/scvelo/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/velocity/scvelo.html#argument-groups", + "href": "components/modules/velocity/scvelo.html#argument-groups", + "title": "Scvelo", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nVelocyto loom file.\nfile, required\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput directory. If it does not exist, will be created.\nfile, required\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n\n\n\nFiltering and normalization\nArguments for filtering, normalization an log transform (see scvelo.pp.filter_and_normalize function)\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--min_counts\nMinimum number of counts required for a gene to pass filtering (spliced).\ninteger\n\n\n--min_counts_u\nMinimum number of counts required for a gene to pass filtering (unspliced).\ninteger\n\n\n--min_cells\nMinimum number of cells expressed required to pass filtering (spliced).\ninteger\n\n\n--min_cells_u\nMinimum number of cells expressed required to pass filtering (unspliced).\ninteger\n\n\n--min_shared_counts\nMinimum number of counts (both unspliced and spliced) required for a gene.\ninteger\n\n\n--min_shared_cells\nMinimum number of cells required to be expressed (both unspliced and spliced).\ninteger\n\n\n--n_top_genes\nNumber of genes to keep.\ninteger\n\n\n--log_transform\nDo not log transform counts.\nboolean, default: TRUE\n\n\n\n\n\nFitting parameters\nArguments for fitting the data\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--n_principal_components\nNumber of principal components to use for calculating moments.\ninteger\n\n\n--n_neighbors\nNumber of neighbors to use. First/second-order moments are computed for each cell across its nearest neighbors, where the neighbor graph is obtained from euclidean distances in PCA space.\ninteger, default: 30" + }, + { + "objectID": "components/modules/velocity/scvelo.html#authors", + "href": "components/modules/velocity/scvelo.html#authors", + "title": "Scvelo", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/interpret/lianapy.html", + "href": "components/modules/interpret/lianapy.html", + "title": "Lianapy", + "section": "", + "text": "ID: lianapy\nNamespace: interpret\n\n\n\nSource" + }, + { + "objectID": "components/modules/interpret/lianapy.html#example-commands", + "href": "components/modules/interpret/lianapy.html#example-commands", + "title": "Lianapy", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/interpret/lianapy/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"path/to/file\"\n# output: \"$id.$key.output.output\"\noutput_compression: \"gzip\"\nmodality: \"rna\"\n# layer: \"foo\"\ngroupby: \"bulk_labels\"\nresource_name: \"consensus\"\ngene_symbol: \"gene_symbol\"\nexpr_prop: 0.1\nmin_cells: 5\naggregate_method: \"rra\"\nreturn_all_lrs: false\nn_perms: 100\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/interpret/lianapy/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/interpret/lianapy.html#argument-group", + "href": "components/modules/interpret/lianapy.html#argument-group", + "title": "Lianapy", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required\n\n\n--output\nOutput h5mu file.\nfile, required\n\n\n--output_compression\n\nstring, default: \"gzip\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--layer\nLayer in anndata.AnnData.layers to use. If None, use mudata.mod[modality].X.\nstring\n\n\n--groupby\nThe key of the observations grouping to consider.\nstring, default: \"bulk_labels\"\n\n\n--resource_name\nName of the resource to be loaded and use for ligand-receptor inference.\nstring, default: \"consensus\"\n\n\n--gene_symbol\nColumn name in var DataFrame in which gene symbol are stored.\nstring, default: \"gene_symbol\"\n\n\n--expr_prop\nMinimum expression proportion for the ligands/receptors (and their subunits) in the corresponding cell identities. Set to ‘0’, to return unfiltered results.\ndouble, default: 0.1\n\n\n--min_cells\nMinimum cells per cell identity (‘groupby’) to be considered for downstream analysis.\ninteger, default: 5\n\n\n--aggregate_method\nMethod aggregation approach, one of [‘mean’, ‘rra’], where ‘mean’ represents the mean rank, while ‘rra’ is the RobustRankAggregate (Kolde et al., 2014) of the interactions.\nstring, default: \"rra\"\n\n\n--return_all_lrs\nBool whether to return all LRs, or only those that surpass the ‘expr_prop’ threshold. Those interactions that do not pass the ‘expr_prop’ threshold will be assigned to the worst score of the ones that do. ‘False’ by default.\nboolean, default: FALSE\n\n\n--n_perms\nNumber of permutations for the permutation test. Note that this is relevant only for permutation-based methods - e.g. ’CellPhoneDB\ninteger, default: 100" + }, + { + "objectID": "components/modules/interpret/lianapy.html#authors", + "href": "components/modules/interpret/lianapy.html#authors", + "title": "Lianapy", + "section": "Authors", + "text": "Authors\n\nMauro Saporita (author)\nPovilas Gibas (author)" + }, + { + "objectID": "components/modules/mapping/cellranger_count.html", + "href": "components/modules/mapping/cellranger_count.html", + "title": "Cellranger count", + "section": "", + "text": "ID: cellranger_count\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/cellranger_count.html#example-commands", + "href": "components/modules/mapping/cellranger_count.html#example-commands", + "title": "Cellranger count", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/cellranger_count/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: [\"sample_S1_L001_R1_001.fastq.gz\", \"sample_S1_L001_R2_001.fastq.gz\"]\nreference: # please fill in - example: \"reference.tar.gz\"\n\n# Outputs\n# output: \"$id.$key.output.output\"\n\n# Arguments\n# expect_cells: 3000\nchemistry: \"auto\"\nsecondary_analysis: false\ngenerate_bam: true\ninclude_introns: true\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/cellranger_count/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/cellranger_count.html#argument-groups", + "href": "components/modules/mapping/cellranger_count.html#argument-groups", + "title": "Cellranger count", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nThe fastq.gz files to align. Can also be a single directory containing fastq.gz files.\nfile, required, example: \"sample_S1_L001_R1_001.fastq.gz\", example: \"sample_S1_L001_R2_001.fastq.gz\"\n\n\n--reference\nThe path to Cell Ranger reference tar.gz file. Can also be a directory.\nfile, required, example: \"reference.tar.gz\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nThe folder to store the alignment results.\nfile, required, example: \"/path/to/output\"\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--expect_cells\nExpected number of recovered cells, used as input to cell calling algorithm.\ninteger, example: 3000\n\n\n--chemistry\nAssay configuration. - auto: autodetect mode - threeprime: Single Cell 3’ - fiveprime: Single Cell 5’ - SC3Pv1: Single Cell 3’ v1 - SC3Pv2: Single Cell 3’ v2 - SC3Pv3: Single Cell 3’ v3 - SC3Pv3LT: Single Cell 3’ v3 LT - SC3Pv3HT: Single Cell 3’ v3 HT - SC5P-PE: Single Cell 5’ paired-end - SC5P-R2: Single Cell 5’ R2-only - SC-FB: Single Cell Antibody-only 3’ v2 or 5’ See https://kb.10xgenomics.com/hc/en-us/articles/115003764132-How-does-Cell-Ranger-auto-detect-chemistry- for more information.\nstring, default: \"auto\"\n\n\n--secondary_analysis\nWhether or not to run the secondary analysis e.g. clustering.\nboolean, default: FALSE\n\n\n--generate_bam\nWhether to generate a BAM file.\nboolean, default: TRUE\n\n\n--include_introns\nInclude intronic reads in count (default=true unless –target-panel is specified in which case default=false)\nboolean, default: TRUE" + }, + { + "objectID": "components/modules/mapping/cellranger_count.html#authors", + "href": "components/modules/mapping/cellranger_count.html#authors", + "title": "Cellranger count", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nSamuel D’Souza (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/mapping/htseq_count_to_h5mu.html", + "href": "components/modules/mapping/htseq_count_to_h5mu.html", + "title": "Htseq count to h5mu", + "section": "", + "text": "ID: htseq_count_to_h5mu\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/htseq_count_to_h5mu.html#example-commands", + "href": "components/modules/mapping/htseq_count_to_h5mu.html#example-commands", + "title": "Htseq count to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/htseq_count_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Input\ninput_id: # please fill in - example: [\"foo\"]\ninput_counts: # please fill in - example: [\"counts.tsv\"]\nreference: # please fill in - example: \"gencode_v41_star\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/htseq_count_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/htseq_count_to_h5mu.html#argument-groups", + "href": "components/modules/mapping/htseq_count_to_h5mu.html#argument-groups", + "title": "Htseq count to h5mu", + "section": "Argument groups", + "text": "Argument groups\n\nInput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input_id\nThe obs index for the counts\nstring, required, example: \"foo\"\n\n\n--input_counts\nThe counts as a TSV file as output by HTSeq.\nfile, required, example: \"counts.tsv\"\n\n\n--reference\nThe GTF file.\nfile, required, example: \"gencode_v41_star\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/mapping/htseq_count_to_h5mu.html#authors", + "href": "components/modules/mapping/htseq_count_to_h5mu.html#authors", + "title": "Htseq count to h5mu", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (author, maintainer)\nAngela Oliveira Pisco (author)" + }, + { + "objectID": "components/modules/mapping/htseq_count.html", + "href": "components/modules/mapping/htseq_count.html", + "title": "Htseq count", + "section": "", + "text": "ID: htseq_count\nNamespace: mapping\n\n\n\nSource\nThis script takes one or more alignment files in SAM/BAM format and a feature file in GFF format and calculates for each feature the number of reads mapping to it.\nSee http://htseq.readthedocs.io/en/master/count.html for details." + }, + { + "objectID": "components/modules/mapping/htseq_count.html#example-commands", + "href": "components/modules/mapping/htseq_count.html#example-commands", + "title": "Htseq count", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/htseq_count/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\norder: \"name\"\nstranded: \"yes\"\nminimum_alignment_quality: 10\n# type: \"exon\"\n# id_attribute: [\"gene_id\"]\n# additional_attributes: [\"gene_name\"]\nadd_chromosome_info: false\nmode: \"union\"\nnon_unique: \"none\"\n# secondary_alignments: \"foo\"\n# supplementary_alignments: \"foo\"\ncounts_output_sparse: false\n\n# Input\ninput: # please fill in - example: [\"mysample1.BAM\", \"mysample2.BAM\"]\nreference: # please fill in - example: \"reference.gtf\"\n\n# Output\n# output: \"$id.$key.output.tsv\"\n# output_delimiter: \" \"\n# output_sam: [\"$id.$key.output_sam_*.BAM\"]\n# output_sam_format: \"foo\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/htseq_count/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/htseq_count.html#argument-groups", + "href": "components/modules/mapping/htseq_count.html#argument-groups", + "title": "Htseq count", + "section": "Argument groups", + "text": "Argument groups\n\nInput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to the SAM/BAM files containing the mapped reads.\nfile, required, example: \"mysample1.BAM\", example: \"mysample2.BAM\"\n\n\n--reference\nPath to the GTF file containing the features.\nfile, required, example: \"reference.gtf\"\n\n\n\n\n\nOutput\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nFilename to output the counts to.\nfile, required, example: \"htseq-count.tsv\"\n\n\n--output_delimiter\nColumn delimiter in output.\nstring, example: \" \"\n\n\n--output_sam\nWrite out all SAM alignment records into SAM/BAM files (one per input file needed), annotating each line with its feature assignment (as an optional field with tag ‘XF’). See the -p option to use BAM instead of SAM.\nfile, example: \"mysample1_out.BAM\", example: \"mysample2_out.BAM\"\n\n\n--output_sam_format\nFormat to use with the –output_sam argument.\nstring\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--order\nSorting order of . Paired-end sequencing data must be sorted either by position or by read name, and the sorting order must be specified. Ignored for single-end data.\nstring, default: \"name\"\n\n\n--stranded\nWhether the data is from a strand-specific assay. ‘reverse’ means ‘yes’ with reversed strand interpretation.\nstring, default: \"yes\"\n\n\n--minimum_alignment_quality\nSkip all reads with MAPQ alignment quality lower than the given minimum value. MAPQ is the 5th column of a SAM/BAM file and its usage depends on the software used to map the reads.\ninteger, default: 10\n\n\n--type\nFeature type (3rd column in GTF file) to be used, all features of other type are ignored (default, suitable for Ensembl GTF files: exon)\nstring, example: \"exon\"\n\n\n--id_attribute\nGTF attribute to be used as feature ID (default, suitable for Ensembl GTF files: gene_id). All feature of the right type (see -t option) within the same GTF attribute will be added together. The typical way of using this option is to count all exonic reads from each gene and add the exons but other uses are possible as well. You can call this option multiple times: in that case, the combination of all attributes separated by colons (:) will be used as a unique identifier, e.g. for exons you might use -i gene_id -i exon_number.\nstring, example: \"gene_id\"\n\n\n--additional_attributes\nAdditional feature attributes (suitable for Ensembl GTF files: gene_name). Use multiple times for more than one additional attribute. These attributes are only used as annotations in the output, while the determination of how the counts are added together is done based on option -i.\nstring, example: \"gene_name\"\n\n\n--add_chromosome_info\nStore information about the chromosome of each feature as an additional attribute (e.g. colunm in the TSV output file).\nboolean_true\n\n\n--mode\nMode to handle reads overlapping more than one feature.\nstring, default: \"union\"\n\n\n--non_unique\nWhether and how to score reads that are not uniquely aligned or ambiguously assigned to features.\nstring, default: \"none\"\n\n\n--secondary_alignments\nWhether to score secondary alignments (0x100 flag).\nstring\n\n\n--supplementary_alignments\nWhether to score supplementary alignments (0x800 flag).\nstring\n\n\n--counts_output_sparse\nStore the counts as a sparse matrix (mtx, h5ad, loom).\nboolean_true" + }, + { + "objectID": "components/modules/mapping/htseq_count.html#authors", + "href": "components/modules/mapping/htseq_count.html#authors", + "title": "Htseq count", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (author, maintainer)\nAngela Oliveira Pisco (author)" + }, + { + "objectID": "components/modules/mapping/star_build_reference.html", + "href": "components/modules/mapping/star_build_reference.html", + "title": "Star build reference", + "section": "", + "text": "ID: star_build_reference\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/star_build_reference.html#example-commands", + "href": "components/modules/mapping/star_build_reference.html#example-commands", + "title": "Star build reference", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/star_build_reference/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Input/Output\ngenome_fasta: # please fill in - example: [\"chr1.fasta\", \"chr2.fasta\"]\n# transcriptome_gtf: \"path/to/file\"\n# output: \"$id.$key.output.output\"\n\n# Genome indexing arguments\ngenomeSAindexNbases: 14\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/star_build_reference/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/star_build_reference.html#argument-groups", + "href": "components/modules/mapping/star_build_reference.html#argument-groups", + "title": "Star build reference", + "section": "Argument groups", + "text": "Argument groups\n\nInput/Output\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genome_fasta\nThe fasta files to be included in the reference. Corresponds to the –genomeFastaFiles argument in the STAR command.\nfile, required, example: \"chr1.fasta\", example: \"chr2.fasta\"\n\n\n--transcriptome_gtf\nSpecifies the path to the file with annotated transcripts in the standard GTF format. STAR will extract splice junctions from this file and use them to greatly improve accuracy of the mapping. Corresponds to the –sjdbGTFfile argument in the STAR command.\nfile\n\n\n--output\nPath to output directory. Corresponds to the –genomeDir argument in the STAR command.\nfile, required, example: \"/path/to/foo\"\n\n\n\n\n\nGenome indexing arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genomeSAindexNbases\nLength (bases) of the SA pre-indexing string. Typically between 10 and 15. Longer strings will use much more memory, but allow faster searches. For small genomes, the parameter {genomeSAindexNbases must be scaled down to min(14, log2(GenomeLength)/2 - 1).\ninteger, default: 14" + }, + { + "objectID": "components/modules/mapping/star_build_reference.html#authors", + "href": "components/modules/mapping/star_build_reference.html#authors", + "title": "Star build reference", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/modules/mapping/star_align_v273a.html", + "href": "components/modules/mapping/star_align_v273a.html", + "title": "Star align v273a", + "section": "", + "text": "ID: star_align_v273a\nNamespace: mapping\n\n\n\nSource" + }, + { + "objectID": "components/modules/mapping/star_align_v273a.html#example-commands", + "href": "components/modules/mapping/star_align_v273a.html#example-commands", + "title": "Star align v273a", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/star_align_v273a/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Input/Output\ninput: # please fill in - example: [\"mysample_S1_L001_R1_001.fastq.gz\", \"mysample_S1_L001_R2_001.fastq.gz\"]\nreference: # please fill in - example: \"/path/to/reference\"\n# output: \"$id.$key.output.output\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/star_align_v273a/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/star_align_v273a.html#argument-groups", + "href": "components/modules/mapping/star_align_v273a.html#argument-groups", + "title": "Star align v273a", + "section": "Argument groups", + "text": "Argument groups\n\nInput/Output\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nThe FASTQ files to be analyzed. Corresponds to the –readFilesIn in the STAR command.\nfile, required, example: \"mysample_S1_L001_R1_001.fastq.gz\", example: \"mysample_S1_L001_R2_001.fastq.gz\"\n\n\n--reference\nPath to the reference built by star_build_reference. Corresponds to the –genomeDir in the STAR command.\nfile, required, example: \"/path/to/reference\"\n\n\n--output\nPath to output directory. Corresponds to the –outFileNamePrefix in the STAR command.\nfile, required, example: \"/path/to/foo\"\n\n\n\n\n\nRun Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--runRNGseed\nrandom number generator seed.\ninteger, example: 777\n\n\n\n\n\nGenome Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genomeLoad\nmode of shared memory usage for the genome files. Only used with –runMode alignReads. - LoadAndKeep … load genome into shared and keep it in memory after run - LoadAndRemove … load genome into shared but remove it after run - LoadAndExit … load genome into shared memory and exit, keeping the genome in memory for future runs - Remove … do not map anything, just remove loaded genome from memory - NoSharedMemory … do not use shared memory, each job will have its own private copy of the genome\nstring, example: \"NoSharedMemory\"\n\n\n--genomeFastaFiles\npath(s) to the fasta files with the genome sequences, separated by spaces. These files should be plain text FASTA files, they cannot be zipped. Required for the genome generation (–runMode genomeGenerate). Can also be used in the mapping (–runMode alignReads) to add extra (new) sequences to the genome (e.g. spike-ins).\nfile\n\n\n--genomeFileSizes\ngenome files exact sizes in bytes. Typically, this should not be defined by the user.\ninteger, example: 0\n\n\n--genomeTransformOutput\nwhich output to transform back to original genome - SAM … SAM/BAM alignments - SJ … splice junctions (SJ.out.tab) - None … no transformation of the output\nstring\n\n\n--genomeChrSetMitochondrial\nnames of the mitochondrial chromosomes. Presently only used for STARsolo statistics output/\nstring, example: \"chrM\", example: \"M\", example: \"MT\"\n\n\n\n\n\nSplice Junctions Database\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--sjdbFileChrStartEnd\npath to the files with genomic coordinates (chr start end strand) for the splice junction introns. Multiple files can be supplied and will be concatenated.\nstring\n\n\n--sjdbGTFfile\npath to the GTF file with annotations\nfile\n\n\n--sjdbGTFchrPrefix\nprefix for chromosome names in a GTF file (e.g. ‘chr’ for using ENSMEBL annotations with UCSC genomes)\nstring\n\n\n--sjdbGTFfeatureExon\nfeature type in GTF file to be used as exons for building transcripts\nstring, example: \"exon\"\n\n\n--sjdbGTFtagExonParentTranscript\nGTF attribute name for parent transcript ID (default “transcript_id” works for GTF files)\nstring, example: \"transcript_id\"\n\n\n--sjdbGTFtagExonParentGene\nGTF attribute name for parent gene ID (default “gene_id” works for GTF files)\nstring, example: \"gene_id\"\n\n\n--sjdbGTFtagExonParentGeneName\nGTF attribute name for parent gene name\nstring, example: \"gene_name\"\n\n\n--sjdbGTFtagExonParentGeneType\nGTF attribute name for parent gene type\nstring, example: \"gene_type\", example: \"gene_biotype\"\n\n\n--sjdbOverhang\nlength of the donor/acceptor sequence on each side of the junctions, ideally = (mate_length - 1)\ninteger, example: 100\n\n\n--sjdbScore\nextra alignment score for alignments that cross database junctions\ninteger, example: 2\n\n\n--sjdbInsertSave\nwhich files to save when sjdb junctions are inserted on the fly at the mapping step - Basic … only small junction / transcript files - All … all files including big Genome, SA and SAindex - this will create a complete genome directory\nstring, example: \"Basic\"\n\n\n\n\n\nVariation parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--varVCFfile\npath to the VCF file that contains variation data. The 10th column should contain the genotype information, e.g. 0/1\nstring\n\n\n\n\n\nRead Parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--readFilesType\nformat of input read files - Fastx … FASTA or FASTQ - SAM SE … SAM or BAM single-end reads; for BAM use –readFilesCommand samtools view - SAM PE … SAM or BAM paired-end reads; for BAM use –readFilesCommand samtools view\nstring, example: \"Fastx\"\n\n\n--readFilesSAMattrKeep\nfor –readFilesType SAM SE/PE, which SAM tags to keep in the output BAM, e.g.: –readFilesSAMtagsKeep RG PL - All … keep all tags - None … do not keep any tags\nstring, example: \"All\"\n\n\n--readFilesManifest\npath to the “manifest” file with the names of read files. The manifest file should contain 3 tab-separated columns: paired-end reads: read1_file_name \\(tab\\) read2_file_name \\(tab\\) read_group_line. single-end reads: read1_file_name \\(tab\\) - \\(tab\\) read_group_line. Spaces, but not tabs are allowed in file names. If read_group_line does not start with ID:, it can only contain one ID field, and ID: will be added to it. If read_group_line starts with ID:, it can contain several fields separated by \\(tab\\), and all fields will be be copied verbatim into SAM @RG header line.\nfile\n\n\n--readFilesPrefix\nprefix for the read files names, i.e. it will be added in front of the strings in –readFilesIn\nstring\n\n\n--readFilesCommand\ncommand line to execute for each of the input file. This command should generate FASTA or FASTQ text and send it to stdout For example: zcat - to uncompress .gz files, bzcat - to uncompress .bz2 files, etc.\nstring\n\n\n--readMapNumber\nnumber of reads to map from the beginning of the file -1: map all reads\ninteger, example: -1\n\n\n--readMatesLengthsIn\nEqual/NotEqual - lengths of names,sequences,qualities for both mates are the same / not the same. NotEqual is safe in all situations.\nstring, example: \"NotEqual\"\n\n\n--readNameSeparator\ncharacter(s) separating the part of the read names that will be trimmed in output (read name after space is always trimmed)\nstring, example: \"/\"\n\n\n--readQualityScoreBase\nnumber to be subtracted from the ASCII code to get Phred quality score\ninteger, example: 33\n\n\n\n\n\nRead Clipping\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--clipAdapterType\nadapter clipping type - Hamming … adapter clipping based on Hamming distance, with the number of mismatches controlled by –clip5pAdapterMMp - CellRanger4 … 5p and 3p adapter clipping similar to CellRanger4. Utilizes Opal package by Martin Sosic: https://github.com/Martinsos/opal - None … no adapter clipping, all other clip* parameters are disregarded\nstring, example: \"Hamming\"\n\n\n--clip3pNbases\nnumber(s) of bases to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n--clip3pAdapterSeq\nadapter sequences to clip from 3p of each mate. If one value is given, it will be assumed the same for both mates. - polyA … polyA sequence with the length equal to read length\nstring\n\n\n--clip3pAdapterMMp\nmax proportion of mismatches for 3p adapter clipping for each mate. If one value is given, it will be assumed the same for both mates.\ndouble, example: 0.1\n\n\n--clip3pAfterAdapterNbases\nnumber of bases to clip from 3p of each mate after the adapter clipping. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n--clip5pNbases\nnumber(s) of bases to clip from 5p of each mate. If one value is given, it will be assumed the same for both mates.\ninteger, example: 0\n\n\n\n\n\nLimits\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--limitGenomeGenerateRAM\nmaximum available RAM (bytes) for genome generation\nlong, example: NA\n\n\n--limitIObufferSize\nmax available buffers size (bytes) for input/output, per thread\nlong, example: 30000000, example: 50000000\n\n\n--limitOutSAMoneReadBytes\nmax size of the SAM record (bytes) for one read. Recommended value: >(2(LengthMate1+LengthMate2+100)outFilterMultimapNmax\nlong, example: 100000\n\n\n--limitOutSJoneRead\nmax number of junctions for one read (including all multi-mappers)\ninteger, example: 1000\n\n\n--limitOutSJcollapsed\nmax number of collapsed junctions\ninteger, example: 1000000\n\n\n--limitBAMsortRAM\nmaximum available RAM (bytes) for sorting BAM. If =0, it will be set to the genome index size. 0 value can only be used with –genomeLoad NoSharedMemory option.\nlong, example: 0\n\n\n--limitSjdbInsertNsj\nmaximum number of junctions to be inserted to the genome on the fly at the mapping stage, including those from annotations and those detected in the 1st step of the 2-pass run\ninteger, example: 1000000\n\n\n--limitNreadsSoft\nsoft limit on the number of reads\ninteger, example: -1\n\n\n\n\n\nOutput: general\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outTmpKeep\nwhether to keep the temporary files after STAR runs is finished - None … remove all temporary files - All … keep all files\nstring\n\n\n--outStd\nwhich output will be directed to stdout (standard out) - Log … log messages - SAM … alignments in SAM format (which normally are output to Aligned.out.sam file), normal standard output will go into Log.std.out - BAM_Unsorted … alignments in BAM format, unsorted. Requires –outSAMtype BAM Unsorted - BAM_SortedByCoordinate … alignments in BAM format, sorted by coordinate. Requires –outSAMtype BAM SortedByCoordinate - BAM_Quant … alignments to transcriptome in BAM format, unsorted. Requires –quantMode TranscriptomeSAM\nstring, example: \"Log\"\n\n\n--outReadsUnmapped\noutput of unmapped and partially mapped (i.e. mapped only one mate of a paired end read) reads in separate file(s). - None … no output - Fastx … output in separate fasta/fastq files, Unmapped.out.mate1/2\nstring\n\n\n--outQSconversionAdd\nadd this number to the quality score (e.g. to convert from Illumina to Sanger, use -31)\ninteger, example: 0\n\n\n--outMultimapperOrder\norder of multimapping alignments in the output files - Old_2.4 … quasi-random order used before 2.5.0 - Random … random order of alignments for each multi-mapper. Read mates (pairs) are always adjacent, all alignment for each read stay together. This option will become default in the future releases.\nstring, example: \"Old_2.4\"\n\n\n\n\n\nOutput: SAM and BAM\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSAMtype\ntype of SAM/BAM output 1st word: - BAM … output BAM without sorting - SAM … output SAM without sorting - None … no SAM/BAM output 2nd, 3rd: - Unsorted … standard unsorted - SortedByCoordinate … sorted by coordinate. This option will allocate extra memory for sorting which can be specified by –limitBAMsortRAM.\nstring, example: \"SAM\"\n\n\n--outSAMmode\nmode of SAM output - None … no SAM output - Full … full SAM output - NoQS … full SAM but without quality scores\nstring, example: \"Full\"\n\n\n--outSAMstrandField\nCufflinks-like strand field flag - None … not used - intronMotif … strand derived from the intron motif. This option changes the output alignments: reads with inconsistent and/or non-canonical introns are filtered out.\nstring\n\n\n--outSAMattributes\na string of desired SAM attributes, in the order desired for the output SAM. Tags can be listed in any combination/order. Presets: - None … no attributes - Standard … NH HI AS nM - All … NH HI AS nM NM MD jM jI MC ch Alignment: - NH … number of loci the reads maps to: =1 for unique mappers, >1 for multimappers. Standard SAM tag. - HI … multiple alignment index, starts with –outSAMattrIHstart (=1 by default). Standard SAM tag. - AS … local alignment score, +1/-1 for matches/mismateches, score* penalties for indels and gaps. For PE reads, total score for two mates. Stadnard SAM tag. - nM … number of mismatches. For PE reads, sum over two mates. - NM … edit distance to the reference (number of mismatched + inserted + deleted bases) for each mate. Standard SAM tag. - MD … string encoding mismatched and deleted reference bases (see standard SAM specifications). Standard SAM tag. - jM … intron motifs for all junctions (i.e. N in CIGAR): 0: non-canonical; 1: GT/AG, 2: CT/AC, 3: GC/AG, 4: CT/GC, 5: AT/AC, 6: GT/AT. If splice junctions database is used, and a junction is annotated, 20 is added to its motif value. - jI … start and end of introns for all junctions (1-based). - XS … alignment strand according to –outSAMstrandField. - MC … mate’s CIGAR string. Standard SAM tag. - ch … marks all segment of all chimeric alingments for –chimOutType WithinBAM output. - cN … number of bases clipped from the read ends: 5’ and 3’ Variation: - vA … variant allele - vG … genomic coordinate of the variant overlapped by the read. - vW … 1 - alignment passes WASP filtering; 2,3,4,5,6,7 - alignment does not pass WASP filtering. Requires –waspOutputMode SAMtag. STARsolo: - CR CY UR UY … sequences and quality scores of cell barcodes and UMIs for the solo* demultiplexing. - GX GN … gene ID and gene name for unique-gene reads. - gx gn … gene IDs and gene names for unique- and multi-gene reads. - CB UB … error-corrected cell barcodes and UMIs for solo* demultiplexing. Requires –outSAMtype BAM SortedByCoordinate. - sM … assessment of CB and UMI. - sS … sequence of the entire barcode (CB,UMI,adapter). - sQ … quality of the entire barcode. ***Unsupported/undocumented: - ha … haplotype (1/2) when mapping to the diploid genome. Requires genome generated with –genomeTransformType Diploid . - rB … alignment block read/genomic coordinates. - vR … read coordinate of the variant.\nstring, example: \"Standard\"\n\n\n--outSAMattrIHstart\nstart value for the IH attribute. 0 may be required by some downstream software, such as Cufflinks or StringTie.\ninteger, example: 1\n\n\n--outSAMunmapped\noutput of unmapped reads in the SAM format 1st word: - None … no output - Within … output unmapped reads within the main SAM file (i.e. Aligned.out.sam) 2nd word: - KeepPairs … record unmapped mate for each alignment, and, in case of unsorted output, keep it adjacent to its mapped mate. Only affects multi-mapping reads.\nstring\n\n\n--outSAMorder\ntype of sorting for the SAM output Paired: one mate after the other for all paired alignments PairedKeepInputOrder: one mate after the other for all paired alignments, the order is kept the same as in the input FASTQ files\nstring, example: \"Paired\"\n\n\n--outSAMprimaryFlag\nwhich alignments are considered primary - all others will be marked with 0x100 bit in the FLAG - OneBestScore … only one alignment with the best score is primary - AllBestScore … all alignments with the best score are primary\nstring, example: \"OneBestScore\"\n\n\n--outSAMreadID\nread ID record type - Standard … first word (until space) from the FASTx read ID line, removing /1,/2 from the end - Number … read number (index) in the FASTx file\nstring, example: \"Standard\"\n\n\n--outSAMmapqUnique\n0 to 255: the MAPQ value for unique mappers\ninteger, example: 255\n\n\n--outSAMflagOR\n0 to 65535: sam FLAG will be bitwise OR’d with this value, i.e. FLAG=FLAG | outSAMflagOR. This is applied after all flags have been set by STAR, and after outSAMflagAND. Can be used to set specific bits that are not set otherwise.\ninteger, example: 0\n\n\n--outSAMflagAND\n0 to 65535: sam FLAG will be bitwise AND’d with this value, i.e. FLAG=FLAG & outSAMflagOR. This is applied after all flags have been set by STAR, but before outSAMflagOR. Can be used to unset specific bits that are not set otherwise.\ninteger, example: 65535\n\n\n--outSAMattrRGline\nSAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”. xxx will be added as RG tag to each output alignment. Any spaces in the tag values have to be double quoted. Comma separated RG lines correspons to different (comma separated) input files in –readFilesIn. Commas have to be surrounded by spaces, e.g. –outSAMattrRGline ID:xxx , ID:zzz “DS:z z” , ID:yyy DS:yyyy\nstring\n\n\n--outSAMheaderHD\n@HD (header) line of the SAM header\nstring\n\n\n--outSAMheaderPG\nextra @PG (software) line of the SAM header (in addition to STAR)\nstring\n\n\n--outSAMheaderCommentFile\npath to the file with @CO (comment) lines of the SAM header\nstring\n\n\n--outSAMfilter\nfilter the output into main SAM/BAM files - KeepOnlyAddedReferences … only keep the reads for which all alignments are to the extra reference sequences added with –genomeFastaFiles at the mapping stage. - KeepAllAddedReferences … keep all alignments to the extra reference sequences added with –genomeFastaFiles at the mapping stage.\nstring\n\n\n--outSAMmultNmax\nmax number of multiple alignments for a read that will be output to the SAM/BAM files. Note that if this value is not equal to -1, the top scoring alignment will be output first - -1 … all alignments (up to –outFilterMultimapNmax) will be output\ninteger, example: -1\n\n\n--outSAMtlen\ncalculation method for the TLEN field in the SAM/BAM files - 1 … leftmost base of the (+)strand mate to rightmost base of the (-)mate. (+)sign for the (+)strand mate - 2 … leftmost base of any mate to rightmost base of any mate. (+)sign for the mate with the leftmost base. This is different from 1 for overlapping mates with protruding ends\ninteger, example: 1\n\n\n--outBAMcompression\n-1 to 10 BAM compression level, -1=default compression (6?), 0=no compression, 10=maximum compression\ninteger, example: 1\n\n\n--outBAMsortingThreadN\n>=0: number of threads for BAM sorting. 0 will default to min(6,–runThreadN).\ninteger, example: 0\n\n\n--outBAMsortingBinsN\n>0: number of genome bins for coordinate-sorting\ninteger, example: 50\n\n\n\n\n\nBAM processing\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--bamRemoveDuplicatesType\nmark duplicates in the BAM file, for now only works with (i) sorted BAM fed with inputBAMfile, and (ii) for paired-end alignments only - - … no duplicate removal/marking - UniqueIdentical … mark all multimappers, and duplicate unique mappers. The coordinates, FLAG, CIGAR must be identical - UniqueIdenticalNotMulti … mark duplicate unique mappers but not multimappers.\nstring\n\n\n--bamRemoveDuplicatesMate2basesN\nnumber of bases from the 5’ of mate 2 to use in collapsing (e.g. for RAMPAGE)\ninteger, example: 0\n\n\n\n\n\nOutput Wiggle\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outWigType\ntype of signal output, e.g. “bedGraph” OR “bedGraph read1_5p”. Requires sorted BAM: –outSAMtype BAM SortedByCoordinate . 1st word: - None … no signal output - bedGraph … bedGraph format - wiggle … wiggle format 2nd word: - read1_5p … signal from only 5’ of the 1st read, useful for CAGE/RAMPAGE etc - read2 … signal from only 2nd read\nstring\n\n\n--outWigStrand\nstrandedness of wiggle/bedGraph output - Stranded … separate strands, str1 and str2 - Unstranded … collapsed strands\nstring, example: \"Stranded\"\n\n\n--outWigReferencesPrefix\nprefix matching reference names to include in the output wiggle file, e.g. “chr”, default “-” - include all references\nstring\n\n\n--outWigNorm\ntype of normalization for the signal - RPM … reads per million of mapped reads - None … no normalization, “raw” counts\nstring, example: \"RPM\"\n\n\n\n\n\nOutput Filtering\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outFilterType\ntype of filtering - Normal … standard filtering using only current alignment - BySJout … keep only those reads that contain junctions that passed filtering into SJ.out.tab\nstring, example: \"Normal\"\n\n\n--outFilterMultimapScoreRange\nthe score range below the maximum score for multimapping alignments\ninteger, example: 1\n\n\n--outFilterMultimapNmax\nmaximum number of loci the read is allowed to map to. Alignments (all of them) will be output only if the read maps to no more loci than this value. Otherwise no alignments will be output, and the read will be counted as “mapped to too many loci” in the Log.final.out .\ninteger, example: 10\n\n\n--outFilterMismatchNmax\nalignment will be output only if it has no more mismatches than this value.\ninteger, example: 10\n\n\n--outFilterMismatchNoverLmax\nalignment will be output only if its ratio of mismatches to mapped length is less than or equal to this value.\ndouble, example: 0.3\n\n\n--outFilterMismatchNoverReadLmax\nalignment will be output only if its ratio of mismatches to read length is less than or equal to this value.\ndouble, example: 1\n\n\n--outFilterScoreMin\nalignment will be output only if its score is higher than or equal to this value.\ninteger, example: 0\n\n\n--outFilterScoreMinOverLread\nsame as outFilterScoreMin, but normalized to read length (sum of mates’ lengths for paired-end reads)\ndouble, example: 0.66\n\n\n--outFilterMatchNmin\nalignment will be output only if the number of matched bases is higher than or equal to this value.\ninteger, example: 0\n\n\n--outFilterMatchNminOverLread\nsam as outFilterMatchNmin, but normalized to the read length (sum of mates’ lengths for paired-end reads).\ndouble, example: 0.66\n\n\n--outFilterIntronMotifs\nfilter alignment using their motifs - None … no filtering - RemoveNoncanonical … filter out alignments that contain non-canonical junctions - RemoveNoncanonicalUnannotated … filter out alignments that contain non-canonical unannotated junctions when using annotated splice junctions database. The annotated non-canonical junctions will be kept.\nstring\n\n\n--outFilterIntronStrands\nfilter alignments - RemoveInconsistentStrands … remove alignments that have junctions with inconsistent strands - None … no filtering\nstring, example: \"RemoveInconsistentStrands\"\n\n\n\n\n\nOutput splice junctions (SJ.out.tab)\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSJtype\ntype of splice junction output - Standard … standard SJ.out.tab output - None … no splice junction output\nstring, example: \"Standard\"\n\n\n\n\n\nOutput Filtering: Splice Junctions\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--outSJfilterReads\nwhich reads to consider for collapsed splice junctions output - All … all reads, unique- and multi-mappers - Unique … uniquely mapping reads only\nstring, example: \"All\"\n\n\n--outSJfilterOverhangMin\nminimum overhang length for splice junctions on both sides for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif does not apply to annotated junctions\ninteger, example: 30, example: 12, example: 12, example: 12\n\n\n--outSJfilterCountUniqueMin\nminimum uniquely mapping read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctions\ninteger, example: 3, example: 1, example: 1, example: 1\n\n\n--outSJfilterCountTotalMin\nminimum total (multi-mapping+unique) read count per junction for: (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif. -1 means no output for that motif Junctions are output if one of outSJfilterCountUniqueMin OR outSJfilterCountTotalMin conditions are satisfied does not apply to annotated junctions\ninteger, example: 3, example: 1, example: 1, example: 1\n\n\n--outSJfilterDistToOtherSJmin\nminimum allowed distance to other junctions’ donor/acceptor does not apply to annotated junctions\ninteger, example: 10, example: 0, example: 5, example: 10\n\n\n--outSJfilterIntronMaxVsReadN\nmaximum gap allowed for junctions supported by 1,2,3,,,N reads i.e. by default junctions supported by 1 read can have gaps <=50000b, by 2 reads: <=100000b, by 3 reads: <=200000. by >=4 reads any gap <=alignIntronMax does not apply to annotated junctions\ninteger, example: 50000, example: 100000, example: 200000\n\n\n\n\n\nScoring\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--scoreGap\nsplice junction penalty (independent on intron motif)\ninteger, example: 0\n\n\n--scoreGapNoncan\nnon-canonical junction penalty (in addition to scoreGap)\ninteger, example: -8\n\n\n--scoreGapGCAG\nGC/AG and CT/GC junction penalty (in addition to scoreGap)\ninteger, example: -4\n\n\n--scoreGapATAC\nAT/AC and GT/AT junction penalty (in addition to scoreGap)\ninteger, example: -8\n\n\n--scoreGenomicLengthLog2scale\nextra score logarithmically scaled with genomic length of the alignment: scoreGenomicLengthLog2scale*log2(genomicLength)\ninteger, example: 0\n\n\n--scoreDelOpen\ndeletion open penalty\ninteger, example: -2\n\n\n--scoreDelBase\ndeletion extension penalty per base (in addition to scoreDelOpen)\ninteger, example: -2\n\n\n--scoreInsOpen\ninsertion open penalty\ninteger, example: -2\n\n\n--scoreInsBase\ninsertion extension penalty per base (in addition to scoreInsOpen)\ninteger, example: -2\n\n\n--scoreStitchSJshift\nmaximum score reduction while searching for SJ boundaries in the stitching step\ninteger, example: 1\n\n\n\n\n\nAlignments and Seeding\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--seedSearchStartLmax\ndefines the search start point through the read - the read is split into pieces no longer than this value\ninteger, example: 50\n\n\n--seedSearchStartLmaxOverLread\nseedSearchStartLmax normalized to read length (sum of mates’ lengths for paired-end reads)\ndouble, example: 1\n\n\n--seedSearchLmax\ndefines the maximum length of the seeds, if =0 seed length is not limited\ninteger, example: 0\n\n\n--seedMultimapNmax\nonly pieces that map fewer than this value are utilized in the stitching procedure\ninteger, example: 10000\n\n\n--seedPerReadNmax\nmax number of seeds per read\ninteger, example: 1000\n\n\n--seedPerWindowNmax\nmax number of seeds per window\ninteger, example: 50\n\n\n--seedNoneLociPerWindow\nmax number of one seed loci per window\ninteger, example: 10\n\n\n--seedSplitMin\nmin length of the seed sequences split by Ns or mate gap\ninteger, example: 12\n\n\n--seedMapMin\nmin length of seeds to be mapped\ninteger, example: 5\n\n\n--alignIntronMin\nminimum intron size, genomic gap is considered intron if its length>=alignIntronMin, otherwise it is considered Deletion\ninteger, example: 21\n\n\n--alignIntronMax\nmaximum intron size, if 0, max intron size will be determined by (2^winBinNbits)*winAnchorDistNbins\ninteger, example: 0\n\n\n--alignMatesGapMax\nmaximum gap between two mates, if 0, max intron gap will be determined by (2^winBinNbits)*winAnchorDistNbins\ninteger, example: 0\n\n\n--alignSJoverhangMin\nminimum overhang (i.e. block size) for spliced alignments\ninteger, example: 5\n\n\n--alignSJstitchMismatchNmax\nmaximum number of mismatches for stitching of the splice junctions (-1: no limit). (1) non-canonical motifs, (2) GT/AG and CT/AC motif, (3) GC/AG and CT/GC motif, (4) AT/AC and GT/AT motif.\ninteger, example: 0, example: -1, example: 0, example: 0\n\n\n--alignSJDBoverhangMin\nminimum overhang (i.e. block size) for annotated (sjdb) spliced alignments\ninteger, example: 3\n\n\n--alignSplicedMateMapLmin\nminimum mapped length for a read mate that is spliced\ninteger, example: 0\n\n\n--alignSplicedMateMapLminOverLmate\nalignSplicedMateMapLmin normalized to mate length\ndouble, example: 0.66\n\n\n--alignWindowsPerReadNmax\nmax number of windows per read\ninteger, example: 10000\n\n\n--alignTranscriptsPerWindowNmax\nmax number of transcripts per window\ninteger, example: 100\n\n\n--alignTranscriptsPerReadNmax\nmax number of different alignments per read to consider\ninteger, example: 10000\n\n\n--alignEndsType\ntype of read ends alignment - Local … standard local alignment with soft-clipping allowed - EndToEnd … force end-to-end read alignment, do not soft-clip - Extend5pOfRead1 … fully extend only the 5p of the read1, all other ends: local alignment - Extend5pOfReads12 … fully extend only the 5p of the both read1 and read2, all other ends: local alignment\nstring, example: \"Local\"\n\n\n--alignEndsProtrude\nallow protrusion of alignment ends, i.e. start (end) of the +strand mate downstream of the start (end) of the -strand mate 1st word: int: maximum number of protrusion bases allowed 2nd word: string: - ConcordantPair … report alignments with non-zero protrusion as concordant pairs - DiscordantPair … report alignments with non-zero protrusion as discordant pairs\nstring, example: \"0 ConcordantPair\"\n\n\n--alignSoftClipAtReferenceEnds\nallow the soft-clipping of the alignments past the end of the chromosomes - Yes … allow - No … prohibit, useful for compatibility with Cufflinks\nstring, example: \"Yes\"\n\n\n--alignInsertionFlush\nhow to flush ambiguous insertion positions - None … insertions are not flushed - Right … insertions are flushed to the right\nstring\n\n\n\n\n\nPaired-End reads\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--peOverlapNbasesMin\nminimum number of overlapping bases to trigger mates merging and realignment. Specify >0 value to switch on the “merginf of overlapping mates” algorithm.\ninteger, example: 0\n\n\n--peOverlapMMp\nmaximum proportion of mismatched bases in the overlap area\ndouble, example: 0.01\n\n\n\n\n\nWindows, Anchors, Binning\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--winAnchorMultimapNmax\nmax number of loci anchors are allowed to map to\ninteger, example: 50\n\n\n--winBinNbits\n=log2(winBin), where winBin is the size of the bin for the windows/clustering, each window will occupy an integer number of bins.\ninteger, example: 16\n\n\n--winAnchorDistNbins\nmax number of bins between two anchors that allows aggregation of anchors into one window\ninteger, example: 9\n\n\n--winFlankNbins\nlog2(winFlank), where win Flank is the size of the left and right flanking regions for each window\ninteger, example: 4\n\n\n--winReadCoverageRelativeMin\nminimum relative coverage of the read sequence by the seeds in a window, for STARlong algorithm only.\ndouble, example: 0.5\n\n\n--winReadCoverageBasesMin\nminimum number of bases covered by the seeds in a window , for STARlong algorithm only.\ninteger, example: 0\n\n\n\n\n\nChimeric Alignments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--chimOutType\ntype of chimeric output - Junctions … Chimeric.out.junction - SeparateSAMold … output old SAM into separate Chimeric.out.sam file - WithinBAM … output into main aligned BAM files (Aligned.*.bam) - WithinBAM HardClip … (default) hard-clipping in the CIGAR for supplemental chimeric alignments (default if no 2nd word is present) - WithinBAM SoftClip … soft-clipping in the CIGAR for supplemental chimeric alignments\nstring, example: \"Junctions\"\n\n\n--chimSegmentMin\nminimum length of chimeric segment length, if ==0, no chimeric output\ninteger, example: 0\n\n\n--chimScoreMin\nminimum total (summed) score of the chimeric segments\ninteger, example: 0\n\n\n--chimScoreDropMax\nmax drop (difference) of chimeric score (the sum of scores of all chimeric segments) from the read length\ninteger, example: 20\n\n\n--chimScoreSeparation\nminimum difference (separation) between the best chimeric score and the next one\ninteger, example: 10\n\n\n--chimScoreJunctionNonGTAG\npenalty for a non-GT/AG chimeric junction\ninteger, example: -1\n\n\n--chimJunctionOverhangMin\nminimum overhang for a chimeric junction\ninteger, example: 20\n\n\n--chimSegmentReadGapMax\nmaximum gap in the read sequence between chimeric segments\ninteger, example: 0\n\n\n--chimFilter\ndifferent filters for chimeric alignments - None … no filtering - banGenomicN … Ns are not allowed in the genome sequence around the chimeric junction\nstring, example: \"banGenomicN\"\n\n\n--chimMainSegmentMultNmax\nmaximum number of multi-alignments for the main chimeric segment. =1 will prohibit multimapping main segments.\ninteger, example: 10\n\n\n--chimMultimapNmax\nmaximum number of chimeric multi-alignments - 0 … use the old scheme for chimeric detection which only considered unique alignments\ninteger, example: 0\n\n\n--chimMultimapScoreRange\nthe score range for multi-mapping chimeras below the best chimeric score. Only works with –chimMultimapNmax > 1\ninteger, example: 1\n\n\n--chimNonchimScoreDropMin\nto trigger chimeric detection, the drop in the best non-chimeric alignment score with respect to the read length has to be greater than this value\ninteger, example: 20\n\n\n--chimOutJunctionFormat\nformatting type for the Chimeric.out.junction file - 0 … no comment lines/headers - 1 … comment lines at the end of the file: command line and Nreads: total, unique/multi-mapping\ninteger, example: 0\n\n\n\n\n\nQuantification of Annotations\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--quantMode\ntypes of quantification requested - - … none - TranscriptomeSAM … output SAM/BAM alignments to transcriptome into a separate file - GeneCounts … count reads per gene\nstring\n\n\n--quantTranscriptomeBAMcompression\n-2 to 10 transcriptome BAM compression level - -2 … no BAM output - -1 … default compression (6?) - 0 … no compression - 10 … maximum compression\ninteger, example: 1\n\n\n--quantTranscriptomeBan\nprohibit various alignment type - IndelSoftclipSingleend … prohibit indels, soft clipping and single-end alignments - compatible with RSEM - Singleend … prohibit single-end alignments\nstring, example: \"IndelSoftclipSingleend\"\n\n\n\n\n\n2-pass Mapping\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--twopassMode\n2-pass mapping mode. - None … 1-pass mapping - Basic … basic 2-pass mapping, with all 1st pass junctions inserted into the genome indices on the fly\nstring\n\n\n--twopass1readsN\nnumber of reads to process for the 1st step. Use very large number (or default -1) to map all reads in the first step.\ninteger, example: -1\n\n\n\n\n\nWASP parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--waspOutputMode\nWASP allele-specific output type. This is re-implementation of the original WASP mappability filtering by Bryce van de Geijn, Graham McVicker, Yoav Gilad & Jonathan K Pritchard. Please cite the original WASP paper: Nature Methods 12, 1061-1063 (2015), https://www.nature.com/articles/nmeth.3582 . - SAMtag … add WASP tags to the alignments that pass WASP filtering\nstring\n\n\n\n\n\nSTARsolo (single cell RNA-seq) parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--soloType\ntype of single-cell RNA-seq - CB_UMI_Simple … (a.k.a. Droplet) one UMI and one Cell Barcode of fixed length in read2, e.g. Drop-seq and 10X Chromium. - CB_UMI_Complex … multiple Cell Barcodes of varying length, one UMI of fixed length and one adapter sequence of fixed length are allowed in read2 only (e.g. inDrop, ddSeq). - CB_samTagOut … output Cell Barcode as CR and/or CB SAm tag. No UMI counting. –readFilesIn cDNA_read1 [cDNA_read2 if paired-end] CellBarcode_read . Requires –outSAMtype BAM Unsorted [and/or SortedByCoordinate] - SmartSeq … Smart-seq: each cell in a separate FASTQ (paired- or single-end), barcodes are corresponding read-groups, no UMI sequences, alignments deduplicated according to alignment start and end (after extending soft-clipped bases)\nstring\n\n\n--soloCBwhitelist\nfile(s) with whitelist(s) of cell barcodes. Only –soloType CB_UMI_Complex allows more than one whitelist file. - None … no whitelist: all cell barcodes are allowed\nstring\n\n\n--soloCBstart\ncell barcode start base\ninteger, example: 1\n\n\n--soloCBlen\ncell barcode length\ninteger, example: 16\n\n\n--soloUMIstart\nUMI start base\ninteger, example: 17\n\n\n--soloUMIlen\nUMI length\ninteger, example: 10\n\n\n--soloBarcodeReadLength\nlength of the barcode read - 1 … equal to sum of soloCBlen+soloUMIlen - 0 … not defined, do not check\ninteger, example: 1\n\n\n--soloBarcodeMate\nidentifies which read mate contains the barcode (CB+UMI) sequence - 0 … barcode sequence is on separate read, which should always be the last file in the –readFilesIn listed - 1 … barcode sequence is a part of mate 1 - 2 … barcode sequence is a part of mate 2\ninteger, example: 0\n\n\n--soloCBposition\nposition of Cell Barcode(s) on the barcode read. Presently only works with –soloType CB_UMI_Complex, and barcodes are assumed to be on Read2. Format for each barcode: startAnchor_startPosition_endAnchor_endPosition start(end)Anchor defines the Anchor Base for the CB: 0: read start; 1: read end; 2: adapter start; 3: adapter end start(end)Position is the 0-based position with of the CB start(end) with respect to the Anchor Base String for different barcodes are separated by space. Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 0_0_2_-1 3_1_3_8\nstring\n\n\n--soloUMIposition\nposition of the UMI on the barcode read, same as soloCBposition Example: inDrop (Zilionis et al, Nat. Protocols, 2017): –soloCBposition 3_9_3_14\nstring\n\n\n--soloAdapterSequence\nadapter sequence to anchor barcodes. Only one adapter sequence is allowed.\nstring\n\n\n--soloAdapterMismatchesNmax\nmaximum number of mismatches allowed in adapter sequence.\ninteger, example: 1\n\n\n--soloCBmatchWLtype\nmatching the Cell Barcodes to the WhiteList - Exact … only exact matches allowed - 1MM … only one match in whitelist with 1 mismatched base allowed. Allowed CBs have to have at least one read with exact match. - 1MM_multi … multiple matches in whitelist with 1 mismatched base allowed, posterior probability calculation is used choose one of the matches. Allowed CBs have to have at least one read with exact match. This option matches best with CellRanger 2.2.0 - 1MM_multi_pseudocounts … same as 1MM_Multi, but pseudocounts of 1 are added to all whitelist barcodes. - 1MM_multi_Nbase_pseudocounts … same as 1MM_multi_pseudocounts, multimatching to WL is allowed for CBs with N-bases. This option matches best with CellRanger >= 3.0.0 - EditDist_2 … allow up to edit distance of 3 fpr each of the barcodes. May include one deletion + one insertion. Only works with –soloType CB_UMI_Complex. Matches to multiple passlist barcdoes are not allowed. Similar to ParseBio Split-seq pipeline.\nstring, example: \"1MM_multi\"\n\n\n--soloInputSAMattrBarcodeSeq\nwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode sequence (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeSeq CR UR . This parameter is required when running STARsolo with input from SAM.\nstring\n\n\n--soloInputSAMattrBarcodeQual\nwhen inputting reads from a SAM file (–readsFileType SAM SE/PE), these SAM attributes mark the barcode qualities (in proper order). For instance, for 10X CellRanger or STARsolo BAMs, use –soloInputSAMattrBarcodeQual CY UY . If this parameter is ‘-’ (default), the quality ‘H’ will be assigned to all bases.\nstring\n\n\n--soloStrand\nstrandedness of the solo libraries: - Unstranded … no strand information - Forward … read strand same as the original RNA molecule - Reverse … read strand opposite to the original RNA molecule\nstring, example: \"Forward\"\n\n\n--soloFeatures\ngenomic features for which the UMI counts per Cell Barcode are collected - Gene … genes: reads match the gene transcript - SJ … splice junctions: reported in SJ.out.tab - GeneFull … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns - GeneFull_ExonOverIntron … full gene (pre-mRNA): count all reads overlapping genes’ exons and introns: prioritize 100% overlap with exons - GeneFull_Ex50pAS … full gene (pre-RNA): count all reads overlapping genes’ exons and introns: prioritize >50% overlap with exons. Do not count reads with 100% exonic overlap in the antisense direction.\nstring, example: \"Gene\"\n\n\n--soloMultiMappers\ncounting method for reads mapping to multiple genes - Unique … count only reads that map to unique genes - Uniform … uniformly distribute multi-genic UMIs to all genes - Rescue … distribute UMIs proportionally to unique+uniform counts (~ first iteration of EM) - PropUnique … distribute UMIs proportionally to unique mappers, if present, and uniformly if not. - EM … multi-gene UMIs are distributed using Expectation Maximization algorithm\nstring, example: \"Unique\"\n\n\n--soloUMIdedup\ntype of UMI deduplication (collapsing) algorithm - 1MM_All … all UMIs with 1 mismatch distance to each other are collapsed (i.e. counted once). - 1MM_Directional_UMItools … follows the “directional” method from the UMI-tools by Smith, Heger and Sudbery (Genome Research 2017). - 1MM_Directional … same as 1MM_Directional_UMItools, but with more stringent criteria for duplicate UMIs - Exact … only exactly matching UMIs are collapsed. - NoDedup … no deduplication of UMIs, count all reads. - 1MM_CR … CellRanger2-4 algorithm for 1MM UMI collapsing.\nstring, example: \"1MM_All\"\n\n\n--soloUMIfiltering\ntype of UMI filtering (for reads uniquely mapping to genes) - - … basic filtering: remove UMIs with N and homopolymers (similar to CellRanger 2.2.0). - MultiGeneUMI … basic + remove lower-count UMIs that map to more than one gene. - MultiGeneUMI_All … basic + remove all UMIs that map to more than one gene. - MultiGeneUMI_CR … basic + remove lower-count UMIs that map to more than one gene, matching CellRanger > 3.0.0 . Only works with –soloUMIdedup 1MM_CR\nstring\n\n\n--soloOutFileNames\nfile names for STARsolo output: file_name_prefix gene_names barcode_sequences cell_feature_count_matrix\nstring, example: \"Solo.out/\", example: \"features.tsv\", example: \"barcodes.tsv\", example: \"matrix.mtx\"\n\n\n--soloCellFilter\ncell filtering type and parameters - None … do not output filtered cells - TopCells … only report top cells by UMI count, followed by the exact number of cells - CellRanger2.2 … simple filtering of CellRanger 2.2. Can be followed by numbers: number of expected cells, robust maximum percentile for UMI count, maximum to minimum ratio for UMI count The harcoded values are from CellRanger: nExpectedCells=3000; maxPercentile=0.99; maxMinRatio=10 - EmptyDrops_CR … EmptyDrops filtering in CellRanger flavor. Please cite the original EmptyDrops paper: A.T.L Lun et al, Genome Biology, 20, 63 (2019): https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1662-y Can be followed by 10 numeric parameters: nExpectedCells maxPercentile maxMinRatio indMin indMax umiMin umiMinFracMedian candMaxN FDR simN The harcoded values are from CellRanger: 3000 0.99 10 45000 90000 500 0.01 20000 0.01 10000\nstring, example: \"CellRanger2.2\", example: \"3000\", example: \"0.99\", example: \"10\"\n\n\n--soloOutFormatFeaturesGeneField3\nfield 3 in the Gene features.tsv file. If “-”, then no 3rd field is output.\nstring, example: \"Gene Expression\"\n\n\n--soloCellReadStats\nOutput reads statistics for each CB - Standard … standard output\nstring" + }, + { + "objectID": "components/modules/mapping/star_align_v273a.html#authors", + "href": "components/modules/mapping/star_align_v273a.html#authors", + "title": "Star align v273a", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/mapping/bd_rhapsody.html", + "href": "components/modules/mapping/bd_rhapsody.html", + "title": "BD Rhapsody", + "section": "", + "text": "ID: bd_rhapsody\nNamespace: mapping\n\n\n\nSource\nA wrapper for the BD Rhapsody Analysis CWL v1.10.1 pipeline.\nThe CWL pipeline file is obtained by cloning ‘https://bitbucket.org/CRSwDev/cwl/src/master/’ and removing all objects with class ‘DockerRequirement’ from the YML.\nThis pipeline can be used for a targeted analysis (with --mode targeted) or for a whole transcriptome analysis (with --mode wta).\nThe reference_genome and transcriptome_annotation files can be generated with the make_reference pipeline. Alternatively, BD also provides standard references which can be downloaded from these locations:" + }, + { + "objectID": "components/modules/mapping/bd_rhapsody.html#example-commands", + "href": "components/modules/mapping/bd_rhapsody.html#example-commands", + "title": "BD Rhapsody", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/mapping/bd_rhapsody/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\nmode: # please fill in - example: \"wta\"\ninput: # please fill in - example: [\"input.fastq.gz\"]\nreference: # please fill in - example: [\"reference_genome.tar.gz|reference.fasta\"]\n# transcriptome_annotation: \"transcriptome.gtf\"\n# abseq_reference: [\"abseq_reference.fasta\"]\n# supplemental_reference: [\"supplemental_reference.fasta\"]\nsample_prefix: \"sample\"\n\n# Outputs\n# output: \"$id.$key.output.output\"\n\n# Putative cell calling settings\n# putative_cell_call: \"mRNA\"\n# exact_cell_count: 10000\ndisable_putative_calling: false\n\n# Subsample arguments\n# subsample: 0.01\n# subsample_seed: 3445\n\n# Multiplex arguments\n# sample_tags_version: \"human\"\n# tag_names: [\"4-mySample\", \"9-myOtherSample\", \"6-alsoThisSample\"]\n\n# VDJ arguments\n# vdj_version: \"human\"\n\n# CWL-runner arguments\nparallel: true\ntimestamps: false\ndryrun: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/mapping/bd_rhapsody/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/mapping/bd_rhapsody.html#argument-groups", + "href": "components/modules/mapping/bd_rhapsody.html#argument-groups", + "title": "BD Rhapsody", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--mode\nWhether to run a whole transcriptome analysis (WTA) or a targeted analysis.\nstring, required, example: \"wta\"\n\n\n--input\nPath to your read files in the FASTQ.GZ format. You may specify as many R1/R2 read pairs as you want.\nfile, required, example: \"input.fastq.gz\"\n\n\n--reference\nRefence to map to. For --mode wta, this is the path to STAR index as a tar.gz file. For --mode targeted, this is the path to mRNA reference file for pre-designed, supplemental, or custom panel, in FASTA format\nfile, required, example: \"reference_genome.tar.gz|reference.fasta\"\n\n\n--transcriptome_annotation\nPath to GTF annotation file (only for --mode wta).\nfile, example: \"transcriptome.gtf\"\n\n\n--abseq_reference\nPath to the AbSeq reference file in FASTA format. Only needed if BD AbSeq Ab-Oligos are used.\nfile, example: \"abseq_reference.fasta\"\n\n\n--supplemental_reference\nPath to the supplemental reference file in FASTA format. Only needed if there are additional transgene sequences used in the experiment (only for --mode wta).\nfile, example: \"supplemental_reference.fasta\"\n\n\n--sample_prefix\nSpecify a run name to use as the output file base name. Use only letters, numbers, or hyphens. Do not use special characters or spaces.\nstring, default: \"sample\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput folder. Output still needs to be processed further.\nfile, required, example: \"output_dir\"\n\n\n\n\n\nPutative cell calling settings\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--putative_cell_call\nSpecify the dataset to be used for putative cell calling. For putative cell calling using an AbSeq dataset, please provide an AbSeq_Reference fasta file above.\nstring, example: \"mRNA\"\n\n\n--exact_cell_count\nExact cell count - Set a specific number (>=1) of cells as putative, based on those with the highest error-corrected read count\ninteger, example: 10000\n\n\n--disable_putative_calling\nDisable Refined Putative Cell Calling - Determine putative cells using only the basic algorithm (minimum second derivative along the cumulative reads curve). The refined algorithm attempts to remove false positives and recover false negatives, but may not be ideal for certain complex mixtures of cell types. Does not apply if Exact Cell Count is set.\nboolean_true\n\n\n\n\n\nSubsample arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--subsample\nA number >1 or fraction (0 < n < 1) to indicate the number or percentage of reads to subsample.\ndouble, example: 0.01\n\n\n--subsample_seed\nA seed for replicating a previous subsampled run.\ninteger, example: 3445\n\n\n\n\n\nMultiplex arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--sample_tags_version\nSpecify if multiplexed run.\nstring, example: \"human\"\n\n\n--tag_names\nTag_Names (optional) - Specify the tag number followed by ‘-’ and the desired sample name to appear in Sample_Tag_Metrics.csv. Do not use the special characters: &, (), [], {}, <>, ?, |\nstring, example: \"4-mySample\", example: \"9-myOtherSample\", example: \"6-alsoThisSample\"\n\n\n\n\n\nVDJ arguments\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--vdj_version\nSpecify if VDJ run.\nstring, example: \"human\"\n\n\n\n\n\nCWL-runner arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--parallel\nRun jobs in parallel.\nboolean, default: TRUE\n\n\n--timestamps\nAdd timestamps to the errors, warnings, and notifications.\nboolean_true\n\n\n--dryrun\nIf true, the output directory will only contain the CWL input files, but the pipeline itself will not be executed.\nboolean_true" + }, + { + "objectID": "components/modules/mapping/bd_rhapsody.html#authors", + "href": "components/modules/mapping/bd_rhapsody.html#authors", + "title": "BD Rhapsody", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/integrate/totalvi.html", + "href": "components/modules/integrate/totalvi.html", + "title": "Totalvi", + "section": "", + "text": "ID: totalvi\nNamespace: integrate\n\n\n\nSource" + }, + { + "objectID": "components/modules/integrate/totalvi.html#example-commands", + "href": "components/modules/integrate/totalvi.html#example-commands", + "title": "Totalvi", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/integrate/totalvi/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"path/to/file\"\nreference: # please fill in - example: \"path/to/file\"\nforce_retrain: false\nquery_modality: \"rna\"\n# query_proteins_modality: \"foo\"\nreference_modality: \"rna\"\nreference_proteins_modality: \"prot\"\n# input_layer: \"foo\"\nobs_batch: \"sample_id\"\n# var_input: \"foo\"\n\n# Outputs\n# output: \"$id.$key.output.output\"\nobsm_output: \"X_integrated_totalvi\"\nobsm_normalized_rna_output: \"X_totalvi_normalized_rna\"\nobsm_normalized_protein_output: \"X_totalvi_normalized_protein\"\n# reference_model_path: \"$id.$key.reference_model_path.reference_model_path\"\n# query_model_path: \"$id.$key.query_model_path.query_model_path\"\n\n# Learning parameters\nmax_epochs: 400\nmax_query_epochs: 200\nweight_decay: 0.0\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/integrate/totalvi/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/integrate/totalvi.html#argument-groups", + "href": "components/modules/integrate/totalvi.html#argument-groups", + "title": "Totalvi", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file with query data to integrate with reference.\nfile, required\n\n\n--reference\nInput h5mu file with reference data to train the TOTALVI model.\nfile, required\n\n\n--force_retrain\nIf true, retrain the model and save it to reference_model_path\nboolean_true\n\n\n--query_modality\n\nstring, default: \"rna\"\n\n\n--query_proteins_modality\nName of the modality in the input (query) h5mu file containing protein data\nstring\n\n\n--reference_modality\n\nstring, default: \"rna\"\n\n\n--reference_proteins_modality\nName of the modality containing proteins in the reference\nstring, default: \"prot\"\n\n\n--input_layer\nInput layer to use. If None, X is used\nstring\n\n\n--obs_batch\nColumn name discriminating between your batches.\nstring, default: \"sample_id\"\n\n\n--var_input\n.var column containing highly variable genes. By default, do not subset genes.\nstring\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required\n\n\n--obsm_output\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_integrated_totalvi\"\n\n\n--obsm_normalized_rna_output\nIn which .obsm slot to store the normalized RNA from TOTALVI.\nstring, default: \"X_totalvi_normalized_rna\"\n\n\n--obsm_normalized_protein_output\nIn which .obsm slot to store the normalized protein data from TOTALVI.\nstring, default: \"X_totalvi_normalized_protein\"\n\n\n--reference_model_path\nDirectory with the reference model. If not exists, trained model will be saved there\nfile, default: \"totalvi_model_reference\"\n\n\n--query_model_path\nDirectory, where the query model will be saved\nfile, default: \"totalvi_model_query\"\n\n\n\n\n\nLearning parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--max_epochs\nNumber of passes through the dataset\ninteger, default: 400\n\n\n--max_query_epochs\nNumber of passes through the dataset, when fine-tuning model for query\ninteger, default: 200\n\n\n--weight_decay\nWeight decay, when fine-tuning model for query\ndouble, default: 0" + }, + { + "objectID": "components/modules/integrate/totalvi.html#authors", + "href": "components/modules/integrate/totalvi.html#authors", + "title": "Totalvi", + "section": "Authors", + "text": "Authors\n\nVladimir Shitov" + }, + { + "objectID": "components/modules/integrate/scvi.html", + "href": "components/modules/integrate/scvi.html", + "title": "Scvi", + "section": "", + "text": "ID: scvi\nNamespace: integrate\n\n\n\nSource" + }, + { + "objectID": "components/modules/integrate/scvi.html#example-commands", + "href": "components/modules/integrate/scvi.html#example-commands", + "title": "Scvi", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/integrate/scvi/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"path/to/file\"\nmodality: \"rna\"\n# input_layer: \"foo\"\nobs_batch: \"sample_id\"\n# var_input: \"foo\"\n# obs_labels: \"foo\"\n# obs_size_factor: \"foo\"\n# obs_categorical_covariate: [\"foo\"]\n# obs_continuous_covariate: [\"foo\"]\n\n# Outputs\n# output: \"$id.$key.output.output\"\n# model_output: \"$id.$key.model_output.model_output\"\n# output_compression: \"gzip\"\nobsm_output: \"X_scvi_integrated\"\n\n# SCVI options\nn_hidden_nodes: 128\nn_dimensions_latent_space: 30\nn_hidden_layers: 2\ndropout_rate: 0.1\ndispersion: \"gene\"\ngene_likelihood: \"nb\"\n\n# Variational auto-encoder model options\nuse_layer_normalization: \"both\"\nuse_batch_normalization: \"none\"\nencode_covariates: true\ndeeply_inject_covariates: false\nuse_observed_lib_size: false\n\n# Early stopping arguments\n# early_stopping: true\nearly_stopping_monitor: \"elbo_validation\"\nearly_stopping_patience: 45\nearly_stopping_min_delta: 0.0\n\n# Learning parameters\n# max_epochs: 123\nreduce_lr_on_plateau: true\nlr_factor: 0.6\nlr_patience: 30\n\n# Data validition\nn_obs_min_count: 0\nn_var_min_count: 0\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/integrate/scvi/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/integrate/scvi.html#argument-groups", + "href": "components/modules/integrate/scvi.html#argument-groups", + "title": "Scvi", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--input_layer\nInput layer to use. If None, X is used\nstring\n\n\n--obs_batch\nColumn name discriminating between your batches.\nstring, default: \"sample_id\"\n\n\n--var_input\n.var column containing highly variable genes. By default, do not subset genes.\nstring\n\n\n--obs_labels\nKey in adata.obs for label information. Categories will automatically be converted into integer categories and saved to adata.obs[’_scvi_labels’]. If None, assigns the same label to all the data.\nstring\n\n\n--obs_size_factor\nKey in adata.obs for size factor information. Instead of using library size as a size factor, the provided size factor column will be used as offset in the mean of the likelihood. Assumed to be on linear scale.\nstring\n\n\n--obs_categorical_covariate\nKeys in adata.obs that correspond to categorical data. These covariates can be added in addition to the batch covariate and are also treated as nuisance factors (i.e., the model tries to minimize their effects on the latent space). Thus, these should not be used for biologically-relevant factors that you do not want to correct for.\nstring\n\n\n--obs_continuous_covariate\nKeys in adata.obs that correspond to continuous data. These covariates can be added in addition to the batch covariate and are also treated as nuisance factors (i.e., the model tries to minimize their effects on the latent space). Thus, these should not be used for biologically-relevant factors that you do not want to correct for.\nstring\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required\n\n\n--model_output\nFolder where the state of the trained model will be saved to.\nfile\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--obsm_output\nIn which .obsm slot to store the resulting integrated embedding.\nstring, default: \"X_scvi_integrated\"\n\n\n\n\n\nSCVI options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--n_hidden_nodes\nNumber of nodes per hidden layer.\ninteger, default: 128\n\n\n--n_dimensions_latent_space\nDimensionality of the latent space.\ninteger, default: 30\n\n\n--n_hidden_layers\nNumber of hidden layers used for encoder and decoder neural-networks.\ninteger, default: 2\n\n\n--dropout_rate\nDropout rate for the neural networks.\ndouble, default: 0.1\n\n\n--dispersion\nSet the behavior for the dispersion for negative binomial distributions: - gene: dispersion parameter of negative binomial is constant per gene across cells - gene-batch: dispersion can differ between different batches - gene-label: dispersion can differ between different labels - gene-cell: dispersion can differ for every gene in every cell\nstring, default: \"gene\"\n\n\n--gene_likelihood\nModel used to generate the expression data from a count-based likelihood distribution. - nb: Negative binomial distribution - zinb: Zero-inflated negative binomial distribution - poisson: Poisson distribution\nstring, default: \"nb\"\n\n\n\n\n\nVariational auto-encoder model options\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--use_layer_normalization\nNeural networks for which to enable layer normalization.\nstring, default: \"both\"\n\n\n--use_batch_normalization\nNeural networks for which to enable batch normalization.\nstring, default: \"none\"\n\n\n--encode_covariates\nWhether to concatenate covariates to expression in encoder\nboolean_false\n\n\n--deeply_inject_covariates\nWhether to concatenate covariates into output of hidden layers in encoder/decoder. This option only applies when n_layers > 1. The covariates are concatenated to the input of subsequent hidden layers.\nboolean_true\n\n\n--use_observed_lib_size\nUse observed library size for RNA as scaling factor in mean of conditional distribution.\nboolean_true\n\n\n\n\n\nEarly stopping arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--early_stopping\nWhether to perform early stopping with respect to the validation set.\nboolean\n\n\n--early_stopping_monitor\nMetric logged during validation set epoch.\nstring, default: \"elbo_validation\"\n\n\n--early_stopping_patience\nNumber of validation epochs with no improvement after which training will be stopped.\ninteger, default: 45\n\n\n--early_stopping_min_delta\nMinimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.\ndouble, default: 0\n\n\n\n\n\nLearning parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--max_epochs\nNumber of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.\ninteger\n\n\n--reduce_lr_on_plateau\nWhether to monitor validation loss and reduce learning rate when validation set lr_scheduler_metric plateaus.\nboolean, default: TRUE\n\n\n--lr_factor\nFactor to reduce learning rate.\ndouble, default: 0.6\n\n\n--lr_patience\nNumber of epochs with no improvement after which learning rate will be reduced.\ndouble, default: 30\n\n\n\n\n\nData validition\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--n_obs_min_count\nMinimum number of cells threshold ensuring that every obs_batch category has sufficient observations (cells) for model training.\ninteger, default: 0\n\n\n--n_var_min_count\nMinimum number of genes threshold ensuring that every var_input filter has sufficient observations (genes) for model training.\ninteger, default: 0" + }, + { + "objectID": "components/modules/integrate/scvi.html#authors", + "href": "components/modules/integrate/scvi.html#authors", + "title": "Scvi", + "section": "Authors", + "text": "Authors\n\nMalte D. Luecken (author)\nDries Schaumont (maintainer)\nMatthias Beyens (contributor)" + }, + { + "objectID": "components/modules/query/cellxgene_census.html", + "href": "components/modules/query/cellxgene_census.html", + "title": "Cellxgene census", + "section": "", + "text": "ID: cellxgene_census\nNamespace: query\n\n\n\nSource" + }, + { + "objectID": "components/modules/query/cellxgene_census.html#example-commands", + "href": "components/modules/query/cellxgene_census.html#example-commands", + "title": "Cellxgene census", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/query/cellxgene_census/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput_database: \"CellxGene\"\nmodality: \"rna\"\ncellxgene_release: \"2023-05-15\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Query\nspecies: \"homo_sapiens\"\n# cell_query: \"is_primary_data == True and cell_type_ontology_term_id in ['CL:0000136', 'CL:1000311', 'CL:0002616'] and suspension_type == 'cell'\"\n# cells_filter_columns: [\"dataset_id\", \"tissue\", \"assay\", \"disease\", \"cell_type\"]\n# min_cells_filter_columns: 100\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/query/cellxgene_census/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/query/cellxgene_census.html#argument-groups", + "href": "components/modules/query/cellxgene_census.html#argument-groups", + "title": "Cellxgene census", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\nArguments related to the input (aka query) dataset.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input_database\nFull input database S3 prefix URL. Default: CellxGene Census\nstring, default: \"CellxGene\", example: \"s3://\"\n\n\n--modality\nWhich modality to store the output in.\nstring, default: \"rna\"\n\n\n--cellxgene_release\nCellxGene Census release date. More information: https://chanzuckerberg.github.io/cellxgene-census/cellxgene_census_docsite_data_release_info.html\nstring, default: \"2023-05-15\"\n\n\n\n\n\nQuery\nArguments related to the query.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--species\nSpecie(s) of interest. If not specified, Homo Sapiens will be queried.\nstring, default: \"homo_sapiens\", example: \"homo_sapiens\"\n\n\n--cell_query\nThe query for selecting the cells as defined by the cellxgene census schema.\nstring, example: \"is_primary_data == True and cell_type_ontology_term_id in ['CL:0000136', 'CL:1000311', 'CL:0002616'] and suspension_type == 'cell'\"\n\n\n--cells_filter_columns\nThe query for selecting the cells as defined by the cellxgene census schema.\nstring, example: \"dataset_id\", example: \"tissue\", example: \"assay\", example: \"disease\", example: \"cell_type\"\n\n\n--min_cells_filter_columns\nMinimum of amount of summed cells_filter_columns cells\ndouble, example: 100\n\n\n\n\n\nOutputs\nOutput arguments.\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/query/cellxgene_census.html#authors", + "href": "components/modules/query/cellxgene_census.html#authors", + "title": "Cellxgene census", + "section": "Authors", + "text": "Authors\n\nMatthias Beyens \nDries De Maeyer (author)" + }, + { + "objectID": "components/modules/reference/build_bdrhap_reference.html", + "href": "components/modules/reference/build_bdrhap_reference.html", + "title": "Build bdrhap reference", + "section": "", + "text": "ID: build_bdrhap_reference\nNamespace: reference\n\n\n\nSource" + }, + { + "objectID": "components/modules/reference/build_bdrhap_reference.html#example-commands", + "href": "components/modules/reference/build_bdrhap_reference.html#example-commands", + "title": "Build bdrhap reference", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/reference/build_bdrhap_reference/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ngenome_fasta: # please fill in - example: \"genome_sequence.fa.gz\"\ntranscriptome_gtf: # please fill in - example: \"transcriptome_annotation.gtf.gz\"\n# output: \"$id.$key.output.gz\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/reference/build_bdrhap_reference/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/reference/build_bdrhap_reference.html#argument-group", + "href": "components/modules/reference/build_bdrhap_reference.html#argument-group", + "title": "Build bdrhap reference", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--genome_fasta\nReference genome fasta.\nfile, required, example: \"genome_sequence.fa.gz\"\n\n\n--transcriptome_gtf\nReference transcriptome annotation.\nfile, required, example: \"transcriptome_annotation.gtf.gz\"\n\n\n--output\nStar index\nfile, required, example: \"star_index.tar.gz\"" + }, + { + "objectID": "components/modules/reference/build_bdrhap_reference.html#authors", + "href": "components/modules/reference/build_bdrhap_reference.html#authors", + "title": "Build bdrhap reference", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (author, maintainer)" + }, + { + "objectID": "components/modules/dimred/umap.html", + "href": "components/modules/dimred/umap.html", + "title": "Umap", + "section": "", + "text": "ID: umap\nNamespace: dimred\n\n\n\nSource\nBesides tending to be faster than tSNE, it optimizes the embedding such that it best reflects the topology of the data, which we represent throughout Scanpy using a neighborhood graph. tSNE, by contrast, optimizes the distribution of nearest-neighbor distances in the embedding such that these best match the distribution of distances in the high-dimensional space. We use the implementation of umap-learn [McInnes18]. For a few comparisons of UMAP with tSNE, see this preprint" + }, + { + "objectID": "components/modules/dimred/umap.html#example-commands", + "href": "components/modules/dimred/umap.html#example-commands", + "title": "Umap", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/dimred/umap/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\nuns_neighbors: \"neighbors\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nobsm_output: \"umap\"\n\n# Arguments\nmin_dist: 0.5\nspread: 1.0\nnum_components: 2\n# max_iter: 123\nalpha: 1.0\ngamma: 1.0\nnegative_sample_rate: 5\ninit_pos: \"spectral\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/dimred/umap/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/dimred/umap.html#argument-groups", + "href": "components/modules/dimred/umap.html#argument-groups", + "title": "Umap", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--uns_neighbors\nThe .uns neighbors slot as output by the find_neighbors component.\nstring, default: \"neighbors\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--obsm_output\nThe pre/postfix under which to store the UMAP results.\nstring, default: \"umap\"\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--min_dist\nThe effective minimum distance between embedded points. Smaller values will result in a more clustered/clumped embedding where nearby points on the manifold are drawn closer together, while larger values will result on a more even dispersal of points. The value should be set relative to the spread value, which determines the scale at which embedded points will be spread out.\ndouble, default: 0.5\n\n\n--spread\nThe effective scale of embedded points. In combination with min_dist this determines how clustered/clumped the embedded points are.\ndouble, default: 1\n\n\n--num_components\nThe number of dimensions of the embedding.\ninteger, default: 2\n\n\n--max_iter\nThe number of iterations (epochs) of the optimization. Called n_epochs in the original UMAP. Default is set to 500 if neighbors[‘connectivities’].shape[0] <= 10000, else 200.\ninteger\n\n\n--alpha\nThe initial learning rate for the embedding optimization.\ndouble, default: 1\n\n\n--gamma\nWeighting applied to negative samples in low dimensional embedding optimization. Values higher than one will result in greater weight being given to negative samples.\ndouble, default: 1\n\n\n--negative_sample_rate\nThe number of negative edge/1-simplex samples to use per positive edge/1-simplex sample in optimizing the low dimensional embedding.\ninteger, default: 5\n\n\n--init_pos\nHow to initialize the low dimensional embedding. Called init in the original UMAP. Options are: * Any key from .obsm * 'paga': positions from paga() * 'spectral': use a spectral embedding of the graph * 'random': assign initial embedding positions at random.\nstring, default: \"spectral\"" + }, + { + "objectID": "components/modules/dimred/umap.html#authors", + "href": "components/modules/dimred/umap.html#authors", + "title": "Umap", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)" + }, + { + "objectID": "components/modules/filter/do_filter.html", + "href": "components/modules/filter/do_filter.html", + "title": "Do filter", + "section": "", + "text": "ID: do_filter\nNamespace: filter\n\n\n\nSource" + }, + { + "objectID": "components/modules/filter/do_filter.html#example-commands", + "href": "components/modules/filter/do_filter.html#example-commands", + "title": "Do filter", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/filter/do_filter/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# obs_filter: [\"filter_with_x\"]\n# var_filter: [\"filter_with_x\"]\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/filter/do_filter/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/filter/do_filter.html#argument-group", + "href": "components/modules/filter/do_filter.html#argument-group", + "title": "Do filter", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--obs_filter\nWhich .obs columns to use to filter the observations by.\nstring, example: \"filter_with_x\"\n\n\n--var_filter\nWhich .var columns to use to filter the observations by.\nstring, example: \"filter_with_x\"\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/filter/do_filter.html#authors", + "href": "components/modules/filter/do_filter.html#authors", + "title": "Do filter", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer, contributor)" + }, + { + "objectID": "components/modules/filter/filter_with_hvg.html", + "href": "components/modules/filter/filter_with_hvg.html", + "title": "Filter with hvg", + "section": "", + "text": "ID: filter_with_hvg\nNamespace: filter\n\n\n\nSource\nExpects logarithmized data, except when flavor=‘seurat_v3’ in which count data is expected.\nDepending on flavor, this reproduces the R-implementations of Seurat [Satija15], Cell Ranger [Zheng17], and Seurat v3 [Stuart19].\nFor the dispersion-based methods ([Satija15] and [Zheng17]), the normalized dispersion is obtained by scaling with the mean and standard deviation of the dispersions for genes falling into a given bin for mean expression of genes. This means that for each bin of mean expression, highly variable genes are selected.\nFor [Stuart19], a normalized variance for each gene is computed. First, the data are standardized (i.e., z-score normalization per feature) with a regularized standard deviation. Next, the normalized variance is computed as the variance of each gene after the transformation. Genes are ranked by the normalized variance." + }, + { + "objectID": "components/modules/filter/filter_with_hvg.html#example-commands", + "href": "components/modules/filter/filter_with_hvg.html#example-commands", + "title": "Filter with hvg", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/filter/filter_with_hvg/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# layer: \"foo\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nvar_name_filter: \"filter_with_hvg\"\nvarm_name: \"hvg\"\ndo_subset: false\nflavor: \"seurat\"\n# n_top_genes: 123\nmin_mean: 0.0125\nmax_mean: 3\nmin_disp: 0.5\n# max_disp: 123.0\nspan: 0.3\nn_bins: 20\n# obs_batch_key: \"foo\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/filter/filter_with_hvg/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/filter/filter_with_hvg.html#argument-group", + "href": "components/modules/filter/filter_with_hvg.html#argument-group", + "title": "Filter with hvg", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--layer\nuse adata.layers[layer] for expression values instead of adata.X.\nstring\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--var_name_filter\nIn which .var slot to store a boolean array corresponding to which observations should be filtered out.\nstring, default: \"filter_with_hvg\"\n\n\n--varm_name\nIn which .varm slot to store additional metadata.\nstring, default: \"hvg\"\n\n\n--do_subset\nWhether to subset before storing the output.\nboolean_true\n\n\n--flavor\nChoose the flavor for identifying highly variable genes. For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_genes.\nstring, default: \"seurat\"\n\n\n--n_top_genes\nNumber of highly-variable genes to keep. Mandatory if flavor=‘seurat_v3’.\ninteger\n\n\n--min_mean\nIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’.\ndouble, default: 0.0125\n\n\n--max_mean\nIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’.\ndouble, default: 3\n\n\n--min_disp\nIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’.\ndouble, default: 0.5\n\n\n--max_disp\nIf n_top_genes is defined, this and all other cutoffs for the means and the normalized dispersions are ignored. Ignored if flavor=‘seurat_v3’. Default is +inf.\ndouble\n\n\n--span\nThe fraction of the data (cells) used when estimating the variance in the loess model fit if flavor=‘seurat_v3’.\ndouble, default: 0.3\n\n\n--n_bins\nNumber of bins for binning the mean gene expression. Normalization is done with respect to each bin. If just a single gene falls into a bin, the normalized dispersion is artificially set to 1.\ninteger, default: 20\n\n\n--obs_batch_key\nIf specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method. For all flavors, genes are first sorted by how many batches they are a HVG. For dispersion-based flavors ties are broken by normalized dispersion. If flavor = ‘seurat_v3’, ties are broken by the median (across batches) rank based on within-batch normalized variance.\nstring" + }, + { + "objectID": "components/modules/filter/filter_with_hvg.html#authors", + "href": "components/modules/filter/filter_with_hvg.html#authors", + "title": "Filter with hvg", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (contributor)\nRobrecht Cannoodt (maintainer, contributor)" + }, + { + "objectID": "components/modules/filter/subset_h5mu.html", + "href": "components/modules/filter/subset_h5mu.html", + "title": "Subset h5mu", + "section": "", + "text": "ID: subset_h5mu\nNamespace: filter\n\n\n\nSource" + }, + { + "objectID": "components/modules/filter/subset_h5mu.html#example-commands", + "href": "components/modules/filter/subset_h5mu.html#example-commands", + "title": "Subset h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/filter/subset_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n# number_of_observations: 5\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/filter/subset_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/filter/subset_h5mu.html#argument-group", + "href": "components/modules/filter/subset_h5mu.html#argument-group", + "title": "Subset h5mu", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--number_of_observations\nNumber of observations to be selected from the h5mu file.\ninteger, example: 5" + }, + { + "objectID": "components/modules/filter/subset_h5mu.html#authors", + "href": "components/modules/filter/subset_h5mu.html#authors", + "title": "Subset h5mu", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/correction/cellbender_remove_background.html", + "href": "components/modules/correction/cellbender_remove_background.html", + "title": "Cellbender remove background", + "section": "", + "text": "ID: cellbender_remove_background\nNamespace: correction\n\n\n\nSource\nThis module removes counts due to ambient RNA molecules and random barcode swapping from (raw) UMI-based scRNA-seq count matrices. At the moment, only the count matrices produced by the CellRanger count pipeline is supported. Support for additional tools and protocols will be added in the future. A quick start tutorial can be found here.\nFleming et al. 2022, bioRxiv." + }, + { + "objectID": "components/modules/correction/cellbender_remove_background.html#example-commands", + "href": "components/modules/correction/cellbender_remove_background.html#example-commands", + "title": "Cellbender remove background", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/correction/cellbender_remove_background/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nlayer_output: \"cellbender_corrected\"\nobs_background_fraction: \"cellbender_background_fraction\"\nobs_cell_probability: \"cellbender_cell_probability\"\nobs_cell_size: \"cellbender_cell_size\"\nobs_droplet_efficiency: \"cellbender_droplet_efficiency\"\nobs_latent_scale: \"cellbender_latent_scale\"\nvar_ambient_expression: \"cellbender_ambient_expression\"\nobsm_gene_expression_encoding: \"cellbender_gene_expression_encoding\"\n\n# Arguments\nexpected_cells_from_qc: false\n# expected_cells: 1000\n# total_droplets_included: 25000\n# force_cell_umi_prior: 123\n# force_empty_umi_prior: 123\nmodel: \"full\"\nepochs: 150\nlow_count_threshold: 5\nz_dim: 64\nz_layers: [512]\ntraining_fraction: 0.9\nempty_drop_training_fraction: 0.2\n# ignore_features: [123]\nfpr: [0.01]\n# exclude_feature_types: [\"foo\"]\nprojected_ambient_count_threshold: 0.1\nlearning_rate: 1.0E-4\n# final_elbo_fail_fraction: 123.0\n# epoch_elbo_fail_fraction: 123.0\nnum_training_tries: 1\nlearning_rate_retry_mult: 0.2\nposterior_batch_size: 128\n# posterior_regulation: \"foo\"\n# alpha: 123.0\n# q: 123.0\nestimator: \"mckp\"\nestimator_multiple_cpu: false\n# constant_learning_rate: true\ndebug: false\ncuda: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/correction/cellbender_remove_background/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/correction/cellbender_remove_background.html#argument-groups", + "href": "components/modules/correction/cellbender_remove_background.html#argument-groups", + "title": "Cellbender remove background", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file. Data file on which to run tool. Data must be un-filtered: it should include empty droplets.\nfile, required, example: \"input.h5mu\"\n\n\n--modality\nList of modalities to process.\nstring, default: \"rna\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nFull count matrix as an h5mu file, with background RNA removed. This file contains all the original droplet barcodes.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"\n\n\n--layer_output\nOutput layer\nstring, default: \"cellbender_corrected\"\n\n\n--obs_background_fraction\n\nstring, default: \"cellbender_background_fraction\"\n\n\n--obs_cell_probability\n\nstring, default: \"cellbender_cell_probability\"\n\n\n--obs_cell_size\n\nstring, default: \"cellbender_cell_size\"\n\n\n--obs_droplet_efficiency\n\nstring, default: \"cellbender_droplet_efficiency\"\n\n\n--obs_latent_scale\n\nstring, default: \"cellbender_latent_scale\"\n\n\n--var_ambient_expression\n\nstring, default: \"cellbender_ambient_expression\"\n\n\n--obsm_gene_expression_encoding\n\nstring, default: \"cellbender_gene_expression_encoding\"\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--expected_cells_from_qc\nWill use the Cell Ranger QC to determine the estimated number of cells\nboolean, default: FALSE\n\n\n--expected_cells\nNumber of cells expected in the dataset (a rough estimate within a factor of 2 is sufficient).\ninteger, example: 1000\n\n\n--total_droplets_included\nThe number of droplets from the rank-ordered UMI plot that will have their cell probabilities inferred as an output. Include the droplets which might contain cells. Droplets beyond TOTAL_DROPLETS_INCLUDED should be ‘surely empty’ droplets.\ninteger, example: 25000\n\n\n--force_cell_umi_prior\nIgnore CellBender’s heuristic prior estimation, and use this prior for UMI counts in cells.\ninteger\n\n\n--force_empty_umi_prior\nIgnore CellBender’s heuristic prior estimation, and use this prior for UMI counts in empty droplets.\ninteger\n\n\n--model\nWhich model is being used for count data. * ‘naive’ subtracts the estimated ambient profile. * ‘simple’ does not model either ambient RNA or random barcode swapping (for debugging purposes – not recommended). * ‘ambient’ assumes background RNA is incorporated into droplets. * ‘swapping’ assumes background RNA comes from random barcode swapping (via PCR chimeras). * ‘full’ uses a combined ambient and swapping model.\nstring, default: \"full\"\n\n\n--epochs\nNumber of epochs to train.\ninteger, default: 150\n\n\n--low_count_threshold\nDroplets with UMI counts below this number are completely excluded from the analysis. This can help identify the correct prior for empty droplet counts in the rare case where empty counts are extremely high (over 200).\ninteger, default: 5\n\n\n--z_dim\nDimension of latent variable z.\ninteger, default: 64\n\n\n--z_layers\nDimension of hidden layers in the encoder for z.\ninteger, default: 512\n\n\n--training_fraction\nTraining detail: the fraction of the data used for training. The rest is never seen by the inference algorithm. Speeds up learning.\ndouble, default: 0.9\n\n\n--empty_drop_training_fraction\nTraining detail: the fraction of the training data each epoch that is drawn (randomly sampled) from surely empty droplets.\ndouble, default: 0.2\n\n\n--ignore_features\nInteger indices of features to ignore entirely. In the output count matrix, the counts for these features will be unchanged.\ninteger\n\n\n--fpr\nTarget ‘delta’ false positive rate in [0, 1). Use 0 for a cohort of samples which will be jointly analyzed for differential expression. A false positive is a true signal count that is erroneously removed. More background removal is accompanied by more signal removal at high values of FPR. You can specify multiple values, which will create multiple output files.\ndouble, default: 0.01\n\n\n--exclude_feature_types\nFeature types to ignore during the analysis. These features will be left unchanged in the output file.\nstring\n\n\n--projected_ambient_count_threshold\nControls how many features are included in the analysis, which can lead to a large speedup. If a feature is expected to have less than PROJECTED_AMBIENT_COUNT_THRESHOLD counts total in all cells (summed), then that gene is excluded, and it will be unchanged in the output count matrix. For example, PROJECTED_AMBIENT_COUNT_THRESHOLD = 0 will include all features which have even a single count in any empty droplet.\ndouble, default: 0.1\n\n\n--learning_rate\nTraining detail: lower learning rate for inference. A OneCycle learning rate schedule is used, where the upper learning rate is ten times this value. (For this value, probably do not exceed 1e-3).\ndouble, default: 1e-04\n\n\n--final_elbo_fail_fraction\nTraining is considered to have failed if (best_test_ELBO - final_test_ELBO)/(best_test_ELBO - initial_test_ELBO) > FINAL_ELBO_FAIL_FRACTION. Training will automatically re-run if –num-training-tries > 1. By default, will not fail training based on final_training_ELBO.\ndouble\n\n\n--epoch_elbo_fail_fraction\nTraining is considered to have failed if (previous_epoch_test_ELBO - current_epoch_test_ELBO)/(previous_epoch_test_ELBO - initial_train_ELBO) > EPOCH_ELBO_FAIL_FRACTION. Training will automatically re-run if –num-training-tries > 1. By default, will not fail training based on epoch_training_ELBO.\ndouble\n\n\n--num_training_tries\nNumber of times to attempt to train the model. At each subsequent attempt, the learning rate is multiplied by LEARNING_RATE_RETRY_MULT.\ninteger, default: 1\n\n\n--learning_rate_retry_mult\nLearning rate is multiplied by this amount each time a new training attempt is made. (This parameter is only used if training fails based on EPOCH_ELBO_FAIL_FRACTION or FINAL_ELBO_FAIL_FRACTION and NUM_TRAINING_TRIES is > 1.)\ndouble, default: 0.2\n\n\n--posterior_batch_size\nTraining detail: size of batches when creating the posterior. Reduce this to avoid running out of GPU memory creating the posterior (will be slower).\ninteger, default: 128\n\n\n--posterior_regulation\nPosterior regularization method. (For experts: not required for normal usage, see documentation). * PRq is approximate quantile-targeting. * PRmu is approximate mean-targeting aggregated over genes (behavior of v0.2.0). * PRmu_gene is approximate mean-targeting per gene.\nstring\n\n\n--alpha\nTunable parameter alpha for the PRq posterior regularization method (not normally used: see documentation).\ndouble\n\n\n--q\nTunable parameter q for the CDF threshold estimation method (not normally used: see documentation).\ndouble\n\n\n--estimator\nOutput denoised count estimation method. (For experts: not required for normal usage, see documentation).\nstring, default: \"mckp\"\n\n\n--estimator_multiple_cpu\nIncluding the flag –estimator-multiple-cpu will use more than one CPU to compute the MCKP output count estimator in parallel (does nothing for other estimators).\nboolean_true\n\n\n--constant_learning_rate\nIncluding the flag –constant-learning-rate will use the ClippedAdam optimizer instead of the OneCycleLR learning rate schedule, which is the default. Learning is faster with the OneCycleLR schedule. However, training can easily be continued from a checkpoint for more epochs than the initial command specified when using ClippedAdam. On the other hand, if using the OneCycleLR schedule with 150 epochs specified, it is not possible to pick up from that final checkpoint and continue training until 250 epochs.\nboolean\n\n\n--debug\nIncluding the flag –debug will log extra messages useful for debugging.\nboolean_true\n\n\n--cuda\nIncluding the flag –cuda will run the inference on a GPU.\nboolean_true" + }, + { + "objectID": "components/modules/convert/from_h5mu_to_h5ad.html", + "href": "components/modules/convert/from_h5mu_to_h5ad.html", + "title": "From h5mu to h5ad", + "section": "", + "text": "ID: from_h5mu_to_h5ad\nNamespace: convert\n\n\n\nSource" + }, + { + "objectID": "components/modules/convert/from_h5mu_to_h5ad.html#example-commands", + "href": "components/modules/convert/from_h5mu_to_h5ad.html#example-commands", + "title": "From h5mu to h5ad", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/from_h5mu_to_h5ad/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# output: \"$id.$key.output.h5ad\"\noutput_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/from_h5mu_to_h5ad/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/from_h5mu_to_h5ad.html#argument-group", + "href": "components/modules/convert/from_h5mu_to_h5ad.html#argument-group", + "title": "From h5mu to h5ad", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput MuData file\nfile, required, default: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--output\nOutput AnnData file.\nfile, default: \"output.h5ad\"\n\n\n--output_compression\nThe compression format to be used on the final h5ad object.\nstring, default: \"gzip\"" + }, + { + "objectID": "components/modules/convert/from_h5mu_to_h5ad.html#authors", + "href": "components/modules/convert/from_h5mu_to_h5ad.html#authors", + "title": "From h5mu to h5ad", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/convert/from_10xmtx_to_h5mu.html", + "href": "components/modules/convert/from_10xmtx_to_h5mu.html", + "title": "From 10xmtx to h5mu", + "section": "", + "text": "ID: from_10xmtx_to_h5mu\nNamespace: convert\n\n\n\nSource" + }, + { + "objectID": "components/modules/convert/from_10xmtx_to_h5mu.html#example-commands", + "href": "components/modules/convert/from_10xmtx_to_h5mu.html#example-commands", + "title": "From 10xmtx to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/from_10xmtx_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input_dir_containing_gz_files\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/from_10xmtx_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/from_10xmtx_to_h5mu.html#argument-group", + "href": "components/modules/convert/from_10xmtx_to_h5mu.html#argument-group", + "title": "From 10xmtx to h5mu", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput mtx folder\nfile, required, example: \"input_dir_containing_gz_files\"\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/convert/from_10xmtx_to_h5mu.html#authors", + "href": "components/modules/convert/from_10xmtx_to_h5mu.html#authors", + "title": "From 10xmtx to h5mu", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/convert/from_10xh5_to_h5mu.html", + "href": "components/modules/convert/from_10xh5_to_h5mu.html", + "title": "From 10xh5 to h5mu", + "section": "", + "text": "ID: from_10xh5_to_h5mu\nNamespace: convert\n\n\n\nSource" + }, + { + "objectID": "components/modules/convert/from_10xh5_to_h5mu.html#example-commands", + "href": "components/modules/convert/from_10xh5_to_h5mu.html#example-commands", + "title": "From 10xh5 to h5mu", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/from_10xh5_to_h5mu/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"raw_feature_bc_matrix.h5\"\n# input_metrics_summary: \"metrics_cellranger.h5\"\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nuns_metrics: \"metrics_cellranger\"\n\n# Arguments\n# min_genes: 100\n# min_counts: 1000\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/from_10xh5_to_h5mu/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/from_10xh5_to_h5mu.html#argument-groups", + "href": "components/modules/convert/from_10xh5_to_h5mu.html#argument-groups", + "title": "From 10xh5 to h5mu", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nA 10x h5 file as generated by Cell Ranger.\nfile, required, example: \"raw_feature_bc_matrix.h5\"\n\n\n--input_metrics_summary\nA metrics summary csv file as generated by Cell Ranger.\nfile, example: \"metrics_cellranger.h5\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\n\nstring, example: \"gzip\"\n\n\n--uns_metrics\nName of the .uns slot under which to QC metrics (if any).\nstring, default: \"metrics_cellranger\"\n\n\n\n\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--min_genes\nMinimum number of counts required for a cell to pass filtering.\ninteger, example: 100\n\n\n--min_counts\nMinimum number of genes expressed required for a cell to pass filtering.\ninteger, example: 1000" + }, + { + "objectID": "components/modules/convert/from_10xh5_to_h5mu.html#authors", + "href": "components/modules/convert/from_10xh5_to_h5mu.html#authors", + "title": "From 10xh5 to h5mu", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html", + "href": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html", + "title": "From bd to 10x molecular barcode tags", + "section": "", + "text": "ID: from_bd_to_10x_molecular_barcode_tags\nNamespace: convert\n\n\n\nSource" + }, + { + "objectID": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html#example-commands", + "href": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html#example-commands", + "title": "From bd to 10x molecular barcode tags", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/convert/from_bd_to_10x_molecular_barcode_tags/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.bam\"\n# output: \"$id.$key.output.sam\"\nbam: false\n# threads: 123\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/convert/from_bd_to_10x_molecular_barcode_tags/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html#argument-group", + "href": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html#argument-group", + "title": "From bd to 10x molecular barcode tags", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput SAM or BAM file.\nfile, required, example: \"input.bam\"\n\n\n--output\nOutput alignment file.\nfile, example: \"output.sam\"\n\n\n--bam\nOutput a BAM file.\nboolean_true\n\n\n--threads\nNumber of threads\ninteger" + }, + { + "objectID": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html#authors", + "href": "components/modules/convert/from_bd_to_10x_molecular_barcode_tags.html#authors", + "title": "From bd to 10x molecular barcode tags", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/labels_transfer/knn.html", + "href": "components/modules/labels_transfer/knn.html", + "title": "Knn", + "section": "", + "text": "ID: knn\nNamespace: labels_transfer\n\n\n\nSource" + }, + { + "objectID": "components/modules/labels_transfer/knn.html#example-commands", + "href": "components/modules/labels_transfer/knn.html#example-commands", + "title": "Knn", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/labels_transfer/knn/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Learning parameters\nn_neighbors: # please fill in - example: 123\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/labels_transfer/knn/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/labels_transfer/knn.html#argument-groups", + "href": "components/modules/labels_transfer/knn.html#argument-groups", + "title": "Knn", + "section": "Argument groups", + "text": "Argument groups\n\nInput dataset (query) arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nThe query data to transfer the labels to. Should be a .h5mu file.\nfile, required\n\n\n--modality\nWhich modality to use.\nstring, default: \"rna\"\n\n\n--input_obsm_features\nThe .obsm key of the embedding to use for the classifier’s inference. If not provided, the .X slot will be used instead. Make sure that embedding was obtained in the same way as the reference embedding (e.g. by the same model or preprocessing).\nstring, example: \"X_integrated_scanvi\"\n\n\n\n\n\nReference dataset arguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--reference\nThe reference data to train classifiers on.\nfile, example: \"https:/zenodo.org/record/6337966/files/HLCA_emb_and_metadata.h5ad\"\n\n\n--reference_obsm_features\nThe .obsm key of the embedding to use for the classifier’s training. Make sure that embedding was obtained in the same way as the query embedding (e.g. by the same model or preprocessing).\nstring, required, default: \"X_integrated_scanvi\"\n\n\n--reference_obs_targets\nThe .obs key of the target labels to tranfer.\nstring, default: \"ann_level_1\", default: \"ann_level_2\", default: \"ann_level_3\", default: \"ann_level_4\", default: \"ann_level_5\", default: \"ann_finest_level\"\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nThe query data in .h5mu format with predicted labels transfered from the reference.\nfile, required\n\n\n--output_obs_predictions\nIn which .obs slots to store the predicted information. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the \"_pred\" suffix.\nstring\n\n\n--output_obs_uncertainty\nIn which .obs slots to store the uncertainty of the predictions. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the \"_uncertainty\" suffix.\nstring\n\n\n--output_uns_parameters\nThe .uns key to store additional information about the parameters used for the label transfer.\nstring, default: \"labels_transfer\"\n\n\n\n\n\nLearning parameters\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--n_neighbors\nNumber of nearest neighbors to use for classification\ninteger, required" + }, + { + "objectID": "components/modules/labels_transfer/knn.html#authors", + "href": "components/modules/labels_transfer/knn.html#authors", + "title": "Knn", + "section": "Authors", + "text": "Authors\n\nVladimir Shitov (author)" + }, + { + "objectID": "components/modules/report/mermaid.html", + "href": "components/modules/report/mermaid.html", + "title": "Mermaid", + "section": "", + "text": "ID: mermaid\nNamespace: report\n\n\n\nSource" + }, + { + "objectID": "components/modules/report/mermaid.html#example-commands", + "href": "components/modules/report/mermaid.html#example-commands", + "title": "Mermaid", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/report/mermaid/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"path/to/file\"\n# output: \"$id.$key.output.output\"\n# output_format: \"foo\"\nwidth: 800\nheight: 600\nbackground_color: \"white\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/report/mermaid/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/report/mermaid.html#argument-group", + "href": "components/modules/report/mermaid.html#argument-group", + "title": "Mermaid", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput directory\nfile, required\n\n\n--output\nGenerated network as output.\nfile, required\n\n\n--output_format\nOutput format for the generated image. By default will be inferred from the extension of the file specified with –output.\nstring\n\n\n--width\nWidth of the page\ninteger, default: 800\n\n\n--height\nHeight of the page\ninteger, default: 600\n\n\n--background_color\nBackground color for pngs/svgs (not pdfs)\nstring, default: \"white\", example: \"#F0F0F0\"" + }, + { + "objectID": "components/modules/report/mermaid.html#authors", + "href": "components/modules/report/mermaid.html#authors", + "title": "Mermaid", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)" + }, + { + "objectID": "components/modules/download/download_file.html", + "href": "components/modules/download/download_file.html", + "title": "Download file", + "section": "", + "text": "ID: download_file\nNamespace: download\n\n\n\nSource" + }, + { + "objectID": "components/modules/download/download_file.html#example-commands", + "href": "components/modules/download/download_file.html#example-commands", + "title": "Download file", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/download/download_file/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"https://cf.10xgenomics.com/samples/cell-exp/3.0.0/pbmc_1k_protein_v3/pbmc_1k_protein_v3_raw_feature_bc_matrix.h5\"\n# output: \"$id.$key.output.h5\"\nverbose: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/download/download_file/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/download/download_file.html#argument-group", + "href": "components/modules/download/download_file.html#argument-group", + "title": "Download file", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nURL to a file to download.\nstring, required, example: \"https://cf.10xgenomics.com/samples/cell-exp/3.0.0/pbmc_1k_protein_v3/pbmc_1k_protein_v3_raw_feature_bc_matrix.h5\"\n\n\n--output\nPath where to store output.\nfile, required, example: \"pbmc_1k_protein_v3_raw_feature_bc_matrix.h5\"\n\n\n--verbose\nIncrease verbosity\nboolean_true" + }, + { + "objectID": "components/modules/download/download_file.html#authors", + "href": "components/modules/download/download_file.html#authors", + "title": "Download file", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer)" + }, + { + "objectID": "components/modules/qc/calculate_qc_metrics.html", + "href": "components/modules/qc/calculate_qc_metrics.html", + "title": "Calculate qc metrics", + "section": "", + "text": "ID: calculate_qc_metrics\nNamespace: qc\n\n\n\nSource\nThe metrics are comparable to what scanpy.pp.calculate_qc_metrics output, although they have slightly different names:\nVar metrics (name in this component -> name in scanpy): - pct_dropout -> pct_dropout_by_{expr_type} - num_nonzero_obs -> n_cells_by_{expr_type} - obs_mean -> mean_{expr_type} - total_counts -> total_{expr_type}\nObs metrics: - num_nonzero_vars -> n_genes_by_{expr_type} - pct_{var_qc_metrics]} -> pct_{expr_type}{qc_var} - total_counts{var_qc_metrics} -> total_{expr_type}{qc_var} - pct_of_counts_in_top{top_n_vars}vars -> pct{expr_type}in_top{n}{var_type} - total_counts -> total{expr_type}" + }, + { + "objectID": "components/modules/qc/calculate_qc_metrics.html#example-commands", + "href": "components/modules/qc/calculate_qc_metrics.html#example-commands", + "title": "Calculate qc metrics", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/qc/calculate_qc_metrics/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Inputs\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# layer: \"raw_counts\"\n# var_qc_metrics: [\"ercc\", \"highly_variable\", \"mitochondrial\"]\n# var_qc_metrics_fill_na_value: true\n# top_n_vars: [123]\n\n# Outputs\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/qc/calculate_qc_metrics/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/qc/calculate_qc_metrics.html#argument-groups", + "href": "components/modules/qc/calculate_qc_metrics.html#argument-groups", + "title": "Calculate qc metrics", + "section": "Argument groups", + "text": "Argument groups\n\nInputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--layer\n\nstring, example: \"raw_counts\"\n\n\n--var_qc_metrics\nKeys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled ‘True’, compared to the total sum of the values for all genes.\nstring, example: \"ercc,highly_variable,mitochondrial\"\n\n\n--var_qc_metrics_fill_na_value\nFill any ‘NA’ values found in the columns specified with –var_qc_metrics to ‘True’ or ‘False’. as False.\nboolean\n\n\n--top_n_vars\nNumber of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. --top_n_vars 20,50 finds cumulative proportion to the 20th and 50th most expressed vars.\ninteger\n\n\n\n\n\nOutputs\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/qc/calculate_qc_metrics.html#authors", + "href": "components/modules/qc/calculate_qc_metrics.html#authors", + "title": "Calculate qc metrics", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/modules/qc/fastqc.html", + "href": "components/modules/qc/fastqc.html", + "title": "Fastqc", + "section": "", + "text": "ID: fastqc\nNamespace: qc\n\n\n\nSource\nThis component can take one or more files (by means of shell globbing) or a complete directory" + }, + { + "objectID": "components/modules/qc/fastqc.html#example-commands", + "href": "components/modules/qc/fastqc.html#example-commands", + "title": "Fastqc", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/qc/fastqc/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\nmode: \"files\"\ninput: # please fill in - example: \"fastq_dir/\"\n# output: \"$id.$key.output.output\"\n# threads: 123\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/qc/fastqc/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/qc/fastqc.html#argument-group", + "href": "components/modules/qc/fastqc.html#argument-group", + "title": "Fastqc", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--mode\nThe mode in which the component works. Can be either files or dir.\nstring, default: \"files\"\n\n\n--input\nDirectory containing input fastq files.\nfile, required, example: \"fastq_dir\"\n\n\n--output\nOutput directory to write reports to.\nfile, required, example: \"qc\"\n\n\n--threads\nSpecifies the number of files which can be processed simultaneously. Each thread will be allocated 250MB of memory.\ninteger" + }, + { + "objectID": "components/modules/files/make_params.html", + "href": "components/modules/files/make_params.html", + "title": "Make params", + "section": "", + "text": "ID: make_params\nNamespace: files\n\n\n\nSource" + }, + { + "objectID": "components/modules/files/make_params.html#example-commands", + "href": "components/modules/files/make_params.html#example-commands", + "title": "Make params", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/files/make_params/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\nbase_dir: # please fill in - example: \"/path/to/dir\"\npattern: # please fill in - example: \"*.fastq.gz\"\nn_dirname_drop: 0\nn_basename_id: 0\nid_name: \"id\"\npath_name: \"path\"\n# group_name: \"param_list\"\n# output: \"$id.$key.output.yaml\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/files/make_params/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/files/make_params.html#argument-group", + "href": "components/modules/files/make_params.html#argument-group", + "title": "Make params", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--base_dir\nBase directory to search recursively\nfile, required, example: \"/path/to/dir\"\n\n\n--pattern\nAn optional regular expression. Only file names which match the regular expression will be matched.\nstring, required, example: \"*.fastq.gz\"\n\n\n--n_dirname_drop\nFor every matched file, the parent directory will be traversed N times.\ninteger, default: 0\n\n\n--n_basename_id\nThe unique identifiers will consist of at least N dirnames.\ninteger, default: 0\n\n\n--id_name\nThe name for storing the identifier field in the yaml.\nstring, default: \"id\"\n\n\n--path_name\nThe name for storing the path field in the yaml.\nstring, default: \"path\"\n\n\n--group_name\nTop level name for the group of entries.\nstring, example: \"param_list\"\n\n\n--output\nOutput YAML file.\nfile, required, example: \"params.yaml\"" + }, + { + "objectID": "components/modules/files/make_params.html#authors", + "href": "components/modules/files/make_params.html#authors", + "title": "Make params", + "section": "Authors", + "text": "Authors\n\nAngela Oliveira Pisco (author)\nRobrecht Cannoodt (maintainer, author)" + }, + { + "objectID": "components/modules/demux/bcl2fastq.html", + "href": "components/modules/demux/bcl2fastq.html", + "title": "Bcl2fastq", + "section": "", + "text": "ID: bcl2fastq\nNamespace: demux\n\n\n\nSource" + }, + { + "objectID": "components/modules/demux/bcl2fastq.html#example-commands", + "href": "components/modules/demux/bcl2fastq.html#example-commands", + "title": "Bcl2fastq", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/demux/bcl2fastq/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"bcl_dir\"\nsample_sheet: # please fill in - example: \"SampleSheet.csv\"\n# output: \"$id.$key.output.output\"\n# reports: \"$id.$key.reports.reports\"\nignore_missing: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/demux/bcl2fastq/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/demux/bcl2fastq.html#argument-group", + "href": "components/modules/demux/bcl2fastq.html#argument-group", + "title": "Bcl2fastq", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput run directory\nfile, required, example: \"bcl_dir\"\n\n\n--sample_sheet\nPointer to the sample sheet\nfile, required, example: \"SampleSheet.csv\"\n\n\n--output\nOutput directory containig fastq files\nfile, required, example: \"fastq_dir\"\n\n\n--reports\nReports directory\nfile, example: \"reports_dir\"\n\n\n--ignore_missing\n\nboolean_true" + }, + { + "objectID": "components/modules/demux/bcl2fastq.html#authors", + "href": "components/modules/demux/bcl2fastq.html#authors", + "title": "Bcl2fastq", + "section": "Authors", + "text": "Authors\n\nToni Verbeiren (author, maintainer)" + }, + { + "objectID": "components/modules/transfer/publish.html", + "href": "components/modules/transfer/publish.html", + "title": "Publish", + "section": "", + "text": "ID: publish\nNamespace: transfer\n\n\n\nSource" + }, + { + "objectID": "components/modules/transfer/publish.html#example-commands", + "href": "components/modules/transfer/publish.html#example-commands", + "title": "Publish", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/transfer/publish/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"path/to/file\"\n# output: \"$id.$key.output.output\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/transfer/publish/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/transfer/publish.html#argument-group", + "href": "components/modules/transfer/publish.html#argument-group", + "title": "Publish", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput filename\nfile, required\n\n\n--output\nOutput filename\nfile, required" + }, + { + "objectID": "components/modules/transfer/publish.html#authors", + "href": "components/modules/transfer/publish.html#authors", + "title": "Publish", + "section": "Authors", + "text": "Authors\n\nToni Verbeiren (maintainer)" + }, + { + "objectID": "components/modules/metadata/join_csv.html", + "href": "components/modules/metadata/join_csv.html", + "title": "Join csv", + "section": "", + "text": "ID: join_csv\nNamespace: metadata\n\n\n\nSource" + }, + { + "objectID": "components/modules/metadata/join_csv.html#example-commands", + "href": "components/modules/metadata/join_csv.html#example-commands", + "title": "Join csv", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/metadata/join_csv/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# MuData Input\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# obs_key: \"foo\"\n# var_key: \"foo\"\n\n# MuData Output\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Metadata Input\ninput_csv: # please fill in - example: \"metadata.csv\"\ncsv_key: \"id\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/metadata/join_csv/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/metadata/join_csv.html#argument-groups", + "href": "components/modules/metadata/join_csv.html#argument-groups", + "title": "Join csv", + "section": "Argument groups", + "text": "Argument groups\n\nMuData Input\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--obs_key\nObs column name where the sample id can be found for each observation to join on. Useful when adding metadata to concatenated samples. Mutually exclusive with --var_key.”\nstring\n\n\n--var_key\nVar column name where the sample id can be found for each variable to join on. Mutually exclusive with --obs_key.”\nstring\n\n\n\n\n\nMuData Output\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--output\nOutput h5mu file.\nfile, required, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n\n\n\nMetadata Input\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input_csv\n.csv file containing metadata\nfile, required, example: \"metadata.csv\"\n\n\n--csv_key\ncolumn of the the csv that corresponds to the sample id.\nstring, default: \"id\"" + }, + { + "objectID": "components/modules/metadata/join_csv.html#authors", + "href": "components/modules/metadata/join_csv.html#authors", + "title": "Join csv", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (author)" + }, + { + "objectID": "components/modules/metadata/add_id.html", + "href": "components/modules/metadata/add_id.html", + "title": "Add id", + "section": "", + "text": "ID: add_id\nNamespace: metadata\n\n\n\nSource\nAlso allows to make .obs_names (the .obs index) unique by prefixing the values with an unique id per .h5mu file" + }, + { + "objectID": "components/modules/metadata/add_id.html#example-commands", + "href": "components/modules/metadata/add_id.html#example-commands", + "title": "Add id", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/metadata/add_id/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"sample_path\"\ninput_id: # please fill in - example: \"foo\"\nobs_output: \"sample_id\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nmake_observation_keys_unique: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/metadata/add_id/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/metadata/add_id.html#argument-group", + "href": "components/modules/metadata/add_id.html#argument-group", + "title": "Add id", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to the input .h5mu.\nfile, required, example: \"sample_path\"\n\n\n--input_id\nThe input id.\nstring, required\n\n\n--obs_output\nName of the .obs column where to store the id.\nstring, default: \"sample_id\"\n\n\n--output\n\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--make_observation_keys_unique\nJoin the id to the .obs index (.obs_names).\nboolean_true" + }, + { + "objectID": "components/modules/metadata/add_id.html#authors", + "href": "components/modules/metadata/add_id.html#authors", + "title": "Add id", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/dataflow/split_modalities.html", + "href": "components/modules/dataflow/split_modalities.html", + "title": "Split modalities", + "section": "", + "text": "ID: split_modalities\nNamespace: dataflow\n\n\n\nSource" + }, + { + "objectID": "components/modules/dataflow/split_modalities.html#example-commands", + "href": "components/modules/dataflow/split_modalities.html#example-commands", + "title": "Split modalities", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/dataflow/split_modalities/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"sample_path\"\n# output: \"$id.$key.output.output\"\n# output_compression: \"gzip\"\n# output_types: \"$id.$key.output_types.csv\"\ncompression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/dataflow/split_modalities/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/dataflow/split_modalities.html#argument-group", + "href": "components/modules/dataflow/split_modalities.html#argument-group", + "title": "Split modalities", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPath to a single .h5mu file.\nfile, required, default: \"sample_path\"\n\n\n--output\nOutput directory containing multiple h5mu files.\nfile, required, example: \"/path/to/output\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--output_types\nA csv containing the base filename and modality type per output file.\nfile, required, example: \"types.csv\"\n\n\n--compression\nThe compression format to be used on the final h5mu object.\nstring, default: \"gzip\"" + }, + { + "objectID": "components/modules/dataflow/split_modalities.html#authors", + "href": "components/modules/dataflow/split_modalities.html#authors", + "title": "Split modalities", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)\nRobrecht Cannoodt (contributor)" + }, + { + "objectID": "components/modules/dataflow/merge.html", + "href": "components/modules/dataflow/merge.html", + "title": "Merge", + "section": "", + "text": "ID: merge\nNamespace: dataflow\n\n\n\nSource" + }, + { + "objectID": "components/modules/dataflow/merge.html#example-commands", + "href": "components/modules/dataflow/merge.html#example-commands", + "title": "Merge", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/dataflow/merge/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: [\"sample_paths\"]\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/dataflow/merge/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/dataflow/merge.html#argument-group", + "href": "components/modules/dataflow/merge.html#argument-group", + "title": "Merge", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nPaths to the single-modality .h5mu files that need to be combined\nfile, required, default: \"sample_paths\"\n\n\n--output\nPath to the output file.\nfile, default: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"" + }, + { + "objectID": "components/modules/dataflow/merge.html#authors", + "href": "components/modules/dataflow/merge.html#authors", + "title": "Merge", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/transform/normalize_total.html", + "href": "components/modules/transform/normalize_total.html", + "title": "Normalize total", + "section": "", + "text": "ID: normalize_total\nNamespace: transform\n\n\n\nSource\nNormalize each cell by total counts over all genes, so that every cell has the same total count after normalization. If choosing target_sum=1e6, this is CPM normalization.\nIf exclude_highly_expressed=True, very highly expressed genes are excluded from the computation of the normalization factor (size factor) for each cell. This is meaningful as these can strongly influence the resulting normalized values for all other genes [Weinreb17]." + }, + { + "objectID": "components/modules/transform/normalize_total.html#example-commands", + "href": "components/modules/transform/normalize_total.html#example-commands", + "title": "Normalize total", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/transform/normalize_total/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\n# input_layer: \"foo\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\n# output_layer: \"foo\"\ntarget_sum: 10000\nexclude_highly_expressed: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/transform/normalize_total/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/transform/normalize_total.html#argument-group", + "href": "components/modules/transform/normalize_total.html#argument-group", + "title": "Normalize total", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--input_layer\nInput layer to use. By default, X is normalized\nstring\n\n\n--output\nOutput h5mu file.\nfile, required, default: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--output_layer\nOutput layer to use. By default, use X.\nstring\n\n\n--target_sum\nIf None, after normalization, each observation (cell) has a total count equal to the median of total counts for observations (cells) before normalization.\ninteger, default: 10000\n\n\n--exclude_highly_expressed\nExclude (very) highly expressed genes for the computation of the normalization factor (size factor) for each cell. A gene is considered highly expressed, if it has more than max_fraction of the total counts in at least one cell. The not-excluded genes will sum up to target_sum.\nboolean_true" + }, + { + "objectID": "components/modules/transform/normalize_total.html#authors", + "href": "components/modules/transform/normalize_total.html#authors", + "title": "Normalize total", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)\nRobrecht Cannoodt (contributor)" + }, + { + "objectID": "components/modules/transform/delete_layer.html", + "href": "components/modules/transform/delete_layer.html", + "title": "Delete layer", + "section": "", + "text": "ID: delete_layer\nNamespace: transform\n\n\n\nSource" + }, + { + "objectID": "components/modules/transform/delete_layer.html#example-commands", + "href": "components/modules/transform/delete_layer.html#example-commands", + "title": "Delete layer", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/transform/delete_layer/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\nlayer: # please fill in - example: [\"foo\"]\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nmissing_ok: false\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/transform/delete_layer/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/transform/delete_layer.html#argument-group", + "href": "components/modules/transform/delete_layer.html#argument-group", + "title": "Delete layer", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--layer\nInput layer to remove\nstring, required\n\n\n--output\nOutput h5mu file.\nfile, required, default: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--missing_ok\nDo not raise an error if the layer does not exist for all modalities.\nboolean_true" + }, + { + "objectID": "components/modules/transform/delete_layer.html#authors", + "href": "components/modules/transform/delete_layer.html#authors", + "title": "Delete layer", + "section": "Authors", + "text": "Authors\n\nDries Schaumont (maintainer)" + }, + { + "objectID": "components/modules/transform/regress_out.html", + "href": "components/modules/transform/regress_out.html", + "title": "Regress out", + "section": "", + "text": "ID: regress_out\nNamespace: transform\n\n\n\nSource\nUses simple linear regression. This is inspired by Seurat’s regressOut function in R [Satija15]. Note that this function tends to overcorrect in certain circumstances as described in issue theislab/scanpy#526. See https://github.com/theislab/scanpy/issues/526" + }, + { + "objectID": "components/modules/transform/regress_out.html#example-commands", + "href": "components/modules/transform/regress_out.html#example-commands", + "title": "Regress out", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/transform/regress_out/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nmodality: \"rna\"\n# obs_keys: [\"foo\"]\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/transform/regress_out/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/transform/regress_out.html#argument-group", + "href": "components/modules/transform/regress_out.html#argument-group", + "title": "Regress out", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--output\nOutput h5mu file.\nfile, required, default: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--modality\nWhich modality (one or more) to run this component on.\nstring, default: \"rna\"\n\n\n--obs_keys\nWhich .obs keys to regress on.\nstring" + }, + { + "objectID": "components/modules/transform/regress_out.html#authors", + "href": "components/modules/transform/regress_out.html#authors", + "title": "Regress out", + "section": "Authors", + "text": "Authors\n\nRobrecht Cannoodt (maintainer, contributor)" + }, + { + "objectID": "components/modules/neighbors/find_neighbors.html", + "href": "components/modules/neighbors/find_neighbors.html", + "title": "Find neighbors", + "section": "", + "text": "ID: find_neighbors\nNamespace: neighbors\n\n\n\nSource\nThe neighbor search efficiency of this heavily relies on UMAP [McInnes18], which also provides a method for estimating connectivities of data points - the connectivity of the manifold (method==‘umap’). If method==‘gauss’, connectivities are computed according to [Coifman05], in the adaption of [Haghverdi16]." + }, + { + "objectID": "components/modules/neighbors/find_neighbors.html#example-commands", + "href": "components/modules/neighbors/find_neighbors.html#example-commands", + "title": "Find neighbors", + "section": "Example commands", + "text": "Example commands\nYou can run the pipeline using nextflow run.\n\nView help\nYou can use --help as a parameter to get an overview of the possible parameters.\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -main-script target/nextflow/neighbors/find_neighbors/main.nf \\\n --help\n\n\nRun command\n\n\nExample of params.yaml\n\n# Arguments\ninput: # please fill in - example: \"input.h5mu\"\nmodality: \"rna\"\nobsm_input: \"X_pca\"\n# output: \"$id.$key.output.h5mu\"\n# output_compression: \"gzip\"\nuns_output: \"neighbors\"\nobsp_distances: \"distances\"\nobsp_connectivities: \"connectivities\"\nmetric: \"euclidean\"\nnum_neighbors: 15\nseed: 0\n\n# Nextflow input-output arguments\npublish_dir: # please fill in - example: \"output/\"\n# param_list: \"my_params.yaml\"\n\nnextflow run openpipelines-bio/openpipeline \\\n -r 0.10.0 -latest \\\n -profile docker \\\n -main-script target/nextflow/neighbors/find_neighbors/main.nf \\\n -params-file params.yaml\n\n\n\n\n\n\nNote\n\n\n\nReplace -profile docker with -profile podman or -profile singularity depending on the desired backend." + }, + { + "objectID": "components/modules/neighbors/find_neighbors.html#argument-group", + "href": "components/modules/neighbors/find_neighbors.html#argument-group", + "title": "Find neighbors", + "section": "Argument group", + "text": "Argument group\n\nArguments\n\n\n\n\n\n\n\n\nName\nDescription\nAttributes\n\n\n\n\n--input\nInput h5mu file\nfile, required, example: \"input.h5mu\"\n\n\n--modality\n\nstring, default: \"rna\"\n\n\n--obsm_input\nWhich .obsm slot to use as a starting PCA embedding.\nstring, default: \"X_pca\"\n\n\n--output\nOutput h5mu file containing the found neighbors.\nfile, example: \"output.h5mu\"\n\n\n--output_compression\nThe compression format to be used on the output h5mu object.\nstring, example: \"gzip\"\n\n\n--uns_output\nMandatory .uns slot to store various neighbor output objects.\nstring, default: \"neighbors\"\n\n\n--obsp_distances\nIn which .obsp slot to store the distance matrix between the resulting neighbors.\nstring, default: \"distances\"\n\n\n--obsp_connectivities\nIn which .obsp slot to store the connectivities matrix between the resulting neighbors.\nstring, default: \"connectivities\"\n\n\n--metric\nThe distance metric to be used in the generation of the nearest neighborhood network.\nstring, default: \"euclidean\"\n\n\n--num_neighbors\nThe size of local neighborhood (in terms of number of neighboring data points) used for manifold approximation. Larger values result in more global views of the manifold, while smaller values result in more local data being preserved. In general values should be in the range 2 to 100. If knn is True, number of nearest neighbors to be searched. If knn is False, a Gaussian kernel width is set to the distance of the n_neighbors neighbor.\ninteger, default: 15\n\n\n--seed\nA random seed.\ninteger, default: 0" + }, + { + "objectID": "components/modules/neighbors/find_neighbors.html#authors", + "href": "components/modules/neighbors/find_neighbors.html#authors", + "title": "Find neighbors", + "section": "Authors", + "text": "Authors\n\nDries De Maeyer (maintainer)\nRobrecht Cannoodt (contributor)" + }, + { + "objectID": "contributing/running_tests.html", + "href": "contributing/running_tests.html", + "title": "Running tests", + "section": "", + "text": "Fetching the test data.\nThe input data that is needed to run the tests will need to be downloaded from the openpipelines Amazon AWS s3 bucket first. To do so, the download/sync_test_resource component can be used, which will download the data to the correct location (resources_test) by default.\n./bin/viash run ./src/download/sync_test_resources/config.vsh.yaml -p docker -- --input s3://openpipelines-data\nOr, if you do not want to use Docker and have aws-cli tools installed natively:\n./bin/viash run ./src/download/sync_test_resources/config.vsh.yaml -p native -- --input s3://openpipelines-data\n\n\nRunning component unittests\nTo build and run tests for individual component that you are working on, use viash test with the config.vsh.yaml of the component you would like to test. For example:\n./bin/viash test ./src/convert/from_10xh5_to_h5mu/config.vsh.yaml\nKeep in mind that when no platform is passed to viash test, it will use the first platform that is specified in the config, which is docker for most of the components in openpipelines. Use -p native for example if you do not want to use docker.\nIt is also possible to execute the tests for all components in each namespace using ./bin/viash_test (note the underscore instead of a space).\n./bin/viash_test\n\n\nIntegration tests\nIndividual integration tests can be run by using the integration_test.sh scripts for a pipeline, located next to the main.nf in the workflows folder.\n./workflows/ingestion/cellranger_demux/integration_test.sh\nRunning all integration tests is also possible using a helper script that can be found at workflows/test/integration_test.sh. Using this script requires a working R installation with tidyverse installed. However, as pipelines are implemented by combining individual components\n./workflows/test/integration_test.sh" + }, + { + "objectID": "contributing/getting_started.html", + "href": "contributing/getting_started.html", + "title": "Getting started", + "section": "", + "text": "Forking the code and cloning the repository\nThe openpipelines code is hosted on GitHub. To start working on openpipeline, you should create your own copy of the repository by forking it. Visit the openpipeline repository here and use the ‘Fork’ button on the top right hand side of the page. After you are done forking, you can clone the repository to a local directory on your computer using git clone. You can choose between using an SSH key to log in to GitHub or username and password (HTTPS) to connect to github.\n\nHTTPSSSH\n\n\ngit clone https://github.com/<YOUR USERNAME>/openpipeline.git\ncd openpipeline\ngit remote add upstream https://github.com/openpipeline-bio/openpipeline.git\n\n\ngit clone git@github.com:<YOUR USERNAME>/openpipeline.git\ncd openpipeline\ngit remote add upstream https://github.com/openpipeline-bio/openpipeline.git\n\n\n\n\n\nInstalling viash and nextflow\nOpenpipelines is being developed in Viash and Nextflow. If you are unfamiliar with either one of these platforms, you can check out their respective documentations here and here. To start contributing to openpipelines, you will need at least a working version of Java 11, OpenJDK 11, or a later version (up to Java 18). Additionally, by using Docker,you can build and test pipeline components and pipelines without needing to manually install dependencies for these components on your machine.\nViash and Nextflow can be installed by following the guides in the documentation for both of these tools. Make sure the viash and nextflow binaries are located in an existing directory that is listed in your $PATH. You can check if everything worked by running the following two commands and see if they output the correct location of the executables.\nwhich viash\nwhich nextflow" + }, + { + "objectID": "contributing/pull_requests.html", + "href": "contributing/pull_requests.html", + "title": "Publishing your changes", + "section": "", + "text": "While creating changes on your local branch, another developper could have added new changes the openpipeline repository. These changes will need to be included into your local branch before a pull request can be merged. Updating your branch involves merging the upstream branch (usually main) into your branch:\n# download the changes from the openpipelines repo\ngit fetch upstream\n# change your current branch to the branch of the pull request\ngit checkout <feature_branch>\n# merge the changes from upstream into your branch\ngit merge upstream/main\n# push the updates, your pull request will also be updated\ngit push" + }, + { + "objectID": "contributing/pull_requests.html#updating-your-pull-request-or-branch", + "href": "contributing/pull_requests.html#updating-your-pull-request-or-branch", + "title": "Publishing your changes", + "section": "", + "text": "While creating changes on your local branch, another developper could have added new changes the openpipeline repository. These changes will need to be included into your local branch before a pull request can be merged. Updating your branch involves merging the upstream branch (usually main) into your branch:\n# download the changes from the openpipelines repo\ngit fetch upstream\n# change your current branch to the branch of the pull request\ngit checkout <feature_branch>\n# merge the changes from upstream into your branch\ngit merge upstream/main\n# push the updates, your pull request will also be updated\ngit push" + }, + { + "objectID": "contributing/project_structure.html", + "href": "contributing/project_structure.html", + "title": "Project structure", + "section": "", + "text": "The root of the repository contains three main folders:\n\nsrc, which contains the source code for individual components.\nThe workflows folder containing the implementations of the pipelines (combining one or more components).\n(optionally) the target folder\n\nEach subfolder from src contains a Viash namespace, a logical grouping of pipeline components that perform a similar function. Within each namespace, subfolders designate individual pipeline components. For example ./src/convert/from_bdrhap_to_h5ad contains the implementation for a component from_bdrhap_to_h5ad which is grouped together with other components such as from_10xmtx_to_h5mu into a namespace convert. In a similar manner as grouping components into namespaces, pipelines are grouped together into folders. However, these are not component namespaces and as such do not interact with viash ns commands.\nAs will become apparent later on, Viash not only provides commands to perform operations on individual components, but also on groups of components in a namespace and all components in a project. As a rule of thumb, the basic Viash commands (like ./bin/viash test) are designated for running commands on individual components, while ns commands are (./bin/viash ns test) are for namespaces. When cloning a fresh repository, there will be no target folder present. This is because the target folder will only be created after components have been build." + }, + { + "objectID": "contributing/project_structure.html#sec-project-structure", + "href": "contributing/project_structure.html#sec-project-structure", + "title": "Project structure", + "section": "", + "text": "The root of the repository contains three main folders:\n\nsrc, which contains the source code for individual components.\nThe workflows folder containing the implementations of the pipelines (combining one or more components).\n(optionally) the target folder\n\nEach subfolder from src contains a Viash namespace, a logical grouping of pipeline components that perform a similar function. Within each namespace, subfolders designate individual pipeline components. For example ./src/convert/from_bdrhap_to_h5ad contains the implementation for a component from_bdrhap_to_h5ad which is grouped together with other components such as from_10xmtx_to_h5mu into a namespace convert. In a similar manner as grouping components into namespaces, pipelines are grouped together into folders. However, these are not component namespaces and as such do not interact with viash ns commands.\nAs will become apparent later on, Viash not only provides commands to perform operations on individual components, but also on groups of components in a namespace and all components in a project. As a rule of thumb, the basic Viash commands (like ./bin/viash test) are designated for running commands on individual components, while ns commands are (./bin/viash ns test) are for namespaces. When cloning a fresh repository, there will be no target folder present. This is because the target folder will only be created after components have been build." + }, + { + "objectID": "contributing/project_structure.html#sec-versioning", + "href": "contributing/project_structure.html#sec-versioning", + "title": "Project structure", + "section": "Versioning and branching strategy", + "text": "Versioning and branching strategy\nOpenPipeline tries to use of semantic versioning to govern changes between versions. An release of openpipelines uses a version number in the format MAJOR.MINOR.PATCH. Currenly, openpipelines is still at major version 0.x.y, meaning that public-facing breaking changes are possible on MINOR releases. These breaking changes will be documented in a dedicated section of the CHANGELOG that is published with each release. A PATCH release (i.e. a release where the MAJOR and MINOR version number stay the same), is used to resolve bugs with the pipeline but should not introduce breaking changes. Keep in mind that patches might introduce behavioral changes that may look breaking but are actually rectifying changes that were inadvertently introduced previously (and were in fact also ‘breaking changes’). In this case, a bug can also be released without changing the MINOR version, in a PATH release.\nBetween releases, development progress is tracked on Git branches. A git branch represents a snapshot of a codebase in time, to which changes can be added (i.e. committed). Eventually, all new feature or bugfixes must be reconsiled into a single branch so that a new release can be created. This process is called merging and the process of requesting the merging of two branches is called a pull request. Openpipelines follows the convention that the target branch for all pull requests is the main branch. Thus, the main branch contains the latest changes for the code and it can be considered the development branch.\nOnce a pull request has been approved and merged, Github Actions CI will automatically build all components (creating the target directory) and push the result to the main_build branch. In essence, the main_build branch is a copy of the main branch, but also containing the build components. Once it is time to create a openpipelines release, the Github CI release workflow is manually triggered, the components on the main branch will be build and tested. Then, the result will be pushed to the release branch and the integration tests will be run. If all tests succeeded, a new github tag and release can be created manually from the release branch.\n\n\n\n\n%%{init: { 'logLevel': 'debug', 'theme': 'default'} } }%%\ngitGraph\n commit id: \"initial commit\"\n branch main_build\n commit id: \"CI build\"\n checkout main\n commit\n checkout main_build\n merge main\n checkout main\n branch feature_a\n branch feature_b\n checkout feature_a\n commit\n commit\n checkout main\n commit id: \"#release 0.1\" type: HIGHLIGHT\n checkout main_build\n merge main\n checkout main\n branch release\n commit tag: \"0.1\"\n checkout main\n commit\n checkout feature_b\n commit\n commit\n checkout feature_a\n commit\n checkout main\n merge feature_a\n checkout main_build\n merge main\n checkout main\n checkout feature_b\n commit\n checkout main\n merge feature_b\n checkout main_build\n merge main\n checkout release\n merge main tag: \"0.2\"" + }, + { + "objectID": "team/index.html", + "href": "team/index.html", + "title": "Team", + "section": "", + "text": "Angela Oliveira Pisco\n Contributor\n \n \n \n \n \n \n \n \n \n \n \n Director of Computational Biology \n at \n \n Insitro\n \n \n \n \n \n Core Member \n at \n \n Open Problems\n \n \n \n \n \n \n \n \n Dries De Maeyer\n Core Team Member\n \n \n \n \n \n \n \n \n \n \n \n Principal Scientist \n at \n \n Janssen Pharmaceuticals\n \n \n \n \n \n \n \n \n Dries Schaumont\n Core Team Member\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Data Scientist \n at \n \n Data Intuitive\n \n \n \n \n \n \n \n \n Malte D. Luecken\n Core Team Member\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Group Leader \n at \n \n Helmholtz Munich\n \n \n \n \n \n Core Member \n at \n \n Open Problems\n \n \n \n \n \n \n \n \n Marijke Van Moerbeke\n Contributor\n \n \n \n \n \n \n \n \n Statistical Consultant \n at \n \n OpenAnalytics\n \n \n \n \n \n \n \n \n Matthias Beyens\n Contributor\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Principal Scientist \n at \n \n Janssen Pharmaceuticals\n \n \n \n \n \n \n \n \n Mauro Saporita\n Contributor\n \n \n \n \n \n \n \n \n \n \n \n Lead Nextflow Developer \n at \n \n Ardigen\n \n \n \n \n \n \n \n \n Povilas Gibas\n Contributor\n \n \n \n \n \n \n \n \n \n \n \n Bioinformatician \n at \n \n Ardigen\n \n \n \n \n \n \n \n \n Robrecht Cannoodt\n Core Team Member\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Data Science Engineer \n at \n \n Data Intuitive\n \n \n \n \n \n Core Member \n at \n \n Open Problems\n \n \n \n \n \n \n \n \n Samuel D'Souza\n Contributor\n \n \n \n \n \n \n \n \n Data Engineer \n at \n \n Chan Zuckerberg Biohub\n \n \n \n \n \n \n \n \n Toni Verbeiren\n Core Team Member\n \n \n \n \n \n \n \n \n Data Scientist and CEO \n at \n \n Data Intuitive\n \n \n \n \n \n \n \n \n Vladimir Shitov\n Contributor\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n PhD Candidate \n at \n \n Helmholtz Munich\n \n \n \n \n \n\n\nNo matching items" + } +] \ No newline at end of file diff --git a/pr-preview/pr-51/site_libs/bootstrap/bootstrap-icons.css b/pr-preview/pr-51/site_libs/bootstrap/bootstrap-icons.css new file mode 100644 index 00000000..c3bfba65 --- /dev/null +++ b/pr-preview/pr-51/site_libs/bootstrap/bootstrap-icons.css @@ -0,0 +1,1981 @@ +/*! + * Bootstrap Icons v1.10.5 (https://icons.getbootstrap.com/) + * Copyright 2019-2023 The Bootstrap Authors + * Licensed under MIT (https://github.com/twbs/icons/blob/main/LICENSE) + */ + +@font-face { + font-display: block; + font-family: "bootstrap-icons"; + src: 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Be={placement:"bottom",modifiers:[],strategy:"absolute"};function Re(){for(var t=arguments.length,e=new Array(t),i=0;ij.on(t,"mouseover",d))),this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Je),this._element.classList.add(Je),j.trigger(this._element,"shown.bs.dropdown",t)}hide(){if(c(this._element)||!this._isShown(this._menu))return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){j.trigger(this._element,"hide.bs.dropdown",t).defaultPrevented||("ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._popper&&this._popper.destroy(),this._menu.classList.remove(Je),this._element.classList.remove(Je),this._element.setAttribute("aria-expanded","false"),U.removeDataAttribute(this._menu,"popper"),j.trigger(this._element,"hidden.bs.dropdown",t))}_getConfig(t){if(t={...this.constructor.Default,...U.getDataAttributes(this._element),...t},a(Ue,t,this.constructor.DefaultType),"object"==typeof t.reference&&!o(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${Ue.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(t){if(void 0===Fe)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let e=this._element;"parent"===this._config.reference?e=t:o(this._config.reference)?e=r(this._config.reference):"object"==typeof this._config.reference&&(e=this._config.reference);const i=this._getPopperConfig(),n=i.modifiers.find((t=>"applyStyles"===t.name&&!1===t.enabled));this._popper=qe(e,this._menu,i),n&&U.setDataAttribute(this._menu,"popper","static")}_isShown(t=this._element){return t.classList.contains(Je)}_getMenuElement(){return V.next(this._element,ei)[0]}_getPlacement(){const t=this._element.parentNode;if(t.classList.contains("dropend"))return ri;if(t.classList.contains("dropstart"))return ai;const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ni:ii:e?oi:si}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return"static"===this._config.display&&(t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,..."function"==typeof this._config.popperConfig?this._config.popperConfig(t):this._config.popperConfig}}_selectMenuItem({key:t,target:e}){const i=V.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter(l);i.length&&v(i,e,t===Ye,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(t&&(2===t.button||"keyup"===t.type&&"Tab"!==t.key))return;const e=V.find(ti);for(let i=0,n=e.length;ie+t)),this._setElementAttributes(di,"paddingRight",(e=>e+t)),this._setElementAttributes(ui,"marginRight",(e=>e-t))}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t)[e];t.style[e]=`${i(Number.parseFloat(s))}px`}))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,"paddingRight"),this._resetElementAttributes(di,"paddingRight"),this._resetElementAttributes(ui,"marginRight")}_saveInitialAttribute(t,e){const i=t.style[e];i&&U.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=U.getDataAttribute(t,e);void 0===i?t.style.removeProperty(e):(U.removeDataAttribute(t,e),t.style[e]=i)}))}_applyManipulationCallback(t,e){o(t)?e(t):V.find(t,this._element).forEach(e)}isOverflowing(){return this.getWidth()>0}}const pi={className:"modal-backdrop",isVisible:!0,isAnimated:!1,rootElement:"body",clickCallback:null},mi={className:"string",isVisible:"boolean",isAnimated:"boolean",rootElement:"(element|string)",clickCallback:"(function|null)"},gi="show",_i="mousedown.bs.backdrop";class bi{constructor(t){this._config=this._getConfig(t),this._isAppended=!1,this._element=null}show(t){this._config.isVisible?(this._append(),this._config.isAnimated&&u(this._getElement()),this._getElement().classList.add(gi),this._emulateAnimation((()=>{_(t)}))):_(t)}hide(t){this._config.isVisible?(this._getElement().classList.remove(gi),this._emulateAnimation((()=>{this.dispose(),_(t)}))):_(t)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_getConfig(t){return(t={...pi,..."object"==typeof t?t:{}}).rootElement=r(t.rootElement),a("backdrop",t,mi),t}_append(){this._isAppended||(this._config.rootElement.append(this._getElement()),j.on(this._getElement(),_i,(()=>{_(this._config.clickCallback)})),this._isAppended=!0)}dispose(){this._isAppended&&(j.off(this._element,_i),this._element.remove(),this._isAppended=!1)}_emulateAnimation(t){b(t,this._getElement(),this._config.isAnimated)}}const vi={trapElement:null,autofocus:!0},yi={trapElement:"element",autofocus:"boolean"},wi=".bs.focustrap",Ei="backward";class Ai{constructor(t){this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}activate(){const{trapElement:t,autofocus:e}=this._config;this._isActive||(e&&t.focus(),j.off(document,wi),j.on(document,"focusin.bs.focustrap",(t=>this._handleFocusin(t))),j.on(document,"keydown.tab.bs.focustrap",(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,j.off(document,wi))}_handleFocusin(t){const{target:e}=t,{trapElement:i}=this._config;if(e===document||e===i||i.contains(e))return;const n=V.focusableChildren(i);0===n.length?i.focus():this._lastTabNavDirection===Ei?n[n.length-1].focus():n[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?Ei:"forward")}_getConfig(t){return t={...vi,..."object"==typeof t?t:{}},a("focustrap",t,yi),t}}const Ti="modal",Oi="Escape",Ci={backdrop:!0,keyboard:!0,focus:!0},ki={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean"},Li="hidden.bs.modal",xi="show.bs.modal",Di="resize.bs.modal",Si="click.dismiss.bs.modal",Ni="keydown.dismiss.bs.modal",Ii="mousedown.dismiss.bs.modal",Pi="modal-open",ji="show",Mi="modal-static";class Hi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._dialog=V.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._ignoreBackdropClick=!1,this._isTransitioning=!1,this._scrollBar=new fi}static get Default(){return Ci}static get NAME(){return Ti}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||j.trigger(this._element,xi,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isAnimated()&&(this._isTransitioning=!0),this._scrollBar.hide(),document.body.classList.add(Pi),this._adjustDialog(),this._setEscapeEvent(),this._setResizeEvent(),j.on(this._dialog,Ii,(()=>{j.one(this._element,"mouseup.dismiss.bs.modal",(t=>{t.target===this._element&&(this._ignoreBackdropClick=!0)}))})),this._showBackdrop((()=>this._showElement(t))))}hide(){if(!this._isShown||this._isTransitioning)return;if(j.trigger(this._element,"hide.bs.modal").defaultPrevented)return;this._isShown=!1;const t=this._isAnimated();t&&(this._isTransitioning=!0),this._setEscapeEvent(),this._setResizeEvent(),this._focustrap.deactivate(),this._element.classList.remove(ji),j.off(this._element,Si),j.off(this._dialog,Ii),this._queueCallback((()=>this._hideModal()),this._element,t)}dispose(){[window,this._dialog].forEach((t=>j.off(t,".bs.modal"))),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new bi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_getConfig(t){return t={...Ci,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Ti,t,ki),t}_showElement(t){const e=this._isAnimated(),i=V.findOne(".modal-body",this._dialog);this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0,i&&(i.scrollTop=0),e&&u(this._element),this._element.classList.add(ji),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,j.trigger(this._element,"shown.bs.modal",{relatedTarget:t})}),this._dialog,e)}_setEscapeEvent(){this._isShown?j.on(this._element,Ni,(t=>{this._config.keyboard&&t.key===Oi?(t.preventDefault(),this.hide()):this._config.keyboard||t.key!==Oi||this._triggerBackdropTransition()})):j.off(this._element,Ni)}_setResizeEvent(){this._isShown?j.on(window,Di,(()=>this._adjustDialog())):j.off(window,Di)}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Pi),this._resetAdjustments(),this._scrollBar.reset(),j.trigger(this._element,Li)}))}_showBackdrop(t){j.on(this._element,Si,(t=>{this._ignoreBackdropClick?this._ignoreBackdropClick=!1:t.target===t.currentTarget&&(!0===this._config.backdrop?this.hide():"static"===this._config.backdrop&&this._triggerBackdropTransition())})),this._backdrop.show(t)}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(j.trigger(this._element,"hidePrevented.bs.modal").defaultPrevented)return;const{classList:t,scrollHeight:e,style:i}=this._element,n=e>document.documentElement.clientHeight;!n&&"hidden"===i.overflowY||t.contains(Mi)||(n||(i.overflowY="hidden"),t.add(Mi),this._queueCallback((()=>{t.remove(Mi),n||this._queueCallback((()=>{i.overflowY=""}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;(!i&&t&&!m()||i&&!t&&m())&&(this._element.style.paddingLeft=`${e}px`),(i&&!t&&!m()||!i&&t&&m())&&(this._element.style.paddingRight=`${e}px`)}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}j.on(document,"click.bs.modal.data-api",'[data-bs-toggle="modal"]',(function(t){const e=n(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),j.one(e,xi,(t=>{t.defaultPrevented||j.one(e,Li,(()=>{l(this)&&this.focus()}))}));const i=V.findOne(".modal.show");i&&Hi.getInstance(i).hide(),Hi.getOrCreateInstance(e).toggle(this)})),R(Hi),g(Hi);const Bi="offcanvas",Ri={backdrop:!0,keyboard:!0,scroll:!1},Wi={backdrop:"boolean",keyboard:"boolean",scroll:"boolean"},$i="show",zi=".offcanvas.show",qi="hidden.bs.offcanvas";class Fi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get NAME(){return Bi}static get Default(){return Ri}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||j.trigger(this._element,"show.bs.offcanvas",{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._element.style.visibility="visible",this._backdrop.show(),this._config.scroll||(new fi).hide(),this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($i),this._queueCallback((()=>{this._config.scroll||this._focustrap.activate(),j.trigger(this._element,"shown.bs.offcanvas",{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(j.trigger(this._element,"hide.bs.offcanvas").defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.remove($i),this._backdrop.hide(),this._queueCallback((()=>{this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._element.style.visibility="hidden",this._config.scroll||(new fi).reset(),j.trigger(this._element,qi)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_getConfig(t){return t={...Ri,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Bi,t,Wi),t}_initializeBackDrop(){return new bi({className:"offcanvas-backdrop",isVisible:this._config.backdrop,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:()=>this.hide()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_addEventListeners(){j.on(this._element,"keydown.dismiss.bs.offcanvas",(t=>{this._config.keyboard&&"Escape"===t.key&&this.hide()}))}static jQueryInterface(t){return this.each((function(){const e=Fi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}j.on(document,"click.bs.offcanvas.data-api",'[data-bs-toggle="offcanvas"]',(function(t){const e=n(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this))return;j.one(e,qi,(()=>{l(this)&&this.focus()}));const i=V.findOne(zi);i&&i!==e&&Fi.getInstance(i).hide(),Fi.getOrCreateInstance(e).toggle(this)})),j.on(window,"load.bs.offcanvas.data-api",(()=>V.find(zi).forEach((t=>Fi.getOrCreateInstance(t).show())))),R(Fi),g(Fi);const Ui=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Vi=/^(?:(?:https?|mailto|ftp|tel|file|sms):|[^#&/:?]*(?:[#/?]|$))/i,Ki=/^data:(?:image\/(?:bmp|gif|jpeg|jpg|png|tiff|webp)|video\/(?:mpeg|mp4|ogg|webm)|audio\/(?:mp3|oga|ogg|opus));base64,[\d+/a-z]+=*$/i,Xi=(t,e)=>{const i=t.nodeName.toLowerCase();if(e.includes(i))return!Ui.has(i)||Boolean(Vi.test(t.nodeValue)||Ki.test(t.nodeValue));const n=e.filter((t=>t instanceof RegExp));for(let t=0,e=n.length;t{Xi(t,r)||i.removeAttribute(t.nodeName)}))}return n.body.innerHTML}const Qi="tooltip",Gi=new Set(["sanitize","allowList","sanitizeFn"]),Zi={animation:"boolean",template:"string",title:"(string|element|function)",trigger:"string",delay:"(number|object)",html:"boolean",selector:"(string|boolean)",placement:"(string|function)",offset:"(array|string|function)",container:"(string|element|boolean)",fallbackPlacements:"array",boundary:"(string|element)",customClass:"(string|function)",sanitize:"boolean",sanitizeFn:"(null|function)",allowList:"object",popperConfig:"(null|object|function)"},Ji={AUTO:"auto",TOP:"top",RIGHT:m()?"left":"right",BOTTOM:"bottom",LEFT:m()?"right":"left"},tn={animation:!0,template:'

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t=this.getTipElement();if(j.trigger(this._element,this.constructor.Event.HIDE).defaultPrevented)return;t.classList.remove(sn),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._activeTrigger.click=!1,this._activeTrigger.focus=!1,this._activeTrigger.hover=!1;const e=this.tip.classList.contains(nn);this._queueCallback((()=>{this._isWithActiveTrigger()||(this._hoverState!==on&&t.remove(),this._cleanTipClass(),this._element.removeAttribute("aria-describedby"),j.trigger(this._element,this.constructor.Event.HIDDEN),this._disposePopper())}),this.tip,e),this._hoverState=""}update(){null!==this._popper&&this._popper.update()}isWithContent(){return Boolean(this.getTitle())}getTipElement(){if(this.tip)return this.tip;const t=document.createElement("div");t.innerHTML=this._config.template;const e=t.children[0];return this.setContent(e),e.classList.remove(nn,sn),this.tip=e,this.tip}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),an)}_sanitizeAndSetContent(t,e,i){const n=V.findOne(i,t);e||!n?this.setElementContent(n,e):n.remove()}setElementContent(t,e){if(null!==t)return o(e)?(e=r(e),void(this._config.html?e.parentNode!==t&&(t.innerHTML="",t.append(e)):t.textContent=e.textContent)):void(this._config.html?(this._config.sanitize&&(e=Yi(e,this._config.allowList,this._config.sanitizeFn)),t.innerHTML=e):t.textContent=e)}getTitle(){const t=this._element.getAttribute("data-bs-original-title")||this._config.title;return this._resolvePossibleFunction(t)}updateAttachment(t){return"right"===t?"end":"left"===t?"start":t}_initializeOnDelegatedTarget(t,e){return e||this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof 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t in this._activeTrigger)if(this._activeTrigger[t])return!0;return!1}_getConfig(t){const e=U.getDataAttributes(this._element);return Object.keys(e).forEach((t=>{Gi.has(t)&&delete e[t]})),(t={...this.constructor.Default,...e,..."object"==typeof t&&t?t:{}}).container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),a(Qi,t,this.constructor.DefaultType),t.sanitize&&(t.template=Yi(t.template,t.allowList,t.sanitizeFn)),t}_getDelegateConfig(){const t={};for(const e in this._config)this.constructor.Default[e]!==this._config[e]&&(t[e]=this._config[e]);return t}_cleanTipClass(){const t=this.getTipElement(),e=new RegExp(`(^|\\s)${this._getBasicClassPrefix()}\\S+`,"g"),i=t.getAttribute("class").match(e);null!==i&&i.length>0&&i.map((t=>t.trim())).forEach((e=>t.classList.remove(e)))}_getBasicClassPrefix(){return"bs-tooltip"}_handlePopperPlacementChange(t){const{state:e}=t;e&&(this.tip=e.elements.popper,this._cleanTipClass(),this._addAttachmentClass(this._getAttachment(e.placement)))}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null)}static jQueryInterface(t){return this.each((function(){const e=un.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(un);const fn={...un.Default,placement:"right",offset:[0,8],trigger:"click",content:"",template:''},pn={...un.DefaultType,content:"(string|element|function)"},mn={HIDE:"hide.bs.popover",HIDDEN:"hidden.bs.popover",SHOW:"show.bs.popover",SHOWN:"shown.bs.popover",INSERTED:"inserted.bs.popover",CLICK:"click.bs.popover",FOCUSIN:"focusin.bs.popover",FOCUSOUT:"focusout.bs.popover",MOUSEENTER:"mouseenter.bs.popover",MOUSELEAVE:"mouseleave.bs.popover"};class gn extends un{static get Default(){return fn}static get NAME(){return"popover"}static get Event(){return mn}static get DefaultType(){return pn}isWithContent(){return this.getTitle()||this._getContent()}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),".popover-header"),this._sanitizeAndSetContent(t,this._getContent(),".popover-body")}_getContent(){return this._resolvePossibleFunction(this._config.content)}_getBasicClassPrefix(){return"bs-popover"}static jQueryInterface(t){return this.each((function(){const 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e=n(this._element),i=this._element.closest(".nav, .list-group");if(i){const e="UL"===i.nodeName||"OL"===i.nodeName?Ln:kn;t=V.find(e,i),t=t[t.length-1]}const s=t?j.trigger(t,"hide.bs.tab",{relatedTarget:this._element}):null;if(j.trigger(this._element,"show.bs.tab",{relatedTarget:t}).defaultPrevented||null!==s&&s.defaultPrevented)return;this._activate(this._element,i);const o=()=>{j.trigger(t,"hidden.bs.tab",{relatedTarget:this._element}),j.trigger(this._element,"shown.bs.tab",{relatedTarget:t})};e?this._activate(e,e.parentNode,o):o()}_activate(t,e,i){const n=(!e||"UL"!==e.nodeName&&"OL"!==e.nodeName?V.children(e,kn):V.find(Ln,e))[0],s=i&&n&&n.classList.contains(On),o=()=>this._transitionComplete(t,n,i);n&&s?(n.classList.remove(Cn),this._queueCallback(o,t,!0)):o()}_transitionComplete(t,e,i){if(e){e.classList.remove(Tn);const t=V.findOne(":scope > .dropdown-menu 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Copyright 2022 Fonticons, Inc. + */ +.fa { + font-family: var(--fa-style-family, "Font Awesome 6 Free"); + font-weight: var(--fa-style, 900); } + +.fa, +.fas, +.fa-solid, +.far, +.fa-regular, +.fal, +.fa-light, +.fat, +.fa-thin, +.fad, +.fa-duotone, +.fab, +.fa-brands { + -moz-osx-font-smoothing: grayscale; + -webkit-font-smoothing: antialiased; + display: var(--fa-display, inline-block); + font-style: normal; + font-variant: normal; + line-height: 1; + text-rendering: auto; } + +.fa-1x { + font-size: 1em; } + +.fa-2x { + font-size: 2em; } + +.fa-3x { + font-size: 3em; } + +.fa-4x { + font-size: 4em; } + +.fa-5x { + font-size: 5em; } + +.fa-6x { + font-size: 6em; } + +.fa-7x { + font-size: 7em; } + +.fa-8x { + font-size: 8em; } + +.fa-9x { + font-size: 9em; } + +.fa-10x { + font-size: 10em; } + +.fa-2xs { + font-size: 0.625em; + line-height: 0.1em; + vertical-align: 0.225em; } + +.fa-xs { + font-size: 0.75em; + line-height: 0.08333em; + vertical-align: 0.125em; } + +.fa-sm { + font-size: 0.875em; + line-height: 0.07143em; + vertical-align: 0.05357em; } + +.fa-lg { + font-size: 1.25em; + line-height: 0.05em; + vertical-align: -0.075em; } + +.fa-xl { + font-size: 1.5em; + line-height: 0.04167em; + vertical-align: -0.125em; } + +.fa-2xl { + font-size: 2em; + line-height: 0.03125em; + vertical-align: -0.1875em; } + +.fa-fw { + text-align: center; + width: 1.25em; } + +.fa-ul { + list-style-type: none; + margin-left: var(--fa-li-margin, 2.5em); + padding-left: 0; } + .fa-ul > li { + position: relative; } + +.fa-li { + left: calc(var(--fa-li-width, 2em) * -1); + position: absolute; + text-align: center; + width: var(--fa-li-width, 2em); + line-height: inherit; } + +.fa-border { + border-color: var(--fa-border-color, #eee); + border-radius: var(--fa-border-radius, 0.1em); + border-style: var(--fa-border-style, solid); + border-width: var(--fa-border-width, 0.08em); + padding: var(--fa-border-padding, 0.2em 0.25em 0.15em); } + +.fa-pull-left { + float: left; + margin-right: var(--fa-pull-margin, 0.3em); } + +.fa-pull-right { + float: right; + margin-left: var(--fa-pull-margin, 0.3em); } + +.fa-beat { + -webkit-animation-name: fa-beat; + animation-name: fa-beat; + -webkit-animation-delay: var(--fa-animation-delay, 0); + animation-delay: var(--fa-animation-delay, 0); + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 1s); + animation-duration: var(--fa-animation-duration, 1s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out); + animation-timing-function: var(--fa-animation-timing, ease-in-out); } + +.fa-bounce { + -webkit-animation-name: fa-bounce; + animation-name: fa-bounce; + -webkit-animation-delay: var(--fa-animation-delay, 0); + animation-delay: var(--fa-animation-delay, 0); + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 1s); + animation-duration: var(--fa-animation-duration, 1s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); + animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); } + +.fa-fade { + -webkit-animation-name: fa-fade; + animation-name: fa-fade; + -webkit-animation-delay: var(--fa-animation-delay, 0); + animation-delay: var(--fa-animation-delay, 0); + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 1s); + animation-duration: var(--fa-animation-duration, 1s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); + animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); } + +.fa-beat-fade { + -webkit-animation-name: fa-beat-fade; + animation-name: fa-beat-fade; + -webkit-animation-delay: var(--fa-animation-delay, 0); + animation-delay: var(--fa-animation-delay, 0); + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 1s); + animation-duration: var(--fa-animation-duration, 1s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); + animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); } + +.fa-flip { + -webkit-animation-name: fa-flip; + animation-name: fa-flip; + -webkit-animation-delay: var(--fa-animation-delay, 0); + animation-delay: var(--fa-animation-delay, 0); + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 1s); + animation-duration: var(--fa-animation-duration, 1s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out); + animation-timing-function: var(--fa-animation-timing, ease-in-out); } + +.fa-shake { + -webkit-animation-name: fa-shake; + animation-name: fa-shake; + -webkit-animation-delay: var(--fa-animation-delay, 0); + animation-delay: var(--fa-animation-delay, 0); + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 1s); + animation-duration: var(--fa-animation-duration, 1s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, linear); + animation-timing-function: var(--fa-animation-timing, linear); } + +.fa-spin { + -webkit-animation-name: fa-spin; + animation-name: fa-spin; + -webkit-animation-delay: var(--fa-animation-delay, 0); + animation-delay: var(--fa-animation-delay, 0); + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 2s); + animation-duration: var(--fa-animation-duration, 2s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, linear); + animation-timing-function: var(--fa-animation-timing, linear); } + +.fa-spin-reverse { + --fa-animation-direction: reverse; } + +.fa-pulse, +.fa-spin-pulse { + -webkit-animation-name: fa-spin; + animation-name: fa-spin; + -webkit-animation-direction: var(--fa-animation-direction, normal); + animation-direction: var(--fa-animation-direction, normal); + -webkit-animation-duration: var(--fa-animation-duration, 1s); + animation-duration: var(--fa-animation-duration, 1s); + -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); + animation-iteration-count: var(--fa-animation-iteration-count, infinite); + -webkit-animation-timing-function: var(--fa-animation-timing, steps(8)); + animation-timing-function: var(--fa-animation-timing, steps(8)); } + +@media (prefers-reduced-motion: reduce) { + .fa-beat, + .fa-bounce, + .fa-fade, + .fa-beat-fade, + .fa-flip, + .fa-pulse, + .fa-shake, + .fa-spin, + .fa-spin-pulse { + -webkit-animation-delay: -1ms; + animation-delay: -1ms; + -webkit-animation-duration: 1ms; + animation-duration: 1ms; + -webkit-animation-iteration-count: 1; + animation-iteration-count: 1; + transition-delay: 0s; + transition-duration: 0s; } } + +@-webkit-keyframes fa-beat { + 0%, 90% { + -webkit-transform: scale(1); + transform: scale(1); } + 45% { + -webkit-transform: scale(var(--fa-beat-scale, 1.25)); + transform: scale(var(--fa-beat-scale, 1.25)); } } + +@keyframes fa-beat { + 0%, 90% { + -webkit-transform: scale(1); + transform: scale(1); } + 45% { + -webkit-transform: scale(var(--fa-beat-scale, 1.25)); + transform: scale(var(--fa-beat-scale, 1.25)); } } + +@-webkit-keyframes fa-bounce { + 0% { + -webkit-transform: scale(1, 1) translateY(0); + transform: scale(1, 1) translateY(0); } + 10% { + -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); + transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); } + 30% { + -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); + transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); } + 50% { + -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); + transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); } + 57% { + -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); + transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); } + 64% { + -webkit-transform: scale(1, 1) translateY(0); + transform: scale(1, 1) translateY(0); } + 100% { + -webkit-transform: scale(1, 1) translateY(0); + transform: scale(1, 1) translateY(0); } } + +@keyframes fa-bounce { + 0% { + -webkit-transform: scale(1, 1) translateY(0); + transform: scale(1, 1) translateY(0); } + 10% { + -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); + transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); } + 30% { + -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); + transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); } + 50% { + -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); + transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); } + 57% { + -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); + transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); } + 64% { + -webkit-transform: scale(1, 1) translateY(0); + transform: scale(1, 1) translateY(0); } + 100% { + -webkit-transform: scale(1, 1) translateY(0); + transform: scale(1, 1) translateY(0); } } + +@-webkit-keyframes fa-fade { + 50% { + opacity: var(--fa-fade-opacity, 0.4); } } + +@keyframes fa-fade { + 50% { + opacity: var(--fa-fade-opacity, 0.4); } } + +@-webkit-keyframes fa-beat-fade { + 0%, 100% { + opacity: var(--fa-beat-fade-opacity, 0.4); + -webkit-transform: scale(1); + transform: scale(1); } + 50% { + opacity: 1; + -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125)); + transform: scale(var(--fa-beat-fade-scale, 1.125)); } } + +@keyframes fa-beat-fade { + 0%, 100% { + opacity: var(--fa-beat-fade-opacity, 0.4); + -webkit-transform: scale(1); + transform: scale(1); } + 50% { + opacity: 1; + -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125)); + transform: scale(var(--fa-beat-fade-scale, 1.125)); } } + +@-webkit-keyframes fa-flip { + 50% { + -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); + transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } } + +@keyframes fa-flip { + 50% { + -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); + transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } } + +@-webkit-keyframes fa-shake { + 0% { + -webkit-transform: rotate(-15deg); + transform: rotate(-15deg); } + 4% { + -webkit-transform: rotate(15deg); + transform: rotate(15deg); } + 8%, 24% { + -webkit-transform: rotate(-18deg); + transform: rotate(-18deg); } + 12%, 28% { + -webkit-transform: rotate(18deg); + transform: rotate(18deg); } + 16% { + -webkit-transform: rotate(-22deg); + transform: rotate(-22deg); } + 20% { + -webkit-transform: rotate(22deg); + transform: rotate(22deg); } + 32% { + -webkit-transform: rotate(-12deg); + transform: rotate(-12deg); } + 36% { + -webkit-transform: rotate(12deg); + transform: rotate(12deg); } + 40%, 100% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); } } + +@keyframes fa-shake { + 0% { + -webkit-transform: rotate(-15deg); + transform: rotate(-15deg); } + 4% { + -webkit-transform: rotate(15deg); + transform: rotate(15deg); } + 8%, 24% { + -webkit-transform: rotate(-18deg); + transform: rotate(-18deg); } + 12%, 28% { + -webkit-transform: rotate(18deg); + transform: rotate(18deg); } + 16% { + -webkit-transform: rotate(-22deg); + transform: rotate(-22deg); } + 20% { + -webkit-transform: rotate(22deg); + transform: rotate(22deg); } + 32% { + -webkit-transform: rotate(-12deg); + transform: rotate(-12deg); } + 36% { + -webkit-transform: rotate(12deg); + transform: rotate(12deg); } + 40%, 100% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); } } + +@-webkit-keyframes fa-spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); } + 100% { + -webkit-transform: rotate(360deg); + transform: rotate(360deg); } } + +@keyframes fa-spin { + 0% { + -webkit-transform: rotate(0deg); + transform: rotate(0deg); } + 100% { + -webkit-transform: rotate(360deg); + transform: rotate(360deg); } } + +.fa-rotate-90 { + -webkit-transform: rotate(90deg); + transform: rotate(90deg); } + +.fa-rotate-180 { + -webkit-transform: rotate(180deg); + transform: rotate(180deg); } + +.fa-rotate-270 { + -webkit-transform: rotate(270deg); + transform: rotate(270deg); } + +.fa-flip-horizontal { + -webkit-transform: scale(-1, 1); + transform: scale(-1, 1); } + +.fa-flip-vertical { + -webkit-transform: scale(1, -1); + transform: scale(1, -1); } + +.fa-flip-both, +.fa-flip-horizontal.fa-flip-vertical { + -webkit-transform: scale(-1, -1); + transform: scale(-1, -1); } + +.fa-rotate-by { + -webkit-transform: rotate(var(--fa-rotate-angle, none)); + transform: rotate(var(--fa-rotate-angle, none)); } + +.fa-stack { + display: inline-block; + height: 2em; + line-height: 2em; + position: relative; + vertical-align: middle; + width: 2.5em; } + +.fa-stack-1x, +.fa-stack-2x { + left: 0; + position: absolute; + text-align: center; + width: 100%; + z-index: var(--fa-stack-z-index, auto); } + +.fa-stack-1x { + line-height: inherit; } + +.fa-stack-2x { + font-size: 2em; } + +.fa-inverse { + color: var(--fa-inverse, #fff); } + +/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen +readers do not read off random characters that represent icons */ +.fa-0::before { + content: "\30"; } + +.fa-1::before { + content: "\31"; } + +.fa-2::before { + content: "\32"; } + +.fa-3::before { + content: "\33"; } + +.fa-4::before { + content: "\34"; } + +.fa-5::before { + content: "\35"; } + +.fa-6::before { + content: "\36"; } + +.fa-7::before { + content: "\37"; } + +.fa-8::before { + content: "\38"; } + +.fa-9::before { + content: "\39"; } + +.fa-a::before { + content: "\41"; } + +.fa-address-book::before { + content: "\f2b9"; } + +.fa-contact-book::before { + content: "\f2b9"; } + +.fa-address-card::before { + content: "\f2bb"; } + +.fa-contact-card::before { + content: "\f2bb"; } + +.fa-vcard::before { + content: "\f2bb"; } + +.fa-align-center::before { + content: "\f037"; } + +.fa-align-justify::before { + content: "\f039"; } + +.fa-align-left::before { + content: "\f036"; } + +.fa-align-right::before { + content: "\f038"; } + +.fa-anchor::before { + content: "\f13d"; } + +.fa-anchor-circle-check::before { + content: "\e4aa"; } + +.fa-anchor-circle-exclamation::before { + content: "\e4ab"; } + +.fa-anchor-circle-xmark::before { + content: "\e4ac"; } + +.fa-anchor-lock::before { + content: "\e4ad"; } + +.fa-angle-down::before { + content: "\f107"; } + +.fa-angle-left::before { + content: "\f104"; } + +.fa-angle-right::before { + content: "\f105"; } + +.fa-angle-up::before { + content: "\f106"; } + +.fa-angles-down::before { + content: "\f103"; } + +.fa-angle-double-down::before { + content: "\f103"; } + +.fa-angles-left::before { + content: "\f100"; } + +.fa-angle-double-left::before { + content: "\f100"; } + +.fa-angles-right::before { + content: "\f101"; } + +.fa-angle-double-right::before { + content: "\f101"; } + +.fa-angles-up::before { + content: "\f102"; } + +.fa-angle-double-up::before { + content: "\f102"; } + +.fa-ankh::before { + content: "\f644"; } + +.fa-apple-whole::before { + content: "\f5d1"; } + +.fa-apple-alt::before { + content: "\f5d1"; } + +.fa-archway::before { + content: "\f557"; } + +.fa-arrow-down::before { + content: "\f063"; } + +.fa-arrow-down-1-9::before { + content: "\f162"; } + +.fa-sort-numeric-asc::before { + content: "\f162"; } + +.fa-sort-numeric-down::before { + content: "\f162"; } + +.fa-arrow-down-9-1::before { + content: "\f886"; } + +.fa-sort-numeric-desc::before { + content: "\f886"; } + +.fa-sort-numeric-down-alt::before { + content: "\f886"; } + +.fa-arrow-down-a-z::before { + content: "\f15d"; } + +.fa-sort-alpha-asc::before { + content: "\f15d"; } + +.fa-sort-alpha-down::before { + content: "\f15d"; } + +.fa-arrow-down-long::before { + content: "\f175"; } + +.fa-long-arrow-down::before { + content: "\f175"; } + +.fa-arrow-down-short-wide::before { + content: "\f884"; } + +.fa-sort-amount-desc::before { + content: "\f884"; } + +.fa-sort-amount-down-alt::before { + content: "\f884"; } + +.fa-arrow-down-up-across-line::before { + content: "\e4af"; } + +.fa-arrow-down-up-lock::before { + content: "\e4b0"; } + +.fa-arrow-down-wide-short::before { + content: "\f160"; } + +.fa-sort-amount-asc::before { + content: "\f160"; } + +.fa-sort-amount-down::before { + content: "\f160"; } + +.fa-arrow-down-z-a::before { + content: "\f881"; } + +.fa-sort-alpha-desc::before { + content: "\f881"; } + +.fa-sort-alpha-down-alt::before { + content: "\f881"; } + +.fa-arrow-left::before { + content: "\f060"; } + +.fa-arrow-left-long::before { + content: "\f177"; } + +.fa-long-arrow-left::before { + content: "\f177"; } + +.fa-arrow-pointer::before { + content: "\f245"; } + +.fa-mouse-pointer::before { + content: "\f245"; } + +.fa-arrow-right::before { + content: "\f061"; } + +.fa-arrow-right-arrow-left::before { + content: "\f0ec"; } + +.fa-exchange::before { + content: "\f0ec"; } + +.fa-arrow-right-from-bracket::before { + content: "\f08b"; } + +.fa-sign-out::before { + content: "\f08b"; } + +.fa-arrow-right-long::before { + content: "\f178"; } + +.fa-long-arrow-right::before { + content: "\f178"; } + +.fa-arrow-right-to-bracket::before { + content: "\f090"; } + +.fa-sign-in::before { + content: "\f090"; } + +.fa-arrow-right-to-city::before { + content: "\e4b3"; } + +.fa-arrow-rotate-left::before { + content: "\f0e2"; } + +.fa-arrow-left-rotate::before { + content: "\f0e2"; } + +.fa-arrow-rotate-back::before { + content: "\f0e2"; } + +.fa-arrow-rotate-backward::before { + content: "\f0e2"; } + +.fa-undo::before { + content: "\f0e2"; } + +.fa-arrow-rotate-right::before { + content: "\f01e"; } + +.fa-arrow-right-rotate::before { + content: "\f01e"; } + +.fa-arrow-rotate-forward::before { + content: "\f01e"; } + +.fa-redo::before { + content: "\f01e"; } + +.fa-arrow-trend-down::before { + content: "\e097"; } + +.fa-arrow-trend-up::before { + content: "\e098"; } + +.fa-arrow-turn-down::before { + content: "\f149"; } + +.fa-level-down::before { + content: "\f149"; } + +.fa-arrow-turn-up::before { + content: "\f148"; } + +.fa-level-up::before { + content: "\f148"; } + +.fa-arrow-up::before { + content: "\f062"; } + +.fa-arrow-up-1-9::before { + content: "\f163"; } + +.fa-sort-numeric-up::before { + content: "\f163"; } + +.fa-arrow-up-9-1::before { + content: "\f887"; } + +.fa-sort-numeric-up-alt::before { + content: "\f887"; } + +.fa-arrow-up-a-z::before { + content: "\f15e"; } + +.fa-sort-alpha-up::before { + content: "\f15e"; } + +.fa-arrow-up-from-bracket::before { + content: "\e09a"; } + +.fa-arrow-up-from-ground-water::before { + content: "\e4b5"; } + +.fa-arrow-up-from-water-pump::before { + content: "\e4b6"; } + +.fa-arrow-up-long::before { + content: "\f176"; } + +.fa-long-arrow-up::before { + content: "\f176"; } + +.fa-arrow-up-right-dots::before { + content: "\e4b7"; } + +.fa-arrow-up-right-from-square::before { + content: "\f08e"; } + +.fa-external-link::before { + content: "\f08e"; } + +.fa-arrow-up-short-wide::before { + content: "\f885"; } + +.fa-sort-amount-up-alt::before { + content: "\f885"; } + +.fa-arrow-up-wide-short::before { + content: "\f161"; } + +.fa-sort-amount-up::before { + content: "\f161"; } + +.fa-arrow-up-z-a::before { + content: "\f882"; } + +.fa-sort-alpha-up-alt::before { + content: "\f882"; } + +.fa-arrows-down-to-line::before { + content: "\e4b8"; } + +.fa-arrows-down-to-people::before { + content: "\e4b9"; } + +.fa-arrows-left-right::before { + content: "\f07e"; } + +.fa-arrows-h::before { + content: "\f07e"; } + +.fa-arrows-left-right-to-line::before { + content: "\e4ba"; } + +.fa-arrows-rotate::before { + content: "\f021"; } + +.fa-refresh::before { + content: "\f021"; } + +.fa-sync::before { + content: "\f021"; } + +.fa-arrows-spin::before { + content: "\e4bb"; } + +.fa-arrows-split-up-and-left::before { + content: "\e4bc"; } + +.fa-arrows-to-circle::before { + content: "\e4bd"; } + +.fa-arrows-to-dot::before { + content: "\e4be"; } + +.fa-arrows-to-eye::before { + content: "\e4bf"; } + +.fa-arrows-turn-right::before { + content: "\e4c0"; } + +.fa-arrows-turn-to-dots::before { + content: "\e4c1"; } + +.fa-arrows-up-down::before { + content: "\f07d"; } + +.fa-arrows-v::before { + content: "\f07d"; } + +.fa-arrows-up-down-left-right::before { + content: "\f047"; } + +.fa-arrows::before { + content: "\f047"; } + +.fa-arrows-up-to-line::before { + content: "\e4c2"; } + +.fa-asterisk::before { + content: "\2a"; } + +.fa-at::before { + content: "\40"; } + +.fa-atom::before { + content: "\f5d2"; } + +.fa-audio-description::before { + content: "\f29e"; } + +.fa-austral-sign::before { + content: "\e0a9"; } + +.fa-award::before { + content: "\f559"; } + +.fa-b::before { + content: "\42"; } + +.fa-baby::before { + content: "\f77c"; } + +.fa-baby-carriage::before { + content: "\f77d"; } + +.fa-carriage-baby::before { + content: "\f77d"; } + +.fa-backward::before { + content: "\f04a"; } + +.fa-backward-fast::before { + content: "\f049"; } + +.fa-fast-backward::before { + content: "\f049"; } + +.fa-backward-step::before { + content: "\f048"; } + +.fa-step-backward::before { + content: "\f048"; } + +.fa-bacon::before { + content: "\f7e5"; } + +.fa-bacteria::before { + content: "\e059"; } + +.fa-bacterium::before { + content: "\e05a"; } + +.fa-bag-shopping::before { + content: "\f290"; } + +.fa-shopping-bag::before { + content: "\f290"; } + +.fa-bahai::before { + content: "\f666"; } + +.fa-baht-sign::before { + content: "\e0ac"; } + +.fa-ban::before { + content: "\f05e"; } + +.fa-cancel::before { + content: "\f05e"; } + +.fa-ban-smoking::before { + content: "\f54d"; } + +.fa-smoking-ban::before { + content: "\f54d"; } + +.fa-bandage::before { + content: "\f462"; } + +.fa-band-aid::before { + content: "\f462"; } + +.fa-barcode::before { + content: "\f02a"; } + +.fa-bars::before { + content: "\f0c9"; } + +.fa-navicon::before { + content: "\f0c9"; } + +.fa-bars-progress::before { + content: "\f828"; } + +.fa-tasks-alt::before { + content: "\f828"; } + +.fa-bars-staggered::before { + content: "\f550"; } + +.fa-reorder::before { + content: "\f550"; } + +.fa-stream::before { + content: "\f550"; } + +.fa-baseball::before { + content: "\f433"; } + +.fa-baseball-ball::before { + content: "\f433"; } + +.fa-baseball-bat-ball::before { + content: "\f432"; } + +.fa-basket-shopping::before { + content: "\f291"; } + +.fa-shopping-basket::before { + content: "\f291"; } + +.fa-basketball::before { + content: "\f434"; } + +.fa-basketball-ball::before { + content: "\f434"; } + +.fa-bath::before { + content: "\f2cd"; } + +.fa-bathtub::before { + content: "\f2cd"; } + +.fa-battery-empty::before { + content: "\f244"; } + +.fa-battery-0::before { + content: "\f244"; } + +.fa-battery-full::before { + content: "\f240"; } + +.fa-battery::before { + content: "\f240"; } + +.fa-battery-5::before { + content: "\f240"; } + +.fa-battery-half::before { + content: "\f242"; } + +.fa-battery-3::before { + content: "\f242"; } + +.fa-battery-quarter::before { + content: "\f243"; } + +.fa-battery-2::before { + content: "\f243"; } + +.fa-battery-three-quarters::before { + content: "\f241"; } + +.fa-battery-4::before { + content: "\f241"; } + +.fa-bed::before { + content: "\f236"; } + +.fa-bed-pulse::before { + content: "\f487"; } + +.fa-procedures::before { + content: "\f487"; } + +.fa-beer-mug-empty::before { + content: "\f0fc"; } + +.fa-beer::before { + content: "\f0fc"; } + +.fa-bell::before { + content: "\f0f3"; } + +.fa-bell-concierge::before { + content: "\f562"; } + +.fa-concierge-bell::before { + content: "\f562"; } + +.fa-bell-slash::before { + content: "\f1f6"; } + +.fa-bezier-curve::before { + content: "\f55b"; } + +.fa-bicycle::before { + content: "\f206"; } + +.fa-binoculars::before { + content: "\f1e5"; } + +.fa-biohazard::before { + content: "\f780"; } + +.fa-bitcoin-sign::before { + content: "\e0b4"; } + +.fa-blender::before { + content: "\f517"; } + +.fa-blender-phone::before { + content: "\f6b6"; } + +.fa-blog::before { + content: "\f781"; } + +.fa-bold::before { + content: "\f032"; } + +.fa-bolt::before { + content: "\f0e7"; } + +.fa-zap::before { + content: "\f0e7"; } + +.fa-bolt-lightning::before { + content: "\e0b7"; } + +.fa-bomb::before { + content: "\f1e2"; } + +.fa-bone::before { + content: "\f5d7"; } + +.fa-bong::before { + content: "\f55c"; } + +.fa-book::before { + content: "\f02d"; } + +.fa-book-atlas::before { + content: "\f558"; } + +.fa-atlas::before { + content: "\f558"; } + +.fa-book-bible::before { + content: "\f647"; } + +.fa-bible::before { + content: "\f647"; } + +.fa-book-bookmark::before { + content: "\e0bb"; } + +.fa-book-journal-whills::before { + content: "\f66a"; } + +.fa-journal-whills::before { + content: "\f66a"; } + +.fa-book-medical::before { + content: "\f7e6"; } + +.fa-book-open::before { + content: "\f518"; } + +.fa-book-open-reader::before { + content: "\f5da"; } + +.fa-book-reader::before { + content: "\f5da"; } + +.fa-book-quran::before { + content: "\f687"; } + +.fa-quran::before { + content: "\f687"; } + +.fa-book-skull::before { + content: "\f6b7"; } + +.fa-book-dead::before { + content: "\f6b7"; } + +.fa-bookmark::before { + content: "\f02e"; } + +.fa-border-all::before { + content: "\f84c"; } + +.fa-border-none::before { + content: "\f850"; } + +.fa-border-top-left::before { + content: "\f853"; } + +.fa-border-style::before { + content: "\f853"; } + +.fa-bore-hole::before { + content: "\e4c3"; } + +.fa-bottle-droplet::before { + content: "\e4c4"; } + +.fa-bottle-water::before { + content: "\e4c5"; } + +.fa-bowl-food::before { + content: "\e4c6"; } + +.fa-bowl-rice::before { + content: "\e2eb"; } + +.fa-bowling-ball::before { + content: "\f436"; } + +.fa-box::before { + content: "\f466"; } + +.fa-box-archive::before { + content: "\f187"; } + +.fa-archive::before { + content: "\f187"; } + +.fa-box-open::before { + content: "\f49e"; } + +.fa-box-tissue::before { + content: "\e05b"; } + +.fa-boxes-packing::before { + content: "\e4c7"; } + +.fa-boxes-stacked::before { + content: "\f468"; } + +.fa-boxes::before { + content: "\f468"; } + +.fa-boxes-alt::before { + content: "\f468"; } + +.fa-braille::before { + content: "\f2a1"; } + +.fa-brain::before { + content: "\f5dc"; } + +.fa-brazilian-real-sign::before { + content: "\e46c"; } + +.fa-bread-slice::before { + content: "\f7ec"; } + +.fa-bridge::before { + content: "\e4c8"; } + +.fa-bridge-circle-check::before { + content: "\e4c9"; } + +.fa-bridge-circle-exclamation::before { + content: "\e4ca"; } + +.fa-bridge-circle-xmark::before { + content: "\e4cb"; } + +.fa-bridge-lock::before { + content: "\e4cc"; } + +.fa-bridge-water::before { + content: "\e4ce"; } + +.fa-briefcase::before { + content: "\f0b1"; } + +.fa-briefcase-medical::before { + content: "\f469"; } + +.fa-broom::before { + content: "\f51a"; } + +.fa-broom-ball::before { + content: "\f458"; } + +.fa-quidditch::before { + content: "\f458"; } + +.fa-quidditch-broom-ball::before { + content: "\f458"; } + +.fa-brush::before { + content: "\f55d"; } + +.fa-bucket::before { + content: "\e4cf"; } + +.fa-bug::before { + content: "\f188"; } + +.fa-bug-slash::before { + content: "\e490"; } + +.fa-bugs::before { + content: "\e4d0"; } + +.fa-building::before { + content: "\f1ad"; } + +.fa-building-circle-arrow-right::before { + content: "\e4d1"; } + +.fa-building-circle-check::before { + content: "\e4d2"; } + +.fa-building-circle-exclamation::before { + content: "\e4d3"; } + +.fa-building-circle-xmark::before { + content: "\e4d4"; } + +.fa-building-columns::before { + content: "\f19c"; } + +.fa-bank::before { + content: "\f19c"; } + +.fa-institution::before { + content: "\f19c"; } + +.fa-museum::before { + content: "\f19c"; } + +.fa-university::before { + content: "\f19c"; } + +.fa-building-flag::before { + content: "\e4d5"; } + +.fa-building-lock::before { + content: "\e4d6"; } + +.fa-building-ngo::before { + content: "\e4d7"; } + +.fa-building-shield::before { + content: "\e4d8"; } + +.fa-building-un::before { + content: "\e4d9"; } + +.fa-building-user::before { + content: "\e4da"; } + +.fa-building-wheat::before { + content: "\e4db"; } + +.fa-bullhorn::before { + content: "\f0a1"; } + +.fa-bullseye::before { + content: "\f140"; } + +.fa-burger::before { + content: "\f805"; } + +.fa-hamburger::before { + content: "\f805"; } + +.fa-burst::before { + content: "\e4dc"; } + +.fa-bus::before { + content: "\f207"; } + +.fa-bus-simple::before { + content: "\f55e"; } + +.fa-bus-alt::before { + content: "\f55e"; } + +.fa-business-time::before { + content: "\f64a"; } + +.fa-briefcase-clock::before { + content: "\f64a"; } + +.fa-c::before { + content: "\43"; } + +.fa-cake-candles::before { + content: "\f1fd"; } + +.fa-birthday-cake::before { + content: "\f1fd"; } + +.fa-cake::before { + content: "\f1fd"; } + +.fa-calculator::before { + content: "\f1ec"; } + +.fa-calendar::before { + content: "\f133"; } + +.fa-calendar-check::before { + content: "\f274"; } + +.fa-calendar-day::before { + content: "\f783"; } + +.fa-calendar-days::before { + content: "\f073"; } + +.fa-calendar-alt::before { + content: "\f073"; } + +.fa-calendar-minus::before { + content: "\f272"; } + +.fa-calendar-plus::before { + content: "\f271"; } + +.fa-calendar-week::before { + content: "\f784"; } + +.fa-calendar-xmark::before { + content: "\f273"; } + +.fa-calendar-times::before { + content: "\f273"; } + +.fa-camera::before { + content: "\f030"; } + +.fa-camera-alt::before { + content: "\f030"; } + +.fa-camera-retro::before { + content: "\f083"; } + +.fa-camera-rotate::before { + content: "\e0d8"; } + +.fa-campground::before { + content: "\f6bb"; } + +.fa-candy-cane::before { + content: "\f786"; } + +.fa-cannabis::before { + content: "\f55f"; } + +.fa-capsules::before { + content: "\f46b"; } + +.fa-car::before { + content: "\f1b9"; } + +.fa-automobile::before { + content: "\f1b9"; } + +.fa-car-battery::before { + content: "\f5df"; } + +.fa-battery-car::before { + content: "\f5df"; } + +.fa-car-burst::before { + content: "\f5e1"; } + +.fa-car-crash::before { + content: "\f5e1"; } + +.fa-car-on::before { + content: "\e4dd"; } + +.fa-car-rear::before { + content: "\f5de"; } + 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"\e0df"; } + +.fa-cent-sign::before { + content: "\e3f5"; } + +.fa-certificate::before { + content: "\f0a3"; } + +.fa-chair::before { + content: "\f6c0"; } + +.fa-chalkboard::before { + content: "\f51b"; } + +.fa-blackboard::before { + content: "\f51b"; } + +.fa-chalkboard-user::before { + content: "\f51c"; } + +.fa-chalkboard-teacher::before { + content: "\f51c"; } + +.fa-champagne-glasses::before { + content: "\f79f"; } + +.fa-glass-cheers::before { + content: "\f79f"; } + +.fa-charging-station::before { + content: "\f5e7"; } + +.fa-chart-area::before { + content: "\f1fe"; } + +.fa-area-chart::before { + content: "\f1fe"; } + +.fa-chart-bar::before { + content: "\f080"; } + +.fa-bar-chart::before { + content: "\f080"; } + +.fa-chart-column::before { + content: "\e0e3"; } + +.fa-chart-gantt::before { + content: "\e0e4"; } + +.fa-chart-line::before { + content: "\f201"; } + +.fa-line-chart::before { + content: "\f201"; } + +.fa-chart-pie::before { + content: "\f200"; } + 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"\e4e4"; } + +.fa-cloud-sun::before { + content: "\f6c4"; } + +.fa-cloud-sun-rain::before { + content: "\f743"; } + +.fa-clover::before { + content: "\e139"; } + +.fa-code::before { + content: "\f121"; } + +.fa-code-branch::before { + content: "\f126"; } + +.fa-code-commit::before { + content: "\f386"; } + +.fa-code-compare::before { + content: "\e13a"; } + +.fa-code-fork::before { + content: "\e13b"; } + +.fa-code-merge::before { + content: "\f387"; } + +.fa-code-pull-request::before { + content: "\e13c"; } + +.fa-coins::before { + content: "\f51e"; } + +.fa-colon-sign::before { + content: "\e140"; } + +.fa-comment::before { + content: "\f075"; } + +.fa-comment-dollar::before { + content: "\f651"; } + +.fa-comment-dots::before { + content: "\f4ad"; } + +.fa-commenting::before { + content: "\f4ad"; } + +.fa-comment-medical::before { + content: "\f7f5"; } + +.fa-comment-slash::before { + content: "\f4b3"; } + +.fa-comment-sms::before { + content: "\f7cd"; } + +.fa-sms::before { + content: "\f7cd"; } + +.fa-comments::before { + content: "\f086"; } + +.fa-comments-dollar::before { + content: "\f653"; } + +.fa-compact-disc::before { + content: "\f51f"; } + +.fa-compass::before { + content: "\f14e"; } + +.fa-compass-drafting::before { + content: "\f568"; } + +.fa-drafting-compass::before { + content: "\f568"; } + +.fa-compress::before { + content: "\f066"; } + +.fa-computer::before { + content: "\e4e5"; } + +.fa-computer-mouse::before { + content: "\f8cc"; } + +.fa-mouse::before { + content: "\f8cc"; } + +.fa-cookie::before { + content: "\f563"; } + +.fa-cookie-bite::before { + content: "\f564"; } + +.fa-copy::before { + content: "\f0c5"; } + +.fa-copyright::before { + content: "\f1f9"; } + +.fa-couch::before { + content: "\f4b8"; } + +.fa-cow::before { + content: "\f6c8"; } + +.fa-credit-card::before { + content: "\f09d"; } + +.fa-credit-card-alt::before { + content: "\f09d"; } + +.fa-crop::before { + content: "\f125"; } + +.fa-crop-simple::before { + content: "\f565"; } + +.fa-crop-alt::before { + content: "\f565"; } + +.fa-cross::before { + content: "\f654"; } + +.fa-crosshairs::before { + content: "\f05b"; } + +.fa-crow::before { + content: "\f520"; } + +.fa-crown::before { + content: "\f521"; } + +.fa-crutch::before { + content: "\f7f7"; } + +.fa-cruzeiro-sign::before { + content: "\e152"; } + +.fa-cube::before { + content: "\f1b2"; } + +.fa-cubes::before { + content: "\f1b3"; } + +.fa-cubes-stacked::before { + content: "\e4e6"; } + +.fa-d::before { + content: "\44"; } + +.fa-database::before { + content: "\f1c0"; } + +.fa-delete-left::before { + content: "\f55a"; } + +.fa-backspace::before { + content: "\f55a"; } + +.fa-democrat::before { + content: "\f747"; } + +.fa-desktop::before { + content: "\f390"; } + +.fa-desktop-alt::before { + content: "\f390"; } + +.fa-dharmachakra::before { + content: "\f655"; } + +.fa-diagram-next::before { + content: "\e476"; } + +.fa-diagram-predecessor::before { + content: "\e477"; } + 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"\f57d"; } + +.fa-earth-asia::before { + content: "\f57e"; } + +.fa-globe-asia::before { + content: "\f57e"; } + +.fa-earth-europe::before { + content: "\f7a2"; } + +.fa-globe-europe::before { + content: "\f7a2"; } + +.fa-earth-oceania::before { + content: "\e47b"; } + +.fa-globe-oceania::before { + content: "\e47b"; } + +.fa-egg::before { + content: "\f7fb"; } + +.fa-eject::before { + content: "\f052"; } + +.fa-elevator::before { + content: "\e16d"; } + +.fa-ellipsis::before { + content: "\f141"; } + +.fa-ellipsis-h::before { + content: "\f141"; } + +.fa-ellipsis-vertical::before { + content: "\f142"; } + +.fa-ellipsis-v::before { + content: "\f142"; } + +.fa-envelope::before { + content: "\f0e0"; } + +.fa-envelope-circle-check::before { + content: "\e4e8"; } + +.fa-envelope-open::before { + content: "\f2b6"; } + +.fa-envelope-open-text::before { + content: "\f658"; } + +.fa-envelopes-bulk::before { + content: "\f674"; } + +.fa-mail-bulk::before { + content: "\f674"; } + 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"\f597"; } + +.fa-face-kiss-wink-heart::before { + content: "\f598"; } + +.fa-kiss-wink-heart::before { + content: "\f598"; } + +.fa-face-laugh::before { + content: "\f599"; } + +.fa-laugh::before { + content: "\f599"; } + +.fa-face-laugh-beam::before { + content: "\f59a"; } + +.fa-laugh-beam::before { + content: "\f59a"; } + +.fa-face-laugh-squint::before { + content: "\f59b"; } + +.fa-laugh-squint::before { + content: "\f59b"; } + +.fa-face-laugh-wink::before { + content: "\f59c"; } + +.fa-laugh-wink::before { + content: "\f59c"; } + +.fa-face-meh::before { + content: "\f11a"; } + +.fa-meh::before { + content: "\f11a"; } + +.fa-face-meh-blank::before { + content: "\f5a4"; } + +.fa-meh-blank::before { + content: "\f5a4"; } + +.fa-face-rolling-eyes::before { + content: "\f5a5"; } + +.fa-meh-rolling-eyes::before { + content: "\f5a5"; } + +.fa-face-sad-cry::before { + content: "\f5b3"; } + +.fa-sad-cry::before { + content: "\f5b3"; } + +.fa-face-sad-tear::before { + content: "\f5b4"; } + 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+ content: "\f56f"; } + +.fa-arrow-right-to-file::before { + content: "\f56f"; } + +.fa-file-invoice::before { + content: "\f570"; } + +.fa-file-invoice-dollar::before { + content: "\f571"; } + +.fa-file-lines::before { + content: "\f15c"; } + +.fa-file-alt::before { + content: "\f15c"; } + +.fa-file-text::before { + content: "\f15c"; } + +.fa-file-medical::before { + content: "\f477"; } + +.fa-file-pdf::before { + content: "\f1c1"; } + +.fa-file-pen::before { + content: "\f31c"; } + +.fa-file-edit::before { + content: "\f31c"; } + +.fa-file-powerpoint::before { + content: "\f1c4"; } + +.fa-file-prescription::before { + content: "\f572"; } + +.fa-file-shield::before { + content: "\e4f0"; } + +.fa-file-signature::before { + content: "\f573"; } + +.fa-file-video::before { + content: "\f1c8"; } + +.fa-file-waveform::before { + content: "\f478"; } + +.fa-file-medical-alt::before { + content: "\f478"; } + +.fa-file-word::before { + content: "\f1c2"; } + +.fa-file-zipper::before { + content: "\f1c6"; } + +.fa-file-archive::before { + content: "\f1c6"; } + +.fa-fill::before { + content: "\f575"; } + +.fa-fill-drip::before { + content: "\f576"; } + +.fa-film::before { + content: "\f008"; } + +.fa-filter::before { + content: "\f0b0"; } + +.fa-filter-circle-dollar::before { + content: "\f662"; } + +.fa-funnel-dollar::before { + content: "\f662"; } + +.fa-filter-circle-xmark::before { + content: "\e17b"; } + +.fa-fingerprint::before { + content: "\f577"; } + +.fa-fire::before { + content: "\f06d"; } + +.fa-fire-burner::before { + content: "\e4f1"; } + +.fa-fire-extinguisher::before { + content: "\f134"; } + +.fa-fire-flame-curved::before { + content: "\f7e4"; } + +.fa-fire-alt::before { + content: "\f7e4"; } + +.fa-fire-flame-simple::before { + content: "\f46a"; } + +.fa-burn::before { + content: "\f46a"; } + +.fa-fish::before { + content: "\f578"; } + +.fa-fish-fins::before { + content: "\e4f2"; } + +.fa-flag::before { + content: "\f024"; } + +.fa-flag-checkered::before { + content: "\f11e"; } + +.fa-flag-usa::before { + content: "\f74d"; } + +.fa-flask::before { + content: "\f0c3"; } + +.fa-flask-vial::before { + content: "\e4f3"; } + +.fa-floppy-disk::before { + content: "\f0c7"; } + +.fa-save::before { + content: "\f0c7"; } + +.fa-florin-sign::before { + content: "\e184"; } + +.fa-folder::before { + content: "\f07b"; } + +.fa-folder-blank::before { + content: "\f07b"; } + +.fa-folder-closed::before { + content: "\e185"; } + +.fa-folder-minus::before { + content: "\f65d"; } + +.fa-folder-open::before { + content: "\f07c"; } + +.fa-folder-plus::before { + content: "\f65e"; } + +.fa-folder-tree::before { + content: "\f802"; } + +.fa-font::before { + content: "\f031"; } + +.fa-football::before { + content: "\f44e"; } + +.fa-football-ball::before { + content: "\f44e"; } + +.fa-forward::before { + content: "\f04e"; } + +.fa-forward-fast::before { + content: "\f050"; } + +.fa-fast-forward::before { + content: "\f050"; } + +.fa-forward-step::before { + content: "\f051"; } + +.fa-step-forward::before { + content: "\f051"; } + +.fa-franc-sign::before { + content: "\e18f"; } + +.fa-frog::before { + content: "\f52e"; } + +.fa-futbol::before { + content: "\f1e3"; } + +.fa-futbol-ball::before { + content: "\f1e3"; } + +.fa-soccer-ball::before { + content: "\f1e3"; } + +.fa-g::before { + content: "\47"; } + +.fa-gamepad::before { + content: "\f11b"; } + +.fa-gas-pump::before { + content: "\f52f"; } + +.fa-gauge::before { + content: "\f624"; } + +.fa-dashboard::before { + content: "\f624"; } + +.fa-gauge-med::before { + content: "\f624"; } + +.fa-tachometer-alt-average::before { + content: "\f624"; } + +.fa-gauge-high::before { + content: "\f625"; } + +.fa-tachometer-alt::before { + content: "\f625"; } + +.fa-tachometer-alt-fast::before { + content: "\f625"; } + +.fa-gauge-simple::before { + content: "\f629"; } + +.fa-gauge-simple-med::before { + content: "\f629"; } + +.fa-tachometer-average::before { + content: "\f629"; } + +.fa-gauge-simple-high::before { + content: "\f62a"; } + +.fa-tachometer::before { + content: "\f62a"; } + +.fa-tachometer-fast::before { + content: "\f62a"; } + +.fa-gavel::before { + content: "\f0e3"; } + +.fa-legal::before { + content: "\f0e3"; } + +.fa-gear::before { + content: "\f013"; } + +.fa-cog::before { + content: "\f013"; } + +.fa-gears::before { + content: "\f085"; } + +.fa-cogs::before { + content: "\f085"; } + +.fa-gem::before { + content: "\f3a5"; } + +.fa-genderless::before { + content: "\f22d"; } + +.fa-ghost::before { + content: "\f6e2"; } + +.fa-gift::before { + content: "\f06b"; } + +.fa-gifts::before { + content: "\f79c"; } + +.fa-glass-water::before { + content: "\e4f4"; } + +.fa-glass-water-droplet::before { + content: "\e4f5"; } + +.fa-glasses::before { + content: "\f530"; } + +.fa-globe::before { + content: "\f0ac"; } + +.fa-golf-ball-tee::before { + content: "\f450"; } + +.fa-golf-ball::before { + content: "\f450"; } + +.fa-gopuram::before { + content: "\f664"; } + +.fa-graduation-cap::before { + content: "\f19d"; } + +.fa-mortar-board::before { + content: "\f19d"; } + +.fa-greater-than::before { + content: "\3e"; } + +.fa-greater-than-equal::before { + content: "\f532"; } + +.fa-grip::before { + content: "\f58d"; } + +.fa-grip-horizontal::before { + content: "\f58d"; } + +.fa-grip-lines::before { + content: "\f7a4"; } + +.fa-grip-lines-vertical::before { + content: "\f7a5"; } + +.fa-grip-vertical::before { + content: "\f58e"; } + +.fa-group-arrows-rotate::before { + content: "\e4f6"; } + +.fa-guarani-sign::before { + content: "\e19a"; } + +.fa-guitar::before { + content: "\f7a6"; } + +.fa-gun::before { + content: "\e19b"; } + +.fa-h::before { + content: "\48"; } + +.fa-hammer::before { + content: "\f6e3"; } + +.fa-hamsa::before { + content: "\f665"; } + +.fa-hand::before { + content: "\f256"; } + +.fa-hand-paper::before { + content: "\f256"; } + +.fa-hand-back-fist::before { + content: "\f255"; } + +.fa-hand-rock::before { + content: "\f255"; } + +.fa-hand-dots::before { + content: "\f461"; } + +.fa-allergies::before { + content: "\f461"; } + +.fa-hand-fist::before { + content: "\f6de"; } + +.fa-fist-raised::before { + content: "\f6de"; } + +.fa-hand-holding::before { + content: "\f4bd"; } + +.fa-hand-holding-dollar::before { + content: "\f4c0"; } + +.fa-hand-holding-usd::before { + content: "\f4c0"; } + +.fa-hand-holding-droplet::before { + content: "\f4c1"; } + +.fa-hand-holding-water::before { + content: "\f4c1"; } + +.fa-hand-holding-hand::before { + content: "\e4f7"; } + +.fa-hand-holding-heart::before { + content: "\f4be"; } + +.fa-hand-holding-medical::before { + content: "\e05c"; } + +.fa-hand-lizard::before { + content: "\f258"; } + +.fa-hand-middle-finger::before { + content: "\f806"; } + +.fa-hand-peace::before { + content: "\f25b"; } + +.fa-hand-point-down::before { + content: "\f0a7"; } + +.fa-hand-point-left::before { + content: "\f0a5"; } + +.fa-hand-point-right::before { + content: "\f0a4"; } + +.fa-hand-point-up::before { + content: "\f0a6"; } + +.fa-hand-pointer::before { + content: "\f25a"; } + +.fa-hand-scissors::before { + content: "\f257"; } + +.fa-hand-sparkles::before { + content: "\e05d"; } + +.fa-hand-spock::before { + content: "\f259"; } + +.fa-handcuffs::before { + content: "\e4f8"; } + +.fa-hands::before { + content: "\f2a7"; } + +.fa-sign-language::before { + content: "\f2a7"; } + +.fa-signing::before { + content: "\f2a7"; } + +.fa-hands-asl-interpreting::before { + content: "\f2a3"; } + +.fa-american-sign-language-interpreting::before { + content: "\f2a3"; } + +.fa-asl-interpreting::before { + content: "\f2a3"; } + +.fa-hands-american-sign-language-interpreting::before { + content: "\f2a3"; } + +.fa-hands-bound::before { + content: "\e4f9"; } + +.fa-hands-bubbles::before { + content: "\e05e"; } + +.fa-hands-wash::before { + content: "\e05e"; } + +.fa-hands-clapping::before { + content: "\e1a8"; } + +.fa-hands-holding::before { + content: "\f4c2"; } + 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"\f6e8"; } + +.fa-head-side-cough::before { + content: "\e061"; } + +.fa-head-side-cough-slash::before { + content: "\e062"; } + +.fa-head-side-mask::before { + content: "\e063"; } + +.fa-head-side-virus::before { + content: "\e064"; } + +.fa-heading::before { + content: "\f1dc"; } + +.fa-header::before { + content: "\f1dc"; } + +.fa-headphones::before { + content: "\f025"; } + +.fa-headphones-simple::before { + content: "\f58f"; } + +.fa-headphones-alt::before { + content: "\f58f"; } + +.fa-headset::before { + content: "\f590"; } + +.fa-heart::before { + content: "\f004"; } + +.fa-heart-circle-bolt::before { + content: "\e4fc"; } + +.fa-heart-circle-check::before { + content: "\e4fd"; } + +.fa-heart-circle-exclamation::before { + content: "\e4fe"; } + +.fa-heart-circle-minus::before { + content: "\e4ff"; } + +.fa-heart-circle-plus::before { + content: "\e500"; } + +.fa-heart-circle-xmark::before { + content: "\e501"; } + +.fa-heart-crack::before { + content: "\f7a9"; } + 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"\f0f8"; } + +.fa-hospital-user::before { + content: "\f80d"; } + +.fa-hot-tub-person::before { + content: "\f593"; } + +.fa-hot-tub::before { + content: "\f593"; } + +.fa-hotdog::before { + content: "\f80f"; } + +.fa-hotel::before { + content: "\f594"; } + +.fa-hourglass::before { + content: "\f254"; } + +.fa-hourglass-2::before { + content: "\f254"; } + +.fa-hourglass-half::before { + content: "\f254"; } + +.fa-hourglass-empty::before { + content: "\f252"; } + +.fa-hourglass-end::before { + content: "\f253"; } + +.fa-hourglass-3::before { + content: "\f253"; } + +.fa-hourglass-start::before { + content: "\f251"; } + +.fa-hourglass-1::before { + content: "\f251"; } + +.fa-house::before { + content: "\f015"; } + +.fa-home::before { + content: "\f015"; } + +.fa-home-alt::before { + content: "\f015"; } + +.fa-home-lg-alt::before { + content: "\f015"; } + +.fa-house-chimney::before { + content: "\e3af"; } + +.fa-home-lg::before { + content: "\e3af"; } + +.fa-house-chimney-crack::before { + content: "\f6f1"; } + +.fa-house-damage::before { + content: "\f6f1"; } + +.fa-house-chimney-medical::before { + content: "\f7f2"; } + +.fa-clinic-medical::before { + content: "\f7f2"; } + +.fa-house-chimney-user::before { + content: "\e065"; } + +.fa-house-chimney-window::before { + content: "\e00d"; } + +.fa-house-circle-check::before { + content: "\e509"; } + +.fa-house-circle-exclamation::before { + content: "\e50a"; } + +.fa-house-circle-xmark::before { + content: "\e50b"; } + +.fa-house-crack::before { + content: "\e3b1"; } + +.fa-house-fire::before { + content: "\e50c"; } + +.fa-house-flag::before { + content: "\e50d"; } + +.fa-house-flood-water::before { + content: "\e50e"; } + +.fa-house-flood-water-circle-arrow-right::before { + content: "\e50f"; } + +.fa-house-laptop::before { + content: "\e066"; } + +.fa-laptop-house::before { + content: "\e066"; } + +.fa-house-lock::before { + content: "\e510"; } + +.fa-house-medical::before { + content: "\e3b2"; } + 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content: "\e51c"; } + +.fa-language::before { + content: "\f1ab"; } + +.fa-laptop::before { + content: "\f109"; } + +.fa-laptop-code::before { + content: "\f5fc"; } + +.fa-laptop-file::before { + content: "\e51d"; } + +.fa-laptop-medical::before { + content: "\f812"; } + +.fa-lari-sign::before { + content: "\e1c8"; } + +.fa-layer-group::before { + content: "\f5fd"; } + +.fa-leaf::before { + content: "\f06c"; } + +.fa-left-long::before { + content: "\f30a"; } + +.fa-long-arrow-alt-left::before { + content: "\f30a"; } + +.fa-left-right::before { + content: "\f337"; } + +.fa-arrows-alt-h::before { + content: "\f337"; } + +.fa-lemon::before { + content: "\f094"; } + +.fa-less-than::before { + content: "\3c"; } + +.fa-less-than-equal::before { + content: "\f537"; } + +.fa-life-ring::before { + content: "\f1cd"; } + +.fa-lightbulb::before { + content: "\f0eb"; } + +.fa-lines-leaning::before { + content: "\e51e"; } + +.fa-link::before { + content: "\f0c1"; } + +.fa-chain::before { + content: "\f0c1"; } + +.fa-link-slash::before { + content: "\f127"; } + +.fa-chain-broken::before { + content: "\f127"; } + +.fa-chain-slash::before { + content: "\f127"; } + +.fa-unlink::before { + content: "\f127"; } + +.fa-lira-sign::before { + content: "\f195"; } + +.fa-list::before { + content: "\f03a"; } + +.fa-list-squares::before { + content: "\f03a"; } + +.fa-list-check::before { + content: "\f0ae"; } + +.fa-tasks::before { + content: "\f0ae"; } + +.fa-list-ol::before { + content: "\f0cb"; } + +.fa-list-1-2::before { + content: "\f0cb"; } + +.fa-list-numeric::before { + content: "\f0cb"; } + +.fa-list-ul::before { + content: "\f0ca"; } + +.fa-list-dots::before { + content: "\f0ca"; } + +.fa-litecoin-sign::before { + content: "\e1d3"; } + +.fa-location-arrow::before { + content: "\f124"; } + +.fa-location-crosshairs::before { + content: "\f601"; } + +.fa-location::before { + content: "\f601"; } + +.fa-location-dot::before { + content: "\f3c5"; } + +.fa-map-marker-alt::before { + content: "\f3c5"; } + +.fa-location-pin::before { + content: "\f041"; } + +.fa-map-marker::before { + content: "\f041"; } + +.fa-location-pin-lock::before { + content: "\e51f"; } + +.fa-lock::before { + content: "\f023"; } + +.fa-lock-open::before { + content: "\f3c1"; } + +.fa-locust::before { + content: "\e520"; } + +.fa-lungs::before { + content: "\f604"; } + +.fa-lungs-virus::before { + content: "\e067"; } + +.fa-m::before { + content: "\4d"; } + +.fa-magnet::before { + content: "\f076"; } + +.fa-magnifying-glass::before { + content: "\f002"; } + +.fa-search::before { + content: "\f002"; } + +.fa-magnifying-glass-arrow-right::before { + content: "\e521"; } + +.fa-magnifying-glass-chart::before { + content: "\e522"; } + +.fa-magnifying-glass-dollar::before { + content: "\f688"; } + +.fa-search-dollar::before { + content: "\f688"; } + +.fa-magnifying-glass-location::before { + content: "\f689"; } + +.fa-search-location::before { + content: "\f689"; } + 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content: "\f3ce"; } + +.fa-mobile-phone::before { + content: "\f3ce"; } + +.fa-mobile-button::before { + content: "\f10b"; } + +.fa-mobile-retro::before { + content: "\e527"; } + +.fa-mobile-screen::before { + content: "\f3cf"; } + +.fa-mobile-android-alt::before { + content: "\f3cf"; } + +.fa-mobile-screen-button::before { + content: "\f3cd"; } + +.fa-mobile-alt::before { + content: "\f3cd"; } + +.fa-money-bill::before { + content: "\f0d6"; } + +.fa-money-bill-1::before { + content: "\f3d1"; } + +.fa-money-bill-alt::before { + content: "\f3d1"; } + +.fa-money-bill-1-wave::before { + content: "\f53b"; } + +.fa-money-bill-wave-alt::before { + content: "\f53b"; } + +.fa-money-bill-transfer::before { + content: "\e528"; } + +.fa-money-bill-trend-up::before { + content: "\e529"; } + +.fa-money-bill-wave::before { + content: "\f53a"; } + +.fa-money-bill-wheat::before { + content: "\e52a"; } + +.fa-money-bills::before { + content: "\e1f3"; } + +.fa-money-check::before { + content: "\f53c"; } 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"\f044"; } + +.fa-pencil::before { + content: "\f303"; } + +.fa-pencil-alt::before { + content: "\f303"; } + +.fa-people-arrows-left-right::before { + content: "\e068"; } + +.fa-people-arrows::before { + content: "\e068"; } + +.fa-people-carry-box::before { + content: "\f4ce"; } + +.fa-people-carry::before { + content: "\f4ce"; } + +.fa-people-group::before { + content: "\e533"; } + +.fa-people-line::before { + content: "\e534"; } + +.fa-people-pulling::before { + content: "\e535"; } + +.fa-people-robbery::before { + content: "\e536"; } + +.fa-people-roof::before { + content: "\e537"; } + +.fa-pepper-hot::before { + content: "\f816"; } + +.fa-percent::before { + content: "\25"; } + +.fa-percentage::before { + content: "\25"; } + +.fa-person::before { + content: "\f183"; } + +.fa-male::before { + content: "\f183"; } + +.fa-person-arrow-down-to-line::before { + content: "\e538"; } + +.fa-person-arrow-up-from-line::before { + content: "\e539"; } + +.fa-person-biking::before { + content: "\f84a"; } + +.fa-biking::before { + content: "\f84a"; } + +.fa-person-booth::before { + content: "\f756"; } + +.fa-person-breastfeeding::before { + content: "\e53a"; } + +.fa-person-burst::before { + content: "\e53b"; } + +.fa-person-cane::before { + content: "\e53c"; } + +.fa-person-chalkboard::before { + content: "\e53d"; } + +.fa-person-circle-check::before { + content: "\e53e"; } + +.fa-person-circle-exclamation::before { + content: "\e53f"; } + +.fa-person-circle-minus::before { + content: "\e540"; } + +.fa-person-circle-plus::before { + content: "\e541"; } + +.fa-person-circle-question::before { + content: "\e542"; } + +.fa-person-circle-xmark::before { + content: "\e543"; } + +.fa-person-digging::before { + content: "\f85e"; } + +.fa-digging::before { + content: "\f85e"; } + +.fa-person-dots-from-line::before { + content: "\f470"; } + +.fa-diagnoses::before { + content: "\f470"; } + +.fa-person-dress::before { + content: "\f182"; } + +.fa-female::before { + content: "\f182"; } 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content: "\e554"; } + +.fa-person-walking-with-cane::before { + content: "\f29d"; } + +.fa-blind::before { + content: "\f29d"; } + +.fa-peseta-sign::before { + content: "\e221"; } + +.fa-peso-sign::before { + content: "\e222"; } + +.fa-phone::before { + content: "\f095"; } + +.fa-phone-flip::before { + content: "\f879"; } + +.fa-phone-alt::before { + content: "\f879"; } + +.fa-phone-slash::before { + content: "\f3dd"; } + +.fa-phone-volume::before { + content: "\f2a0"; } + +.fa-volume-control-phone::before { + content: "\f2a0"; } + +.fa-photo-film::before { + content: "\f87c"; } + +.fa-photo-video::before { + content: "\f87c"; } + +.fa-piggy-bank::before { + content: "\f4d3"; } + +.fa-pills::before { + content: "\f484"; } + +.fa-pizza-slice::before { + content: "\f818"; } + +.fa-place-of-worship::before { + content: "\f67f"; } + +.fa-plane::before { + content: "\f072"; } + +.fa-plane-arrival::before { + content: "\f5af"; } + +.fa-plane-circle-check::before { + content: "\e555"; } + 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content: "\f0cc"; } + +.fa-stroopwafel::before { + content: "\f551"; } + +.fa-subscript::before { + content: "\f12c"; } + +.fa-suitcase::before { + content: "\f0f2"; } + +.fa-suitcase-medical::before { + content: "\f0fa"; } + +.fa-medkit::before { + content: "\f0fa"; } + +.fa-suitcase-rolling::before { + content: "\f5c1"; } + +.fa-sun::before { + content: "\f185"; } + +.fa-sun-plant-wilt::before { + content: "\e57a"; } + +.fa-superscript::before { + content: "\f12b"; } + +.fa-swatchbook::before { + content: "\f5c3"; } + +.fa-synagogue::before { + content: "\f69b"; } + +.fa-syringe::before { + content: "\f48e"; } + +.fa-t::before { + content: "\54"; } + +.fa-table::before { + content: "\f0ce"; } + +.fa-table-cells::before { + content: "\f00a"; } + +.fa-th::before { + content: "\f00a"; } + +.fa-table-cells-large::before { + content: "\f009"; } + +.fa-th-large::before { + content: "\f009"; } + +.fa-table-columns::before { + content: "\f0db"; } + +.fa-columns::before { + content: "\f0db"; } + +.fa-table-list::before { + content: "\f00b"; } + +.fa-th-list::before { + content: "\f00b"; } + +.fa-table-tennis-paddle-ball::before { + content: "\f45d"; } + +.fa-ping-pong-paddle-ball::before { + content: "\f45d"; } + +.fa-table-tennis::before { + content: "\f45d"; } + +.fa-tablet::before { + content: "\f3fb"; } + +.fa-tablet-android::before { + content: "\f3fb"; } + +.fa-tablet-button::before { + content: "\f10a"; } + +.fa-tablet-screen-button::before { + content: "\f3fa"; } + +.fa-tablet-alt::before { + content: "\f3fa"; } + +.fa-tablets::before { + content: "\f490"; } + +.fa-tachograph-digital::before { + content: "\f566"; } + +.fa-digital-tachograph::before { + content: "\f566"; } + +.fa-tag::before { + content: "\f02b"; } + +.fa-tags::before { + content: "\f02c"; } + +.fa-tape::before { + content: "\f4db"; } + +.fa-tarp::before { + content: "\e57b"; } + +.fa-tarp-droplet::before { + content: "\e57c"; } + +.fa-taxi::before { + content: "\f1ba"; } + +.fa-cab::before { + content: "\f1ba"; } + +.fa-teeth::before { + content: "\f62e"; } + +.fa-teeth-open::before { + content: "\f62f"; } + +.fa-temperature-arrow-down::before { + content: "\e03f"; } + +.fa-temperature-down::before { + content: "\e03f"; } + +.fa-temperature-arrow-up::before { + content: "\e040"; } + +.fa-temperature-up::before { + content: "\e040"; } + +.fa-temperature-empty::before { + content: "\f2cb"; } + +.fa-temperature-0::before { + content: "\f2cb"; } + +.fa-thermometer-0::before { + content: "\f2cb"; } + +.fa-thermometer-empty::before { + content: "\f2cb"; } + +.fa-temperature-full::before { + content: "\f2c7"; } + +.fa-temperature-4::before { + content: "\f2c7"; } + +.fa-thermometer-4::before { + content: "\f2c7"; } + +.fa-thermometer-full::before { + content: "\f2c7"; } + +.fa-temperature-half::before { + content: "\f2c9"; } + +.fa-temperature-2::before { + content: "\f2c9"; } + +.fa-thermometer-2::before { + content: "\f2c9"; } + +.fa-thermometer-half::before { + content: "\f2c9"; } + +.fa-temperature-high::before { + content: "\f769"; } + +.fa-temperature-low::before { + content: "\f76b"; } + +.fa-temperature-quarter::before { + content: "\f2ca"; } + +.fa-temperature-1::before { + content: "\f2ca"; } + +.fa-thermometer-1::before { + content: "\f2ca"; } + +.fa-thermometer-quarter::before { + content: "\f2ca"; } + +.fa-temperature-three-quarters::before { + content: "\f2c8"; } + +.fa-temperature-3::before { + content: "\f2c8"; } + +.fa-thermometer-3::before { + content: "\f2c8"; } + +.fa-thermometer-three-quarters::before { + content: "\f2c8"; } + +.fa-tenge-sign::before { + content: "\f7d7"; } + +.fa-tenge::before { + content: "\f7d7"; } + +.fa-tent::before { + content: "\e57d"; } + +.fa-tent-arrow-down-to-line::before { + content: "\e57e"; } + +.fa-tent-arrow-left-right::before { + content: "\e57f"; } + +.fa-tent-arrow-turn-left::before { + content: "\e580"; } + +.fa-tent-arrows-down::before { + content: "\e581"; } + +.fa-tents::before { + content: "\e582"; } + +.fa-terminal::before { + content: "\f120"; } + +.fa-text-height::before { + content: "\f034"; } + +.fa-text-slash::before { + content: "\f87d"; } + +.fa-remove-format::before { + content: "\f87d"; } + +.fa-text-width::before { + content: "\f035"; } + +.fa-thermometer::before { + content: "\f491"; } + +.fa-thumbs-down::before { + content: "\f165"; } + +.fa-thumbs-up::before { + content: "\f164"; } + +.fa-thumbtack::before { + content: "\f08d"; } + +.fa-thumb-tack::before { + content: "\f08d"; } + +.fa-ticket::before { + content: "\f145"; } + +.fa-ticket-simple::before { + content: "\f3ff"; } + +.fa-ticket-alt::before { + content: "\f3ff"; } + +.fa-timeline::before { + content: "\e29c"; } + +.fa-toggle-off::before { + content: "\f204"; } + +.fa-toggle-on::before { + content: "\f205"; } + +.fa-toilet::before { + content: "\f7d8"; } + +.fa-toilet-paper::before { + content: "\f71e"; } + +.fa-toilet-paper-slash::before { + content: "\e072"; } + +.fa-toilet-portable::before { + content: "\e583"; } + +.fa-toilets-portable::before { + content: "\e584"; } + +.fa-toolbox::before { + content: "\f552"; } + +.fa-tooth::before { + content: "\f5c9"; } + +.fa-torii-gate::before { + content: "\f6a1"; } + +.fa-tornado::before { + content: "\f76f"; } + +.fa-tower-broadcast::before { + content: "\f519"; } + +.fa-broadcast-tower::before { + content: "\f519"; } + +.fa-tower-cell::before { + content: "\e585"; } + +.fa-tower-observation::before { + content: "\e586"; } + +.fa-tractor::before { + content: "\f722"; } + +.fa-trademark::before { + content: "\f25c"; } + +.fa-traffic-light::before { + content: "\f637"; } + +.fa-trailer::before { + content: "\e041"; } + +.fa-train::before { + content: "\f238"; } + +.fa-train-subway::before { + content: "\f239"; } + +.fa-subway::before { + content: "\f239"; } + +.fa-train-tram::before { + content: "\f7da"; } + +.fa-tram::before { + content: "\f7da"; } + +.fa-transgender::before { + content: "\f225"; } + +.fa-transgender-alt::before { + content: "\f225"; } + +.fa-trash::before { + content: "\f1f8"; } + +.fa-trash-arrow-up::before { + content: "\f829"; } + +.fa-trash-restore::before { + content: "\f829"; } + +.fa-trash-can::before { + content: "\f2ed"; } + +.fa-trash-alt::before { + content: "\f2ed"; } + +.fa-trash-can-arrow-up::before { + content: "\f82a"; } + +.fa-trash-restore-alt::before { + content: "\f82a"; } + +.fa-tree::before { + content: "\f1bb"; } + +.fa-tree-city::before { + content: "\e587"; } + +.fa-triangle-exclamation::before { + content: "\f071"; } + +.fa-exclamation-triangle::before { + content: "\f071"; } + +.fa-warning::before { + content: "\f071"; } + +.fa-trophy::before { + content: "\f091"; } + +.fa-trowel::before { + content: "\e589"; } + +.fa-trowel-bricks::before { + content: "\e58a"; } + +.fa-truck::before { + content: "\f0d1"; } + +.fa-truck-arrow-right::before { + content: "\e58b"; } + +.fa-truck-droplet::before { + content: "\e58c"; } + +.fa-truck-fast::before { + content: "\f48b"; } + +.fa-shipping-fast::before { + content: "\f48b"; } + +.fa-truck-field::before { + content: "\e58d"; } + +.fa-truck-field-un::before { + content: "\e58e"; } + +.fa-truck-front::before { + content: "\e2b7"; } + +.fa-truck-medical::before { + content: "\f0f9"; } + +.fa-ambulance::before { + content: "\f0f9"; } + +.fa-truck-monster::before { + content: "\f63b"; } + +.fa-truck-moving::before { + content: "\f4df"; } + +.fa-truck-pickup::before { + content: "\f63c"; } + +.fa-truck-plane::before { + content: "\e58f"; } + +.fa-truck-ramp-box::before { + content: "\f4de"; } + +.fa-truck-loading::before { + content: "\f4de"; } + +.fa-tty::before { + content: "\f1e4"; } + +.fa-teletype::before { + content: "\f1e4"; } + +.fa-turkish-lira-sign::before { + content: "\e2bb"; } + +.fa-try::before { + content: "\e2bb"; } + +.fa-turkish-lira::before { + content: "\e2bb"; } + +.fa-turn-down::before { + content: "\f3be"; } + +.fa-level-down-alt::before { + content: "\f3be"; } + +.fa-turn-up::before { + content: "\f3bf"; } + +.fa-level-up-alt::before { + content: "\f3bf"; } + +.fa-tv::before { + content: "\f26c"; } + +.fa-television::before { + content: "\f26c"; } + +.fa-tv-alt::before { + content: "\f26c"; } + +.fa-u::before { + content: "\55"; } + +.fa-umbrella::before { + content: "\f0e9"; } + +.fa-umbrella-beach::before { + content: "\f5ca"; } + +.fa-underline::before { + content: "\f0cd"; } + +.fa-universal-access::before { + content: "\f29a"; } + +.fa-unlock::before { + content: "\f09c"; } + +.fa-unlock-keyhole::before { + content: "\f13e"; } + +.fa-unlock-alt::before { + content: "\f13e"; } + +.fa-up-down::before { + content: "\f338"; } + +.fa-arrows-alt-v::before { + content: "\f338"; } + +.fa-up-down-left-right::before { + content: "\f0b2"; } + +.fa-arrows-alt::before { + content: "\f0b2"; } + +.fa-up-long::before { + content: "\f30c"; } + +.fa-long-arrow-alt-up::before { + content: "\f30c"; } + +.fa-up-right-and-down-left-from-center::before { + content: "\f424"; } + +.fa-expand-alt::before { + content: "\f424"; } + +.fa-up-right-from-square::before { + content: "\f35d"; } + +.fa-external-link-alt::before { + content: "\f35d"; } + +.fa-upload::before { + content: "\f093"; } + +.fa-user::before { + content: "\f007"; } + +.fa-user-astronaut::before { + content: "\f4fb"; } + +.fa-user-check::before { + content: "\f4fc"; } + +.fa-user-clock::before { + content: "\f4fd"; } + +.fa-user-doctor::before { + content: "\f0f0"; } + +.fa-user-md::before { + content: "\f0f0"; } + +.fa-user-gear::before { + content: "\f4fe"; } + +.fa-user-cog::before { + content: "\f4fe"; } + +.fa-user-graduate::before { + content: "\f501"; } + +.fa-user-group::before { + content: "\f500"; } + +.fa-user-friends::before { + content: "\f500"; } + +.fa-user-injured::before { + content: "\f728"; } + +.fa-user-large::before { + content: "\f406"; } + +.fa-user-alt::before { + content: "\f406"; } + +.fa-user-large-slash::before { + content: "\f4fa"; } + +.fa-user-alt-slash::before { + content: "\f4fa"; } + +.fa-user-lock::before { + content: "\f502"; } + +.fa-user-minus::before { + content: "\f503"; } + +.fa-user-ninja::before { + content: "\f504"; } + +.fa-user-nurse::before { + content: "\f82f"; } + +.fa-user-pen::before { + content: "\f4ff"; } + +.fa-user-edit::before { + content: "\f4ff"; } + +.fa-user-plus::before { + content: "\f234"; } + +.fa-user-secret::before { + content: "\f21b"; } + +.fa-user-shield::before { + content: "\f505"; } + +.fa-user-slash::before { + content: "\f506"; } + +.fa-user-tag::before { + content: "\f507"; } + +.fa-user-tie::before { + content: "\f508"; } + +.fa-user-xmark::before { + content: "\f235"; } + +.fa-user-times::before { + content: "\f235"; } + +.fa-users::before { + content: "\f0c0"; } + +.fa-users-between-lines::before { + content: "\e591"; } + +.fa-users-gear::before { + content: "\f509"; } + +.fa-users-cog::before { + content: "\f509"; } + +.fa-users-line::before { + content: "\e592"; } + +.fa-users-rays::before { + content: "\e593"; } + +.fa-users-rectangle::before { + content: "\e594"; } + +.fa-users-slash::before { + content: "\e073"; } + +.fa-users-viewfinder::before { + content: "\e595"; } + +.fa-utensils::before { + content: "\f2e7"; } + +.fa-cutlery::before { + content: "\f2e7"; } + +.fa-v::before { + content: "\56"; } + +.fa-van-shuttle::before { + content: "\f5b6"; } + +.fa-shuttle-van::before { + content: "\f5b6"; } + +.fa-vault::before { + content: "\e2c5"; } + +.fa-vector-square::before { + content: "\f5cb"; } + +.fa-venus::before { + content: "\f221"; } + +.fa-venus-double::before { + content: "\f226"; } + +.fa-venus-mars::before { + content: "\f228"; } + +.fa-vest::before { + content: "\e085"; } + +.fa-vest-patches::before { + content: "\e086"; } + +.fa-vial::before { + content: "\f492"; } + +.fa-vial-circle-check::before { + content: "\e596"; } + +.fa-vial-virus::before { + content: "\e597"; } + +.fa-vials::before { + content: "\f493"; } + +.fa-video::before { + content: "\f03d"; } + +.fa-video-camera::before { + content: "\f03d"; } + +.fa-video-slash::before { + content: "\f4e2"; } + +.fa-vihara::before { + content: "\f6a7"; } + +.fa-virus::before { + content: "\e074"; } + +.fa-virus-covid::before { + content: "\e4a8"; } + +.fa-virus-covid-slash::before { + content: "\e4a9"; } + +.fa-virus-slash::before { + content: "\e075"; } + +.fa-viruses::before { + content: "\e076"; } + +.fa-voicemail::before { + content: "\f897"; } + +.fa-volcano::before { + content: "\f770"; } + +.fa-volleyball::before { + content: "\f45f"; } + +.fa-volleyball-ball::before { + content: "\f45f"; } + +.fa-volume-high::before { + content: "\f028"; } + +.fa-volume-up::before { + content: "\f028"; } + +.fa-volume-low::before { + content: "\f027"; } + +.fa-volume-down::before { + content: "\f027"; } + +.fa-volume-off::before { + content: "\f026"; } + +.fa-volume-xmark::before { + content: "\f6a9"; } + +.fa-volume-mute::before { + content: "\f6a9"; } + +.fa-volume-times::before { + content: "\f6a9"; } + +.fa-vr-cardboard::before { + content: "\f729"; } + +.fa-w::before { + content: "\57"; } + +.fa-walkie-talkie::before { + content: "\f8ef"; } + +.fa-wallet::before { + content: "\f555"; } + +.fa-wand-magic::before { + content: "\f0d0"; } + +.fa-magic::before { + content: "\f0d0"; } + +.fa-wand-magic-sparkles::before { + content: "\e2ca"; } + +.fa-magic-wand-sparkles::before { + content: "\e2ca"; } + +.fa-wand-sparkles::before { + content: "\f72b"; } + +.fa-warehouse::before { + content: "\f494"; } + +.fa-water::before { + content: "\f773"; } + +.fa-water-ladder::before { + content: "\f5c5"; } + +.fa-ladder-water::before { + content: "\f5c5"; } + +.fa-swimming-pool::before { + content: "\f5c5"; } + +.fa-wave-square::before { + content: "\f83e"; } + +.fa-weight-hanging::before { + content: "\f5cd"; } + +.fa-weight-scale::before { + content: "\f496"; } + +.fa-weight::before { + content: "\f496"; } + +.fa-wheat-awn::before { + content: "\e2cd"; } + +.fa-wheat-alt::before { + content: "\e2cd"; } + +.fa-wheat-awn-circle-exclamation::before { + content: "\e598"; } + +.fa-wheelchair::before { + content: "\f193"; } + +.fa-wheelchair-move::before { + content: "\e2ce"; } + +.fa-wheelchair-alt::before { + content: "\e2ce"; } + +.fa-whiskey-glass::before { + content: "\f7a0"; } + +.fa-glass-whiskey::before { + content: "\f7a0"; } + +.fa-wifi::before { + content: "\f1eb"; } + +.fa-wifi-3::before { + content: "\f1eb"; } + +.fa-wifi-strong::before { + content: "\f1eb"; } + +.fa-wind::before { + content: "\f72e"; } + +.fa-window-maximize::before { + content: "\f2d0"; } + +.fa-window-minimize::before { + content: "\f2d1"; } + +.fa-window-restore::before { + content: "\f2d2"; } + +.fa-wine-bottle::before { + content: "\f72f"; } + +.fa-wine-glass::before { + content: "\f4e3"; } + +.fa-wine-glass-empty::before { + content: "\f5ce"; } + +.fa-wine-glass-alt::before { + content: "\f5ce"; } + +.fa-won-sign::before { + content: "\f159"; } + +.fa-krw::before { + content: "\f159"; } + +.fa-won::before { + content: "\f159"; } + +.fa-worm::before { + content: "\e599"; } + +.fa-wrench::before { + content: "\f0ad"; } + +.fa-x::before { + content: "\58"; } + +.fa-x-ray::before { + content: "\f497"; } + +.fa-xmark::before { + content: "\f00d"; } + +.fa-close::before { + content: "\f00d"; } + +.fa-multiply::before { + content: "\f00d"; } + +.fa-remove::before { + content: "\f00d"; } + +.fa-times::before { + content: "\f00d"; } + +.fa-xmarks-lines::before { + content: "\e59a"; } + +.fa-y::before { + content: "\59"; } + +.fa-yen-sign::before { + content: "\f157"; } + +.fa-cny::before { + content: "\f157"; } + +.fa-jpy::before { + content: "\f157"; } + +.fa-rmb::before { + content: "\f157"; } + +.fa-yen::before { + content: "\f157"; } + +.fa-yin-yang::before { + content: "\f6ad"; } + +.fa-z::before { + content: "\5a"; } + +.sr-only, +.fa-sr-only { + position: absolute; + width: 1px; + height: 1px; + padding: 0; + margin: -1px; + overflow: hidden; + clip: rect(0, 0, 0, 0); + white-space: nowrap; + border-width: 0; } + +.sr-only-focusable:not(:focus), +.fa-sr-only-focusable:not(:focus) { + position: absolute; + width: 1px; + height: 1px; + padding: 0; + margin: -1px; + overflow: hidden; + clip: rect(0, 0, 0, 0); + white-space: nowrap; + border-width: 0; } +:root, :host { + --fa-font-brands: normal 400 1em/1 "Font Awesome 6 Brands"; } + +@font-face { + font-family: 'Font Awesome 6 Brands'; + font-style: normal; + font-weight: 400; + font-display: block; + src: url("1e21o67/fa-brands-400.woff2") format("woff2"), url("1e21o67/fa-brands-400.ttf") format("truetype"); } + +.fab, +.fa-brands { + font-family: 'Font Awesome 6 Brands'; + font-weight: 400; } + +.fa-42-group:before { + content: "\e080"; } + +.fa-innosoft:before { + content: "\e080"; } + +.fa-500px:before { + content: "\f26e"; } + +.fa-accessible-icon:before { + content: "\f368"; } + +.fa-accusoft:before { + content: "\f369"; } + +.fa-adn:before { + content: "\f170"; } + +.fa-adversal:before { + content: "\f36a"; } + +.fa-affiliatetheme:before { + content: "\f36b"; } + +.fa-airbnb:before { + content: "\f834"; } + +.fa-algolia:before { + content: "\f36c"; } + +.fa-alipay:before { + content: "\f642"; } + +.fa-amazon:before { + content: "\f270"; } + +.fa-amazon-pay:before { + content: "\f42c"; } + +.fa-amilia:before { + content: "\f36d"; } + +.fa-android:before { + content: "\f17b"; } + +.fa-angellist:before { + content: "\f209"; } + +.fa-angrycreative:before { + content: "\f36e"; } + +.fa-angular:before { + content: "\f420"; } + +.fa-app-store:before { + content: "\f36f"; } + +.fa-app-store-ios:before { + content: "\f370"; } + +.fa-apper:before { + content: "\f371"; } + +.fa-apple:before { + content: "\f179"; } + +.fa-apple-pay:before { + content: "\f415"; } + +.fa-artstation:before { + content: "\f77a"; } + +.fa-asymmetrik:before { + content: "\f372"; } + +.fa-atlassian:before { + content: "\f77b"; } + +.fa-audible:before { + content: "\f373"; } + +.fa-autoprefixer:before { + content: "\f41c"; } + +.fa-avianex:before { + content: "\f374"; } + +.fa-aviato:before { + content: "\f421"; } + +.fa-aws:before { + content: "\f375"; } + +.fa-bandcamp:before { + content: "\f2d5"; } + +.fa-battle-net:before { + content: "\f835"; } + +.fa-behance:before { + content: "\f1b4"; } + +.fa-behance-square:before { + content: "\f1b5"; } + +.fa-bilibili:before { + content: "\e3d9"; } + +.fa-bimobject:before { + content: "\f378"; } + +.fa-bitbucket:before { + content: "\f171"; } + +.fa-bitcoin:before { + content: "\f379"; } + +.fa-bity:before { + content: "\f37a"; } + +.fa-black-tie:before { + content: "\f27e"; } + +.fa-blackberry:before { + content: "\f37b"; } + +.fa-blogger:before { + content: "\f37c"; } + +.fa-blogger-b:before { + content: "\f37d"; } + +.fa-bluetooth:before { + content: "\f293"; } + +.fa-bluetooth-b:before { + content: "\f294"; } + +.fa-bootstrap:before { + content: "\f836"; } + +.fa-bots:before { + content: "\e340"; } + +.fa-btc:before { + content: "\f15a"; } + +.fa-buffer:before { + content: "\f837"; } + +.fa-buromobelexperte:before { + content: "\f37f"; } + +.fa-buy-n-large:before { + content: "\f8a6"; } + +.fa-buysellads:before { + content: "\f20d"; } + +.fa-canadian-maple-leaf:before { + content: "\f785"; } + +.fa-cc-amazon-pay:before { + content: "\f42d"; } + +.fa-cc-amex:before { + content: "\f1f3"; } + +.fa-cc-apple-pay:before { + content: "\f416"; } + +.fa-cc-diners-club:before { + content: "\f24c"; } + +.fa-cc-discover:before { + content: "\f1f2"; } + +.fa-cc-jcb:before { + content: "\f24b"; } + +.fa-cc-mastercard:before { + content: "\f1f1"; } + +.fa-cc-paypal:before { + content: "\f1f4"; } + +.fa-cc-stripe:before { + content: "\f1f5"; } + +.fa-cc-visa:before { + content: "\f1f0"; } + +.fa-centercode:before { + content: "\f380"; } + +.fa-centos:before { + content: "\f789"; } + +.fa-chrome:before { + content: "\f268"; } + +.fa-chromecast:before { + content: "\f838"; } + +.fa-cloudflare:before { + content: "\e07d"; } + +.fa-cloudscale:before { + content: "\f383"; } + +.fa-cloudsmith:before { + content: "\f384"; } + +.fa-cloudversify:before { + content: "\f385"; } + +.fa-cmplid:before { + content: "\e360"; } + +.fa-codepen:before { + content: "\f1cb"; } + +.fa-codiepie:before { + content: "\f284"; } + +.fa-confluence:before { + content: "\f78d"; } + +.fa-connectdevelop:before { + content: "\f20e"; } + +.fa-contao:before { + content: "\f26d"; } + +.fa-cotton-bureau:before { + content: "\f89e"; } + +.fa-cpanel:before { + content: "\f388"; } + +.fa-creative-commons:before { + content: "\f25e"; } + +.fa-creative-commons-by:before { + content: "\f4e7"; } + +.fa-creative-commons-nc:before { + content: "\f4e8"; } + +.fa-creative-commons-nc-eu:before { + content: "\f4e9"; } + +.fa-creative-commons-nc-jp:before { + content: "\f4ea"; } + +.fa-creative-commons-nd:before { + content: "\f4eb"; } + +.fa-creative-commons-pd:before { + content: "\f4ec"; } + +.fa-creative-commons-pd-alt:before { + content: "\f4ed"; } 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format("woff2"), url("1e21o67/fa-solid-900.ttf") format("truetype"); } + +.fas, +.fa-solid { + font-family: 'Font Awesome 6 Free'; + font-weight: 900; } +@font-face { + font-family: "Font Awesome 5 Brands"; + font-display: block; + font-weight: 400; + src: url("1e21o67/fa-brands-400.woff2") format("woff2"), url("1e21o67/fa-brands-400.ttf") format("truetype"); } + +@font-face { + font-family: "Font Awesome 5 Free"; + font-display: block; + font-weight: 900; + src: url("1e21o67/fa-solid-900.woff2") format("woff2"), url("1e21o67/fa-solid-900.ttf") format("truetype"); } + +@font-face { + font-family: "Font Awesome 5 Free"; + font-display: block; + font-weight: 400; + src: url("1e21o67/fa-regular-400.woff2") format("woff2"), url("1e21o67/fa-regular-400.ttf") format("truetype"); } +@font-face { + font-family: "FontAwesome"; + font-display: block; + src: url("1e21o67/fa-solid-900.woff2") format("woff2"), url("1e21o67/fa-solid-900.ttf") format("truetype"); } + +@font-face { + font-family: "FontAwesome"; + font-display: block; + src: url("1e21o67/fa-brands-400.woff2") format("woff2"), url("1e21o67/fa-brands-400.ttf") format("truetype"); } + +@font-face { + font-family: "FontAwesome"; + font-display: block; + src: url("1e21o67/fa-regular-400.woff2") format("woff2"), url("1e21o67/fa-regular-400.ttf") format("truetype"); + unicode-range: U+F003,U+F006,U+F014,U+F016-F017,U+F01A-F01B,U+F01D,U+F022,U+F03E,U+F044,U+F046,U+F05C-F05D,U+F06E,U+F070,U+F087-F088,U+F08A,U+F094,U+F096-F097,U+F09D,U+F0A0,U+F0A2,U+F0A4-F0A7,U+F0C5,U+F0C7,U+F0E5-F0E6,U+F0EB,U+F0F6-F0F8,U+F10C,U+F114-F115,U+F118-F11A,U+F11C-F11D,U+F133,U+F147,U+F14E,U+F150-F152,U+F185-F186,U+F18E,U+F190-F192,U+F196,U+F1C1-F1C9,U+F1D9,U+F1DB,U+F1E3,U+F1EA,U+F1F7,U+F1F9,U+F20A,U+F247-F248,U+F24A,U+F24D,U+F255-F25B,U+F25D,U+F271-F274,U+F278,U+F27B,U+F28C,U+F28E,U+F29C,U+F2B5,U+F2B7,U+F2BA,U+F2BC,U+F2BE,U+F2C0-F2C1,U+F2C3,U+F2D0,U+F2D2,U+F2D4,U+F2DC; } + +@font-face { + font-family: "FontAwesome"; + font-display: block; + src: url("1e21o67/fa-v4compatibility.woff2") format("woff2"), url("1e21o67/fa-v4compatibility.ttf") format("truetype"); + unicode-range: U+F041,U+F047,U+F065-F066,U+F07D-F07E,U+F080,U+F08B,U+F08E,U+F090,U+F09A,U+F0AC,U+F0AE,U+F0B2,U+F0D0,U+F0D6,U+F0E4,U+F0EC,U+F10A-F10B,U+F123,U+F13E,U+F148-F149,U+F14C,U+F156,U+F15E,U+F160-F161,U+F163,U+F175-F178,U+F195,U+F1F8,U+F219,U+F250,U+F252,U+F27A; } diff --git a/pr-preview/pr-51/site_libs/quarto-contrib/fontawesome6-0.1.0/latex-fontsize.css b/pr-preview/pr-51/site_libs/quarto-contrib/fontawesome6-0.1.0/latex-fontsize.css new file mode 100644 index 00000000..45545ecf --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-contrib/fontawesome6-0.1.0/latex-fontsize.css @@ -0,0 +1,30 @@ +.fa-tiny { + font-size: 0.5em; +} +.fa-scriptsize { + font-size: 0.7em; +} +.fa-footnotesize { + font-size: 0.8em; +} +.fa-small { + font-size: 0.9em; +} +.fa-normalsize { + font-size: 1em; +} +.fa-large { + font-size: 1.2em; +} +.fa-Large { + font-size: 1.5em; +} +.fa-LARGE { + font-size: 1.75em; +} +.fa-huge { + font-size: 2em; +} +.fa-Huge { + font-size: 2.5em; +} diff --git a/pr-preview/pr-51/site_libs/quarto-diagram/mermaid-init.js b/pr-preview/pr-51/site_libs/quarto-diagram/mermaid-init.js new file mode 100644 index 00000000..42129b4e --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-diagram/mermaid-init.js @@ -0,0 +1,266 @@ +// mermaid-init.js +// Initializes the quarto-mermaid JS runtime +// +// Copyright (C) 2022 Posit Software, PBC + +/** + * String.prototype.replaceAll() polyfill + * https://gomakethings.com/how-to-replace-a-section-of-a-string-with-another-one-with-vanilla-js/ + * @author Chris Ferdinandi + * @license MIT + */ +if (!String.prototype.replaceAll) { + String.prototype.replaceAll = function (str, newStr) { + // If a regex pattern + if ( + Object.prototype.toString.call(str).toLowerCase() === "[object regexp]" + ) { + return this.replace(str, newStr); + } + + // If a string + return this.replace(new RegExp(str, "g"), newStr); + }; +} + +const mermaidOpts = { + startOnLoad: false, +}; +// this CSS is adapted from +// mkdocs-material +// Copyright (c) 2016-2022 Martin Donath + +const defaultCSS = + '.label text {fill: var(--mermaid-fg-color);}.node circle, .node ellipse, .node path, .node polygon, .node rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}marker {fill: var(--mermaid-edge-color) !important;}.edgeLabel .label rect {fill: #0000;}.label {color: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.label foreignObject {line-height: normal;overflow: visible;}.label div .edgeLabel {color: var(--mermaid-label-fg-color);}.edgeLabel, .edgeLabel rect, .label div .edgeLabel {background-color: var(--mermaid-label-bg-color);}.edgeLabel, .edgeLabel rect {fill: var(--mermaid-label-bg-color);color: var(--mermaid-edge-color);}.edgePath .path, .flowchart-link {stroke: var(--mermaid-edge-color);}.edgePath .arrowheadPath {fill: var(--mermaid-edge-color);stroke: none;}.cluster rect {fill: var(--mermaid-fg-color--lightest);stroke: var(--mermaid-fg-color--lighter);}.cluster span {color: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}defs #flowchart-circleEnd, defs #flowchart-circleStart, defs #flowchart-crossEnd, defs #flowchart-crossStart, defs #flowchart-pointEnd, defs #flowchart-pointStart {stroke: none;}g.classGroup line, g.classGroup rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}g.classGroup text {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.classLabel .box {fill: var(--mermaid-label-bg-color);background-color: var(--mermaid-label-bg-color);opacity: 1;}.classLabel .label {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.node .divider {stroke: var(--mermaid-node-fg-color);}.relation {stroke: var(--mermaid-edge-color);}.cardinality {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.cardinality text {fill: inherit !important;}defs #classDiagram-compositionEnd, defs #classDiagram-compositionStart, defs #classDiagram-dependencyEnd, defs #classDiagram-dependencyStart, defs #classDiagram-extensionEnd, defs #classDiagram-extensionStart {fill: var(--mermaid-edge-color) !important;stroke: var(--mermaid-edge-color) !important;}defs #classDiagram-aggregationEnd, defs #classDiagram-aggregationStart {fill: var(--mermaid-label-bg-color) !important;stroke: var(--mermaid-edge-color) !important;}g.stateGroup rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}g.stateGroup .state-title {fill: var(--mermaid-label-fg-color) !important;font-family: var(--mermaid-font-family);}g.stateGroup .composit {fill: var(--mermaid-label-bg-color);}.nodeLabel {color: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.node circle.state-end, .node circle.state-start, .start-state {fill: var(--mermaid-edge-color);stroke: none;}.end-state-inner, .end-state-outer {fill: var(--mermaid-edge-color);}.end-state-inner, .node circle.state-end {stroke: var(--mermaid-label-bg-color);}.transition {stroke: var(--mermaid-edge-color);}[id^="state-fork"] rect, [id^="state-join"] rect {fill: var(--mermaid-edge-color) !important;stroke: none !important;}.statediagram-cluster.statediagram-cluster .inner {fill: var(--mermaid-bg-color);}.statediagram-cluster rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}.statediagram-state rect.divider {fill: var(--mermaid-fg-color--lightest);stroke: var(--mermaid-fg-color--lighter);}defs #statediagram-barbEnd {stroke: var(--mermaid-edge-color);}.entityBox {fill: var(--mermaid-label-bg-color);stroke: var(--mermaid-node-fg-color);}.entityLabel {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.relationshipLabelBox {fill: var(--mermaid-label-bg-color);fill-opacity: 1;background-color: var(--mermaid-label-bg-color);opacity: 1;}.relationshipLabel {fill: var(--mermaid-label-fg-color);}.relationshipLine {stroke: var(--mermaid-edge-color);}defs #ONE_OR_MORE_END *, defs #ONE_OR_MORE_START *, defs #ONLY_ONE_END *, defs #ONLY_ONE_START *, defs #ZERO_OR_MORE_END *, defs #ZERO_OR_MORE_START *, defs #ZERO_OR_ONE_END *, defs #ZERO_OR_ONE_START * {stroke: var(--mermaid-edge-color) !important;}.actor, defs #ZERO_OR_MORE_END circle, defs #ZERO_OR_MORE_START circle {fill: var(--mermaid-label-bg-color);}.actor {stroke: var(--mermaid-node-fg-color);}text.actor > tspan {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}line {stroke: var(--mermaid-fg-color--lighter);}.messageLine0, .messageLine1 {stroke: var(--mermaid-edge-color);}.loopText > tspan, .messageText, .noteText > tspan {fill: var(--mermaid-edge-color);stroke: none;font-family: var(--mermaid-font-family) !important;}.noteText > tspan {fill: #000;}#arrowhead path {fill: var(--mermaid-edge-color);stroke: none;}.loopLine {stroke: var(--mermaid-node-fg-color);}.labelBox, .loopLine {fill: var(--mermaid-node-bg-color);}.labelBox {stroke: none;}.labelText, .labelText > span {fill: var(--mermaid-node-fg-color);font-family: var(--mermaid-font-family);}'; + +const mermaidThemeEl = document.querySelector('meta[name="mermaid-theme"]'); +if (mermaidThemeEl) { + mermaidOpts.theme = mermaidThemeEl.content; +} else { + mermaidOpts.themeCSS = defaultCSS; +} + +mermaid.initialize(mermaidOpts); + +const _quartoMermaid = { + // NB: there's effectively a copy of this function + // in `core/svg.ts`. + // if you change something here, you must keep it consistent there as well. + setSvgSize(svg) { + const { widthInPoints, heightInPoints, explicitHeight, explicitWidth } = + this.resolveSize(svg); + + if (explicitWidth && explicitHeight) { + svg.setAttribute("width", widthInPoints); + svg.setAttribute("height", heightInPoints); + svg.style.maxWidth = null; // remove mermaid's default max-width + } else { + if (explicitWidth) { + svg.style.maxWidth = `${widthInPoints}px`; + } + if (explicitHeight) { + svg.style.maxHeight = `${heightInPoints}px`; + } + } + }, + + // NB: there's effectively a copy of this function + // in `core/svg.ts`. + // if you change something here, you must keep it consistent there as well. + makeResponsive(svg) { + const width = svg.getAttribute("width"); + if (width === null) { + throw new Error("Couldn't find SVG width"); + } + const numWidth = Number(width.slice(0, -2)); + + if (numWidth > 650) { + changed = true; + svg.setAttribute("width", "100%"); + svg.removeAttribute("height"); + } + }, + + // NB: there's effectively a copy of this function + // in `core/svg.ts`. + // if you change something here, you must keep it consistent there as well. + fixupAlignment(svg, align) { + let style = svg.getAttribute("style") || ""; + + switch (align) { + case "left": + style = `${style}; display: block; margin: auto auto auto 0`; + break; + case "right": + style = `${style}; display: block; margin: auto 0 auto auto`; + break; + case "center": + style = `${style}; display: block; margin: auto auto auto auto`; + break; + } + svg.setAttribute("style", style); + }, + + resolveOptions(svgEl) { + return svgEl.parentElement.parentElement.parentElement.parentElement + .dataset; + }, + + // NB: there's effectively a copy of this function + // in our mermaid runtime in `core/svg.ts`. + // if you change something here, you must keep it consistent there as well. + resolveSize(svgEl) { + const inInches = (size) => { + if (size.endsWith("in")) { + return Number(size.slice(0, -2)); + } + if (size.endsWith("pt") || size.endsWith("px")) { + // assume 96 dpi for now + return Number(size.slice(0, -2)) / 96; + } + return Number(size); + }; + + // these are figWidth and figHeight on purpose, + // because data attributes are translated to camelCase by the DOM API + const kFigWidth = "figWidth", + kFigHeight = "figHeight"; + const options = this.resolveOptions(svgEl); + const width = svgEl.getAttribute("width"); + const height = svgEl.getAttribute("height"); + if (!width || !height) { + // attempt to resolve figure dimensions via viewBox + throw new Error("Internal error: couldn't find figure dimensions"); + } + const getViewBox = () => { + const vb = svgEl.attributes.getNamedItem("viewBox").value; // do it the roundabout way so that viewBox isn't dropped by deno_dom and text/html + if (!vb) return undefined; + const lst = vb.trim().split(" ").map(Number); + if (lst.length !== 4) return undefined; + if (lst.some(isNaN)) return undefined; + return lst; + }; + + let svgWidthInInches, svgHeightInInches; + + if ( + (width.slice(0, -2) === "pt" && height.slice(0, -2) === "pt") || + (width.slice(0, -2) === "px" && height.slice(0, -2) === "px") || + (!isNaN(Number(width)) && !isNaN(Number(height))) + ) { + // we assume 96 dpi which is generally what seems to be used. + svgWidthInInches = Number(width.slice(0, -2)) / 96; + svgHeightInInches = Number(height.slice(0, -2)) / 96; + } + const viewBox = getViewBox(); + if (viewBox !== undefined) { + // assume width and height come from viewbox. + const [_mx, _my, vbWidth, vbHeight] = viewBox; + svgWidthInInches = vbWidth / 96; + svgHeightInInches = vbHeight / 96; + } else { + throw new Error( + "Internal Error: Couldn't resolve width and height of SVG" + ); + } + const svgWidthOverHeight = svgWidthInInches / svgHeightInInches; + let widthInInches, heightInInches; + + if (options[kFigWidth] && options[kFigHeight]) { + // both were prescribed, so just go with them + widthInInches = inInches(String(options[kFigWidth])); + heightInInches = inInches(String(options[kFigHeight])); + } else if (options[kFigWidth]) { + // we were only given width, use that and adjust height based on aspect ratio; + widthInInches = inInches(String(options[kFigWidth])); + heightInInches = widthInInches / svgWidthOverHeight; + } else if (options[kFigHeight]) { + // we were only given height, use that and adjust width based on aspect ratio; + heightInInches = inInches(String(options[kFigHeight])); + widthInInches = heightInInches * svgWidthOverHeight; + } else { + // we were not given either, use svg's prescribed height + heightInInches = svgHeightInInches; + widthInInches = svgWidthInInches; + } + + return { + widthInInches, + heightInInches, + widthInPoints: Math.round(widthInInches * 96), + heightInPoints: Math.round(heightInInches * 96), + explicitWidth: options?.[kFigWidth] !== undefined, + explicitHeight: options?.[kFigHeight] !== undefined, + }; + }, + + postProcess(svg) { + const options = this.resolveOptions(svg); + if ( + options.responsive && + options["figWidth"] === undefined && + options["figHeight"] === undefined + ) { + this.makeResponsive(svg); + } else { + this.setSvgSize(svg); + } + if (options["reveal"]) { + this.fixupAlignment(svg, options["figAlign"] || "center"); + } + + // forward align attributes to the correct parent dif + // so that the svg figure is aligned correctly + const div = svg.parentElement.parentElement.parentElement; + const align = div.parentElement.parentElement.dataset.layoutAlign; + if (align) { + div.classList.remove("quarto-figure-left"); + div.classList.remove("quarto-figure-center"); + div.classList.remove("quarto-figure-right"); + div.classList.add(`quarto-figure-${align}`); + } + }, +}; + +// deno-lint-ignore no-window-prefix +window.addEventListener( + "load", + async function () { + let i = 0; + // we need pre because of whitespace preservation + for (const el of Array.from(document.querySelectorAll("pre.mermaid-js"))) { + //   doesn't appear to be treated as whitespace by mermaid + // so we replace it with a space. + const text = el.innerText.replaceAll(" ", " "); + const { svg: output } = await mermaid.mermaidAPI.render( + `mermaid-${++i}`, + text, + el + ); + el.innerHTML = output; + if (el.dataset.label) { + // patch mermaid's emitted style + const svg = el.firstChild; + const style = svg.querySelector("style"); + style.innerHTML = style.innerHTML.replaceAll( + `#${svg.id}`, + `#${el.dataset.label}` + ); + svg.id = el.dataset.label; + delete el.dataset.label; + } + + const svg = el.querySelector("svg"); + const parent = el.parentElement; + parent.removeChild(el); + parent.appendChild(svg); + svg.classList.add("mermaid-js"); + } + for (const svgEl of Array.from( + document.querySelectorAll("svg.mermaid-js") + )) { + _quartoMermaid.postProcess(svgEl); + } + }, + false +); diff --git a/pr-preview/pr-51/site_libs/quarto-diagram/mermaid.css b/pr-preview/pr-51/site_libs/quarto-diagram/mermaid.css new file mode 100644 index 00000000..9f8bb7c7 --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-diagram/mermaid.css @@ -0,0 +1,13 @@ +.mermaidTooltip { + position: absolute; + text-align: center; + max-width: 200px; + padding: 2px; + font-family: "trebuchet ms", verdana, arial; + font-size: 12px; + background: #ffffde; + border: 1px solid #aaaa33; + border-radius: 2px; + pointer-events: none; + z-index: 1000; +} diff --git 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i>.03928?Math.pow((a+.055)/1.055,2.4):a/12.92},hue2rgb:(i,a,f)=>(f<0&&(f+=1),f>1&&(f-=1),f<1/6?i+(a-i)*6*f:f<1/2?a:f<2/3?i+(a-i)*(2/3-f)*6:i),hsl2rgb:({h:i,s:a,l:f},p)=>{if(!a)return f*2.55;i/=360,a/=100,f/=100;const w=f<.5?f*(1+a):f+a-f*a,y=2*f-w;switch(p){case"r":return eW.hue2rgb(y,w,i+1/3)*255;case"g":return eW.hue2rgb(y,w,i)*255;case"b":return eW.hue2rgb(y,w,i-1/3)*255}},rgb2hsl:({r:i,g:a,b:f},p)=>{i/=255,a/=255,f/=255;const w=Math.max(i,a,f),y=Math.min(i,a,f),b=(w+y)/2;if(p==="l")return b*100;if(w===y)return 0;const E=w-y,S=b>.5?E/(2-w-y):E/(w+y);if(p==="s")return S*100;switch(w){case i:return((a-f)/E+(aa>f?Math.min(a,Math.max(f,i)):Math.min(f,Math.max(a,i)),round:i=>Math.round(i*1e10)/1e10},unit:{dec2hex:i=>{const a=Math.round(i).toString(16);return a.length>1?a:`0${a}`}}},Xk={};for(let i=0;i<=255;i++)Xk[i]=Na.unit.dec2hex(i);const y0={ALL:0,RGB:1,HSL:2};class r9t{constructor(){this.type=y0.ALL}get(){return this.type}set(a){if(this.type&&this.type!==a)throw new Error("Cannot change both RGB and HSL channels at the same time");this.type=a}reset(){this.type=y0.ALL}is(a){return this.type===a}}const i9t=r9t;class s9t{constructor(a,f){this.color=f,this.changed=!1,this.data=a,this.type=new i9t}set(a,f){return this.color=f,this.changed=!1,this.data=a,this.type.type=y0.ALL,this}_ensureHSL(){const a=this.data,{h:f,s:p,l:w}=a;f===void 0&&(a.h=Na.channel.rgb2hsl(a,"h")),p===void 0&&(a.s=Na.channel.rgb2hsl(a,"s")),w===void 0&&(a.l=Na.channel.rgb2hsl(a,"l"))}_ensureRGB(){const a=this.data,{r:f,g:p,b:w}=a;f===void 0&&(a.r=Na.channel.hsl2rgb(a,"r")),p===void 0&&(a.g=Na.channel.hsl2rgb(a,"g")),w===void 0&&(a.b=Na.channel.hsl2rgb(a,"b"))}get r(){const a=this.data,f=a.r;return!this.type.is(y0.HSL)&&f!==void 0?f:(this._ensureHSL(),Na.channel.hsl2rgb(a,"r"))}get g(){const a=this.data,f=a.g;return!this.type.is(y0.HSL)&&f!==void 0?f:(this._ensureHSL(),Na.channel.hsl2rgb(a,"g"))}get b(){const a=this.data,f=a.b;return!this.type.is(y0.HSL)&&f!==void 0?f:(this._ensureHSL(),Na.channel.hsl2rgb(a,"b"))}get h(){const a=this.data,f=a.h;return!this.type.is(y0.RGB)&&f!==void 0?f:(this._ensureRGB(),Na.channel.rgb2hsl(a,"h"))}get s(){const a=this.data,f=a.s;return!this.type.is(y0.RGB)&&f!==void 0?f:(this._ensureRGB(),Na.channel.rgb2hsl(a,"s"))}get l(){const a=this.data,f=a.l;return!this.type.is(y0.RGB)&&f!==void 0?f:(this._ensureRGB(),Na.channel.rgb2hsl(a,"l"))}get a(){return this.data.a}set r(a){this.type.set(y0.RGB),this.changed=!0,this.data.r=a}set g(a){this.type.set(y0.RGB),this.changed=!0,this.data.g=a}set b(a){this.type.set(y0.RGB),this.changed=!0,this.data.b=a}set h(a){this.type.set(y0.HSL),this.changed=!0,this.data.h=a}set s(a){this.type.set(y0.HSL),this.changed=!0,this.data.s=a}set l(a){this.type.set(y0.HSL),this.changed=!0,this.data.l=a}set a(a){this.changed=!0,this.data.a=a}}const a9t=s9t,tW=new a9t({r:0,g:0,b:0,a:0},"transparent"),jDe={re:/^#((?:[a-f0-9]{2}){2,4}|[a-f0-9]{3})$/i,parse:i=>{if(i.charCodeAt(0)!==35)return;const a=i.match(jDe.re);if(!a)return;const f=a[1],p=parseInt(f,16),w=f.length,y=w%4===0,b=w>4,E=b?1:17,S=b?8:4,N=y?0:-1,B=b?255:15;return tW.set({r:(p>>S*(N+3)&B)*E,g:(p>>S*(N+2)&B)*E,b:(p>>S*(N+1)&B)*E,a:y?(p&B)*E/255:1},i)},stringify:i=>{const{r:a,g:f,b:p,a:w}=i;return w<1?`#${Xk[Math.round(a)]}${Xk[Math.round(f)]}${Xk[Math.round(p)]}${Xk[Math.round(w*255)]}`:`#${Xk[Math.round(a)]}${Xk[Math.round(f)]}${Xk[Math.round(p)]}`}},jN=jDe,nW={re:/^hsla?\(\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?(?:deg|grad|rad|turn)?)\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?%)\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?%)(?:\s*?(?:,|\/)\s*?\+?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e-?\d+)?(%)?))?\s*?\)$/i,hueRe:/^(.+?)(deg|grad|rad|turn)$/i,_hue2deg:i=>{const a=i.match(nW.hueRe);if(a){const[,f,p]=a;switch(p){case"grad":return Na.channel.clamp.h(parseFloat(f)*.9);case"rad":return Na.channel.clamp.h(parseFloat(f)*180/Math.PI);case"turn":return Na.channel.clamp.h(parseFloat(f)*360)}}return Na.channel.clamp.h(parseFloat(i))},parse:i=>{const a=i.charCodeAt(0);if(a!==104&&a!==72)return;const f=i.match(nW.re);if(!f)return;const[,p,w,y,b,E]=f;return tW.set({h:nW._hue2deg(p),s:Na.channel.clamp.s(parseFloat(w)),l:Na.channel.clamp.l(parseFloat(y)),a:b?Na.channel.clamp.a(E?parseFloat(b)/100:parseFloat(b)):1},i)},stringify:i=>{const{h:a,s:f,l:p,a:w}=i;return w<1?`hsla(${Na.lang.round(a)}, ${Na.lang.round(f)}%, ${Na.lang.round(p)}%, ${w})`:`hsl(${Na.lang.round(a)}, ${Na.lang.round(f)}%, ${Na.lang.round(p)}%)`}},rW=nW,iW={colors:{aliceblue:"#f0f8ff",antiquewhite:"#faebd7",aqua:"#00ffff",aquamarine:"#7fffd4",azure:"#f0ffff",beige:"#f5f5dc",bisque:"#ffe4c4",black:"#000000",blanchedalmond:"#ffebcd",blue:"#0000ff",blueviolet:"#8a2be2",brown:"#a52a2a",burlywood:"#deb887",cadetblue:"#5f9ea0",chartreuse:"#7fff00",chocolate:"#d2691e",coral:"#ff7f50",cornflowerblue:"#6495ed",cornsilk:"#fff8dc",crimson:"#dc143c",cyanaqua:"#00ffff",darkblue:"#00008b",darkcyan:"#008b8b",darkgoldenrod:"#b8860b",darkgray:"#a9a9a9",darkgreen:"#006400",darkgrey:"#a9a9a9",darkkhaki:"#bdb76b",darkmagenta:"#8b008b",darkolivegreen:"#556b2f",darkorange:"#ff8c00",darkorchid:"#9932cc",darkred:"#8b0000",darksalmon:"#e9967a",darkseagreen:"#8fbc8f",darkslateblue:"#483d8b",darkslategray:"#2f4f4f",darkslategrey:"#2f4f4f",darkturquoise:"#00ced1",darkviolet:"#9400d3",deeppink:"#ff1493",deepskyblue:"#00bfff",dimgray:"#696969",dimgrey:"#696969",dodgerblue:"#1e90ff",firebrick:"#b22222",floralwhite:"#fffaf0",forestgreen:"#228b22",fuchsia:"#ff00ff",gainsboro:"#dcdcdc",ghostwhite:"#f8f8ff",gold:"#ffd700",goldenrod:"#daa520",gray:"#808080",green:"#008000",greenyellow:"#adff2f",grey:"#808080",honeydew:"#f0fff0",hotpink:"#ff69b4",indianred:"#cd5c5c",indigo:"#4b0082",ivory:"#fffff0",khaki:"#f0e68c",lavender:"#e6e6fa",lavenderblush:"#fff0f5",lawngreen:"#7cfc00",lemonchiffon:"#fffacd",lightblue:"#add8e6",lightcoral:"#f08080",lightcyan:"#e0ffff",lightgoldenrodyellow:"#fafad2",lightgray:"#d3d3d3",lightgreen:"#90ee90",lightgrey:"#d3d3d3",lightpink:"#ffb6c1",lightsalmon:"#ffa07a",lightseagreen:"#20b2aa",lightskyblue:"#87cefa",lightslategray:"#778899",lightslategrey:"#778899",lightsteelblue:"#b0c4de",lightyellow:"#ffffe0",lime:"#00ff00",limegreen:"#32cd32",linen:"#faf0e6",magenta:"#ff00ff",maroon:"#800000",mediumaquamarine:"#66cdaa",mediumblue:"#0000cd",mediumorchid:"#ba55d3",mediumpurple:"#9370db",mediumseagreen:"#3cb371",mediumslateblue:"#7b68ee",mediumspringgreen:"#00fa9a",mediumturquoise:"#48d1cc",mediumvioletred:"#c71585",midnightblue:"#191970",mintcream:"#f5fffa",mistyrose:"#ffe4e1",moccasin:"#ffe4b5",navajowhite:"#ffdead",navy:"#000080",oldlace:"#fdf5e6",olive:"#808000",olivedrab:"#6b8e23",orange:"#ffa500",orangered:"#ff4500",orchid:"#da70d6",palegoldenrod:"#eee8aa",palegreen:"#98fb98",paleturquoise:"#afeeee",palevioletred:"#db7093",papayawhip:"#ffefd5",peachpuff:"#ffdab9",peru:"#cd853f",pink:"#ffc0cb",plum:"#dda0dd",powderblue:"#b0e0e6",purple:"#800080",rebeccapurple:"#663399",red:"#ff0000",rosybrown:"#bc8f8f",royalblue:"#4169e1",saddlebrown:"#8b4513",salmon:"#fa8072",sandybrown:"#f4a460",seagreen:"#2e8b57",seashell:"#fff5ee",sienna:"#a0522d",silver:"#c0c0c0",skyblue:"#87ceeb",slateblue:"#6a5acd",slategray:"#708090",slategrey:"#708090",snow:"#fffafa",springgreen:"#00ff7f",tan:"#d2b48c",teal:"#008080",thistle:"#d8bfd8",transparent:"#00000000",turquoise:"#40e0d0",violet:"#ee82ee",wheat:"#f5deb3",white:"#ffffff",whitesmoke:"#f5f5f5",yellow:"#ffff00",yellowgreen:"#9acd32"},parse:i=>{i=i.toLowerCase();const a=iW.colors[i];if(a)return jN.parse(a)},stringify:i=>{const a=jN.stringify(i);for(const f in iW.colors)if(iW.colors[f]===a)return f}},$De=iW,HDe={re:/^rgba?\(\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?))\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?))\s*?(?:,|\s)\s*?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?))(?:\s*?(?:,|\/)\s*?\+?(-?(?:\d+(?:\.\d+)?|(?:\.\d+))(?:e\d+)?(%?)))?\s*?\)$/i,parse:i=>{const a=i.charCodeAt(0);if(a!==114&&a!==82)return;const f=i.match(HDe.re);if(!f)return;const[,p,w,y,b,E,S,N,B]=f;return tW.set({r:Na.channel.clamp.r(w?parseFloat(p)*2.55:parseFloat(p)),g:Na.channel.clamp.g(b?parseFloat(y)*2.55:parseFloat(y)),b:Na.channel.clamp.b(S?parseFloat(E)*2.55:parseFloat(E)),a:N?Na.channel.clamp.a(B?parseFloat(N)/100:parseFloat(N)):1},i)},stringify:i=>{const{r:a,g:f,b:p,a:w}=i;return w<1?`rgba(${Na.lang.round(a)}, ${Na.lang.round(f)}, ${Na.lang.round(p)}, ${Na.lang.round(w)})`:`rgb(${Na.lang.round(a)}, ${Na.lang.round(f)}, ${Na.lang.round(p)})`}},sW=HDe,r3={format:{keyword:$De,hex:jN,rgb:sW,rgba:sW,hsl:rW,hsla:rW},parse:i=>{if(typeof i!="string")return i;const a=jN.parse(i)||sW.parse(i)||rW.parse(i)||$De.parse(i);if(a)return a;throw new Error(`Unsupported color format: "${i}"`)},stringify:i=>!i.changed&&i.color?i.color:i.type.is(y0.HSL)||i.data.r===void 0?rW.stringify(i):i.a<1||!Number.isInteger(i.r)||!Number.isInteger(i.g)||!Number.isInteger(i.b)?sW.stringify(i):jN.stringify(i)},zDe=(i,a)=>{const f=r3.parse(i);for(const p in a)f[p]=Na.channel.clamp[p](a[p]);return r3.stringify(f)},$N=(i,a,f=0,p=1)=>{if(typeof i!="number")return zDe(i,{a});const w=tW.set({r:Na.channel.clamp.r(i),g:Na.channel.clamp.g(a),b:Na.channel.clamp.b(f),a:Na.channel.clamp.a(p)});return r3.stringify(w)},o9t=i=>{const{r:a,g:f,b:p}=r3.parse(i),w=.2126*Na.channel.toLinear(a)+.7152*Na.channel.toLinear(f)+.0722*Na.channel.toLinear(p);return Na.lang.round(w)},c9t=i=>o9t(i)>=.5,GDe=i=>!c9t(i),qDe=(i,a,f)=>{const 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sans-serif',this.fontSize="16px"}updateColors(){if(this.primaryTextColor=this.primaryTextColor||(this.darkMode?"#eee":"#333"),this.secondaryColor=this.secondaryColor||Gn(this.primaryColor,{h:-120}),this.tertiaryColor=this.tertiaryColor||Gn(this.primaryColor,{h:180,l:5}),this.primaryBorderColor=this.primaryBorderColor||ig(this.primaryColor,this.darkMode),this.secondaryBorderColor=this.secondaryBorderColor||ig(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=this.tertiaryBorderColor||ig(this.tertiaryColor,this.darkMode),this.noteBorderColor=this.noteBorderColor||ig(this.noteBkgColor,this.darkMode),this.noteBkgColor=this.noteBkgColor||"#fff5ad",this.noteTextColor=this.noteTextColor||"#333",this.secondaryTextColor=this.secondaryTextColor||Bi(this.secondaryColor),this.tertiaryTextColor=this.tertiaryTextColor||Bi(this.tertiaryColor),this.lineColor=this.lineColor||Bi(this.background),this.arrowheadColor=this.arrowheadColor||Bi(this.background),this.textColor=this.textColor||this.primaryTextColor,this.border2=this.border2||this.tertiaryBorderColor,this.nodeBkg=this.nodeBkg||this.primaryColor,this.mainBkg=this.mainBkg||this.primaryColor,this.nodeBorder=this.nodeBorder||this.primaryBorderColor,this.clusterBkg=this.clusterBkg||this.tertiaryColor,this.clusterBorder=this.clusterBorder||this.tertiaryBorderColor,this.defaultLinkColor=this.defaultLinkColor||this.lineColor,this.titleColor=this.titleColor||this.tertiaryTextColor,this.edgeLabelBackground=this.edgeLabelBackground||(this.darkMode?ya(this.secondaryColor,30):this.secondaryColor),this.nodeTextColor=this.nodeTextColor||this.primaryTextColor,this.actorBorder=this.actorBorder||this.primaryBorderColor,this.actorBkg=this.actorBkg||this.mainBkg,this.actorTextColor=this.actorTextColor||this.primaryTextColor,this.actorLineColor=this.actorLineColor||"grey",this.labelBoxBkgColor=this.labelBoxBkgColor||this.actorBkg,this.signalColor=this.signalColor||this.textColor,this.signalTextColor=this.signalTextColor||this.textColor,this.labelBoxBorderColor=this.labelBoxBorderColor||this.actorBorder,this.labelTextColor=this.labelTextColor||this.actorTextColor,this.loopTextColor=this.loopTextColor||this.actorTextColor,this.activationBorderColor=this.activationBorderColor||ya(this.secondaryColor,10),this.activationBkgColor=this.activationBkgColor||this.secondaryColor,this.sequenceNumberColor=this.sequenceNumberColor||Bi(this.lineColor),this.sectionBkgColor=this.sectionBkgColor||this.tertiaryColor,this.altSectionBkgColor=this.altSectionBkgColor||"white",this.sectionBkgColor=this.sectionBkgColor||this.secondaryColor,this.sectionBkgColor2=this.sectionBkgColor2||this.primaryColor,this.excludeBkgColor=this.excludeBkgColor||"#eeeeee",this.taskBorderColor=this.taskBorderColor||this.primaryBorderColor,this.taskBkgColor=this.taskBkgColor||this.primaryColor,this.activeTaskBorderColor=this.activeTaskBorderColor||this.primaryColor,this.activeTaskBkgColor=this.activeTaskBkgColor||Qs(this.primaryColor,23),this.gridColor=this.gridColor||"lightgrey",this.doneTaskBkgColor=this.doneTaskBkgColor||"lightgrey",this.doneTaskBorderColor=this.doneTaskBorderColor||"grey",this.critBorderColor=this.critBorderColor||"#ff8888",this.critBkgColor=this.critBkgColor||"red",this.todayLineColor=this.todayLineColor||"red",this.taskTextColor=this.taskTextColor||this.textColor,this.taskTextOutsideColor=this.taskTextOutsideColor||this.textColor,this.taskTextLightColor=this.taskTextLightColor||this.textColor,this.taskTextColor=this.taskTextColor||this.primaryTextColor,this.taskTextDarkColor=this.taskTextDarkColor||this.textColor,this.taskTextClickableColor=this.taskTextClickableColor||"#003163",this.personBorder=this.personBorder||this.primaryBorderColor,this.personBkg=this.personBkg||this.mainBkg,this.transitionColor=this.transitionColor||this.lineColor,this.transitionLabelColor=this.transitionLabelColor||this.textColor,this.stateLabelColor=this.stateLabelColor||this.stateBkg||this.primaryTextColor,this.stateBkg=this.stateBkg||this.mainBkg,this.labelBackgroundColor=this.labelBackgroundColor||this.stateBkg,this.compositeBackground=this.compositeBackground||this.background||this.tertiaryColor,this.altBackground=this.altBackground||this.tertiaryColor,this.compositeTitleBackground=this.compositeTitleBackground||this.mainBkg,this.compositeBorder=this.compositeBorder||this.nodeBorder,this.innerEndBackground=this.nodeBorder,this.errorBkgColor=this.errorBkgColor||this.tertiaryColor,this.errorTextColor=this.errorTextColor||this.tertiaryTextColor,this.transitionColor=this.transitionColor||this.lineColor,this.specialStateColor=this.lineColor,this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||Gn(this.primaryColor,{h:30}),this.cScale4=this.cScale4||Gn(this.primaryColor,{h:60}),this.cScale5=this.cScale5||Gn(this.primaryColor,{h:90}),this.cScale6=this.cScale6||Gn(this.primaryColor,{h:120}),this.cScale7=this.cScale7||Gn(this.primaryColor,{h:150}),this.cScale8=this.cScale8||Gn(this.primaryColor,{h:210,l:150}),this.cScale9=this.cScale9||Gn(this.primaryColor,{h:270}),this.cScale10=this.cScale10||Gn(this.primaryColor,{h:300}),this.cScale11=this.cScale11||Gn(this.primaryColor,{h:330}),this.darkMode)for(let f=0;f{this[p]=a[p]}),this.updateColors(),f.forEach(p=>{this[p]=a[p]})}};const h9t=i=>{const a=new l9t;return a.calculate(i),a};let f9t=class{constructor(){this.background="#333",this.primaryColor="#1f2020",this.secondaryColor=Qs(this.primaryColor,16),this.tertiaryColor=Gn(this.primaryColor,{h:-160}),this.primaryBorderColor=Bi(this.background),this.secondaryBorderColor=ig(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=ig(this.tertiaryColor,this.darkMode),this.primaryTextColor=Bi(this.primaryColor),this.secondaryTextColor=Bi(this.secondaryColor),this.tertiaryTextColor=Bi(this.tertiaryColor),this.lineColor=Bi(this.background),this.textColor=Bi(this.background),this.mainBkg="#1f2020",this.secondBkg="calculated",this.mainContrastColor="lightgrey",this.darkTextColor=Qs(Bi("#323D47"),10),this.lineColor="calculated",this.border1="#81B1DB",this.border2=$N(255,255,255,.25),this.arrowheadColor="calculated",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.labelBackground="#181818",this.textColor="#ccc",this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="#F9FFFE",this.edgeLabelBackground="calculated",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="calculated",this.actorLineColor="calculated",this.signalColor="calculated",this.signalTextColor="calculated",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="calculated",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="#fff5ad",this.noteTextColor="calculated",this.activationBorderColor="calculated",this.activationBkgColor="calculated",this.sequenceNumberColor="black",this.sectionBkgColor=ya("#EAE8D9",30),this.altSectionBkgColor="calculated",this.sectionBkgColor2="#EAE8D9",this.excludeBkgColor=ya(this.sectionBkgColor,10),this.taskBorderColor=$N(255,255,255,70),this.taskBkgColor="calculated",this.taskTextColor="calculated",this.taskTextLightColor="calculated",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor=$N(255,255,255,50),this.activeTaskBkgColor="#81B1DB",this.gridColor="calculated",this.doneTaskBkgColor="calculated",this.doneTaskBorderColor="grey",this.critBorderColor="#E83737",this.critBkgColor="#E83737",this.taskTextDarkColor="calculated",this.todayLineColor="#DB5757",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.labelColor="calculated",this.errorBkgColor="#a44141",this.errorTextColor="#ddd"}updateColors(){this.secondBkg=Qs(this.mainBkg,16),this.lineColor=this.mainContrastColor,this.arrowheadColor=this.mainContrastColor,this.nodeBkg=this.mainBkg,this.nodeBorder=this.border1,this.clusterBkg=this.secondBkg,this.clusterBorder=this.border2,this.defaultLinkColor=this.lineColor,this.edgeLabelBackground=Qs(this.labelBackground,25),this.actorBorder=this.border1,this.actorBkg=this.mainBkg,this.actorTextColor=this.mainContrastColor,this.actorLineColor=this.mainContrastColor,this.signalColor=this.mainContrastColor,this.signalTextColor=this.mainContrastColor,this.labelBoxBkgColor=this.actorBkg,this.labelBoxBorderColor=this.actorBorder,this.labelTextColor=this.mainContrastColor,this.loopTextColor=this.mainContrastColor,this.noteBorderColor=this.secondaryBorderColor,this.noteBkgColor=this.secondBkg,this.noteTextColor=this.secondaryTextColor,this.activationBorderColor=this.border1,this.activationBkgColor=this.secondBkg,this.altSectionBkgColor=this.background,this.taskBkgColor=Qs(this.mainBkg,23),this.taskTextColor=this.darkTextColor,this.taskTextLightColor=this.mainContrastColor,this.taskTextOutsideColor=this.taskTextLightColor,this.gridColor=this.mainContrastColor,this.doneTaskBkgColor=this.mainContrastColor,this.taskTextDarkColor=this.darkTextColor,this.transitionColor=this.transitionColor||this.lineColor,this.transitionLabelColor=this.transitionLabelColor||this.textColor,this.stateLabelColor=this.stateLabelColor||this.stateBkg||this.primaryTextColor,this.stateBkg=this.stateBkg||this.mainBkg,this.labelBackgroundColor=this.labelBackgroundColor||this.stateBkg,this.compositeBackground=this.compositeBackground||this.background||this.tertiaryColor,this.altBackground=this.altBackground||"#555",this.compositeTitleBackground=this.compositeTitleBackground||this.mainBkg,this.compositeBorder=this.compositeBorder||this.nodeBorder,this.innerEndBackground=this.primaryBorderColor,this.specialStateColor="#f4f4f4",this.errorBkgColor=this.errorBkgColor||this.tertiaryColor,this.errorTextColor=this.errorTextColor||this.tertiaryTextColor,this.fillType0=this.primaryColor,this.fillType1=this.secondaryColor,this.fillType2=Gn(this.primaryColor,{h:64}),this.fillType3=Gn(this.secondaryColor,{h:64}),this.fillType4=Gn(this.primaryColor,{h:-64}),this.fillType5=Gn(this.secondaryColor,{h:-64}),this.fillType6=Gn(this.primaryColor,{h:128}),this.fillType7=Gn(this.secondaryColor,{h:128}),this.cScale1=this.cScale1||"#0b0000",this.cScale2=this.cScale2||"#4d1037",this.cScale3=this.cScale3||"#3f5258",this.cScale4=this.cScale4||"#4f2f1b",this.cScale5=this.cScale5||"#6e0a0a",this.cScale6=this.cScale6||"#3b0048",this.cScale7=this.cScale7||"#995a01",this.cScale8=this.cScale8||"#154706",this.cScale9=this.cScale9||"#161722",this.cScale10=this.cScale10||"#00296f",this.cScale11=this.cScale11||"#01629c",this.cScale12=this.cScale12||"#010029",this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||Gn(this.primaryColor,{h:30}),this.cScale4=this.cScale4||Gn(this.primaryColor,{h:60}),this.cScale5=this.cScale5||Gn(this.primaryColor,{h:90}),this.cScale6=this.cScale6||Gn(this.primaryColor,{h:120}),this.cScale7=this.cScale7||Gn(this.primaryColor,{h:150}),this.cScale8=this.cScale8||Gn(this.primaryColor,{h:210}),this.cScale9=this.cScale9||Gn(this.primaryColor,{h:270}),this.cScale10=this.cScale10||Gn(this.primaryColor,{h:300}),this.cScale11=this.cScale11||Gn(this.primaryColor,{h:330});for(let a=0;a{this[p]=a[p]}),this.updateColors(),f.forEach(p=>{this[p]=a[p]})}};const d9t=i=>{const a=new f9t;return a.calculate(i),a};let g9t=class{constructor(){this.background="#f4f4f4",this.primaryColor="#ECECFF",this.secondaryColor=Gn(this.primaryColor,{h:120}),this.secondaryColor="#ffffde",this.tertiaryColor=Gn(this.primaryColor,{h:-160}),this.primaryBorderColor=ig(this.primaryColor,this.darkMode),this.secondaryBorderColor=ig(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=ig(this.tertiaryColor,this.darkMode),this.primaryTextColor=Bi(this.primaryColor),this.secondaryTextColor=Bi(this.secondaryColor),this.tertiaryTextColor=Bi(this.tertiaryColor),this.lineColor=Bi(this.background),this.textColor=Bi(this.background),this.background="white",this.mainBkg="#ECECFF",this.secondBkg="#ffffde",this.lineColor="#333333",this.border1="#9370DB",this.border2="#aaaa33",this.arrowheadColor="#333333",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.labelBackground="#e8e8e8",this.textColor="#333",this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="calculated",this.edgeLabelBackground="calculated",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="black",this.actorLineColor="grey",this.signalColor="calculated",this.signalTextColor="calculated",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="calculated",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="#fff5ad",this.noteTextColor="calculated",this.activationBorderColor="#666",this.activationBkgColor="#f4f4f4",this.sequenceNumberColor="white",this.sectionBkgColor="calculated",this.altSectionBkgColor="calculated",this.sectionBkgColor2="calculated",this.excludeBkgColor="#eeeeee",this.taskBorderColor="calculated",this.taskBkgColor="calculated",this.taskTextLightColor="calculated",this.taskTextColor=this.taskTextLightColor,this.taskTextDarkColor="calculated",this.taskTextOutsideColor=this.taskTextDarkColor,this.taskTextClickableColor="calculated",this.activeTaskBorderColor="calculated",this.activeTaskBkgColor="calculated",this.gridColor="calculated",this.doneTaskBkgColor="calculated",this.doneTaskBorderColor="calculated",this.critBorderColor="calculated",this.critBkgColor="calculated",this.todayLineColor="calculated",this.sectionBkgColor=$N(102,102,255,.49),this.altSectionBkgColor="white",this.sectionBkgColor2="#fff400",this.taskBorderColor="#534fbc",this.taskBkgColor="#8a90dd",this.taskTextLightColor="white",this.taskTextColor="calculated",this.taskTextDarkColor="black",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor="#534fbc",this.activeTaskBkgColor="#bfc7ff",this.gridColor="lightgrey",this.doneTaskBkgColor="lightgrey",this.doneTaskBorderColor="grey",this.critBorderColor="#ff8888",this.critBkgColor="red",this.todayLineColor="red",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.labelColor="black",this.errorBkgColor="#552222",this.errorTextColor="#552222",this.updateColors()}updateColors(){this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||Gn(this.primaryColor,{h:30}),this.cScale4=this.cScale4||Gn(this.primaryColor,{h:60}),this.cScale5=this.cScale5||Gn(this.primaryColor,{h:90}),this.cScale6=this.cScale6||Gn(this.primaryColor,{h:120}),this.cScale7=this.cScale7||Gn(this.primaryColor,{h:150}),this.cScale8=this.cScale8||Gn(this.primaryColor,{h:210}),this.cScale9=this.cScale9||Gn(this.primaryColor,{h:270}),this.cScale10=this.cScale10||Gn(this.primaryColor,{h:300}),this.cScale11=this.cScale11||Gn(this.primaryColor,{h:330}),this["cScalePeer1"]=this["cScalePeer1"]||ya(this.secondaryColor,45),this["cScalePeer2"]=this["cScalePeer2"]||ya(this.tertiaryColor,40);for(let a=0;a{this[p]=a[p]}),this.updateColors(),f.forEach(p=>{this[p]=a[p]})}};const p9t=i=>{const a=new g9t;return a.calculate(i),a};let b9t=class{constructor(){this.background="#f4f4f4",this.primaryColor="#cde498",this.secondaryColor="#cdffb2",this.background="white",this.mainBkg="#cde498",this.secondBkg="#cdffb2",this.lineColor="green",this.border1="#13540c",this.border2="#6eaa49",this.arrowheadColor="green",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.tertiaryColor=Qs("#cde498",10),this.primaryBorderColor=ig(this.primaryColor,this.darkMode),this.secondaryBorderColor=ig(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=ig(this.tertiaryColor,this.darkMode),this.primaryTextColor=Bi(this.primaryColor),this.secondaryTextColor=Bi(this.secondaryColor),this.tertiaryTextColor=Bi(this.primaryColor),this.lineColor=Bi(this.background),this.textColor=Bi(this.background),this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="#333",this.edgeLabelBackground="#e8e8e8",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="black",this.actorLineColor="grey",this.signalColor="#333",this.signalTextColor="#333",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="#326932",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="#fff5ad",this.noteTextColor="calculated",this.activationBorderColor="#666",this.activationBkgColor="#f4f4f4",this.sequenceNumberColor="white",this.sectionBkgColor="#6eaa49",this.altSectionBkgColor="white",this.sectionBkgColor2="#6eaa49",this.excludeBkgColor="#eeeeee",this.taskBorderColor="calculated",this.taskBkgColor="#487e3a",this.taskTextLightColor="white",this.taskTextColor="calculated",this.taskTextDarkColor="black",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor="calculated",this.activeTaskBkgColor="calculated",this.gridColor="lightgrey",this.doneTaskBkgColor="lightgrey",this.doneTaskBorderColor="grey",this.critBorderColor="#ff8888",this.critBkgColor="red",this.todayLineColor="red",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.labelColor="black",this.errorBkgColor="#552222",this.errorTextColor="#552222"}updateColors(){this.actorBorder=ya(this.mainBkg,20),this.actorBkg=this.mainBkg,this.labelBoxBkgColor=this.actorBkg,this.labelTextColor=this.actorTextColor,this.loopTextColor=this.actorTextColor,this.noteBorderColor=this.border2,this.noteTextColor=this.actorTextColor,this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||Gn(this.primaryColor,{h:30}),this.cScale4=this.cScale4||Gn(this.primaryColor,{h:60}),this.cScale5=this.cScale5||Gn(this.primaryColor,{h:90}),this.cScale6=this.cScale6||Gn(this.primaryColor,{h:120}),this.cScale7=this.cScale7||Gn(this.primaryColor,{h:150}),this.cScale8=this.cScale8||Gn(this.primaryColor,{h:210}),this.cScale9=this.cScale9||Gn(this.primaryColor,{h:270}),this.cScale10=this.cScale10||Gn(this.primaryColor,{h:300}),this.cScale11=this.cScale11||Gn(this.primaryColor,{h:330}),this["cScalePeer1"]=this["cScalePeer1"]||ya(this.secondaryColor,45),this["cScalePeer2"]=this["cScalePeer2"]||ya(this.tertiaryColor,40);for(let a=0;a{this[p]=a[p]}),this.updateColors(),f.forEach(p=>{this[p]=a[p]})}};const v9t=i=>{const a=new b9t;return a.calculate(i),a};class w9t{constructor(){this.primaryColor="#eee",this.contrast="#707070",this.secondaryColor=Qs(this.contrast,55),this.background="#ffffff",this.tertiaryColor=Gn(this.primaryColor,{h:-160}),this.primaryBorderColor=ig(this.primaryColor,this.darkMode),this.secondaryBorderColor=ig(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=ig(this.tertiaryColor,this.darkMode),this.primaryTextColor=Bi(this.primaryColor),this.secondaryTextColor=Bi(this.secondaryColor),this.tertiaryTextColor=Bi(this.tertiaryColor),this.lineColor=Bi(this.background),this.textColor=Bi(this.background),this.mainBkg="#eee",this.secondBkg="calculated",this.lineColor="#666",this.border1="#999",this.border2="calculated",this.note="#ffa",this.text="#333",this.critical="#d42",this.done="#bbb",this.arrowheadColor="#333333",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="calculated",this.edgeLabelBackground="white",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="calculated",this.actorLineColor="calculated",this.signalColor="calculated",this.signalTextColor="calculated",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="calculated",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="calculated",this.noteTextColor="calculated",this.activationBorderColor="#666",this.activationBkgColor="#f4f4f4",this.sequenceNumberColor="white",this.sectionBkgColor="calculated",this.altSectionBkgColor="white",this.sectionBkgColor2="calculated",this.excludeBkgColor="#eeeeee",this.taskBorderColor="calculated",this.taskBkgColor="calculated",this.taskTextLightColor="white",this.taskTextColor="calculated",this.taskTextDarkColor="calculated",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor="calculated",this.activeTaskBkgColor="calculated",this.gridColor="calculated",this.doneTaskBkgColor="calculated",this.doneTaskBorderColor="calculated",this.critBkgColor="calculated",this.critBorderColor="calculated",this.todayLineColor="calculated",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.labelColor="black",this.errorBkgColor="#552222",this.errorTextColor="#552222"}updateColors(){this.secondBkg=Qs(this.contrast,55),this.border2=this.contrast,this.actorBorder=Qs(this.border1,23),this.actorBkg=this.mainBkg,this.actorTextColor=this.text,this.actorLineColor=this.lineColor,this.signalColor=this.text,this.signalTextColor=this.text,this.labelBoxBkgColor=this.actorBkg,this.labelBoxBorderColor=this.actorBorder,this.labelTextColor=this.text,this.loopTextColor=this.text,this.noteBorderColor="#999",this.noteBkgColor="#666",this.noteTextColor="#fff",this.cScale0=this.cScale0||"#555",this.cScale1=this.cScale1||"#F4F4F4",this.cScale2=this.cScale2||"#555",this.cScale3=this.cScale3||"#BBB",this.cScale4=this.cScale4||"#777",this.cScale5=this.cScale5||"#999",this.cScale6=this.cScale6||"#DDD",this.cScale7=this.cScale7||"#FFF",this.cScale8=this.cScale8||"#DDD",this.cScale9=this.cScale9||"#BBB",this.cScale10=this.cScale10||"#999",this.cScale11=this.cScale11||"#777";for(let a=0;a{this[p]=a[p]}),this.updateColors(),f.forEach(p=>{this[p]=a[p]})}}const g5={base:{getThemeVariables:h9t},dark:{getThemeVariables:d9t},default:{getThemeVariables:p9t},forest:{getThemeVariables:v9t},neutral:{getThemeVariables:i=>{const a=new w9t;return a.calculate(i),a}}},Qk={theme:"default",themeVariables:g5.default.getThemeVariables(),themeCSS:void 0,maxTextSize:5e4,darkMode:!1,fontFamily:'"trebuchet ms", verdana, arial, sans-serif;',logLevel:5,securityLevel:"strict",startOnLoad:!0,arrowMarkerAbsolute:!1,secure:["secure","securityLevel","startOnLoad","maxTextSize"],deterministicIds:!1,deterministicIDSeed:void 0,flowchart:{titleTopMargin:25,diagramPadding:8,htmlLabels:!0,nodeSpacing:50,rankSpacing:50,curve:"basis",padding:15,useMaxWidth:!0,defaultRenderer:"dagre-wrapper",wrappingWidth:200},sequence:{hideUnusedParticipants:!1,activationWidth:10,diagramMarginX:50,diagramMarginY:10,actorMargin:50,width:150,height:65,boxMargin:10,boxTextMargin:5,noteMargin:10,messageMargin:35,messageAlign:"center",mirrorActors:!0,forceMenus:!1,bottomMarginAdj:1,useMaxWidth:!0,rightAngles:!1,showSequenceNumbers:!1,actorFontSize:14,actorFontFamily:'"Open Sans", sans-serif',actorFontWeight:400,noteFontSize:14,noteFontFamily:'"trebuchet ms", verdana, arial, sans-serif',noteFontWeight:400,noteAlign:"center",messageFontSize:16,messageFontFamily:'"trebuchet ms", verdana, arial, sans-serif',messageFontWeight:400,wrap:!1,wrapPadding:10,labelBoxWidth:50,labelBoxHeight:20,messageFont:function(){return{fontFamily:this.messageFontFamily,fontSize:this.messageFontSize,fontWeight:this.messageFontWeight}},noteFont:function(){return{fontFamily:this.noteFontFamily,fontSize:this.noteFontSize,fontWeight:this.noteFontWeight}},actorFont:function(){return{fontFamily:this.actorFontFamily,fontSize:this.actorFontSize,fontWeight:this.actorFontWeight}}},gantt:{titleTopMargin:25,barHeight:20,barGap:4,topPadding:50,rightPadding:75,leftPadding:75,gridLineStartPadding:35,fontSize:11,sectionFontSize:11,numberSectionStyles:4,displayMode:"",axisFormat:"%Y-%m-%d",tickInterval:void 0,useMaxWidth:!0,topAxis:!1,useWidth:void 0},journey:{diagramMarginX:50,diagramMarginY:10,leftMargin:150,width:150,height:50,boxMargin:10,boxTextMargin:5,noteMargin:10,messageMargin:35,messageAlign:"center",bottomMarginAdj:1,useMaxWidth:!0,rightAngles:!1,taskFontSize:14,taskFontFamily:'"Open Sans", sans-serif',taskMargin:50,activationWidth:10,textPlacement:"fo",actorColours:["#8FBC8F","#7CFC00","#00FFFF","#20B2AA","#B0E0E6","#FFFFE0"],sectionFills:["#191970","#8B008B","#4B0082","#2F4F4F","#800000","#8B4513","#00008B"],sectionColours:["#fff"]},timeline:{diagramMarginX:50,diagramMarginY:10,leftMargin:150,width:150,height:50,boxMargin:10,boxTextMargin:5,noteMargin:10,messageMargin:35,messageAlign:"center",bottomMarginAdj:1,useMaxWidth:!0,rightAngles:!1,taskFontSize:14,taskFontFamily:'"Open Sans", sans-serif',taskMargin:50,activationWidth:10,textPlacement:"fo",actorColours:["#8FBC8F","#7CFC00","#00FFFF","#20B2AA","#B0E0E6","#FFFFE0"],sectionFills:["#191970","#8B008B","#4B0082","#2F4F4F","#800000","#8B4513","#00008B"],sectionColours:["#fff"],disableMulticolor:!1},class:{titleTopMargin:25,arrowMarkerAbsolute:!1,dividerMargin:10,padding:5,textHeight:10,useMaxWidth:!0,defaultRenderer:"dagre-wrapper"},state:{titleTopMargin:25,dividerMargin:10,sizeUnit:5,padding:8,textHeight:10,titleShift:-15,noteMargin:10,forkWidth:70,forkHeight:7,miniPadding:2,fontSizeFactor:5.02,fontSize:24,labelHeight:16,edgeLengthFactor:"20",compositTitleSize:35,radius:5,useMaxWidth:!0,defaultRenderer:"dagre-wrapper"},er:{titleTopMargin:25,diagramPadding:20,layoutDirection:"TB",minEntityWidth:100,minEntityHeight:75,entityPadding:15,stroke:"gray",fill:"honeydew",fontSize:12,useMaxWidth:!0},pie:{useWidth:void 0,useMaxWidth:!0,textPosition:.75},requirement:{useWidth:void 0,useMaxWidth:!0,rect_fill:"#f9f9f9",text_color:"#333",rect_border_size:"0.5px",rect_border_color:"#bbb",rect_min_width:200,rect_min_height:200,fontSize:14,rect_padding:10,line_height:20},gitGraph:{titleTopMargin:25,diagramPadding:8,nodeLabel:{width:75,height:100,x:-25,y:0},mainBranchName:"main",mainBranchOrder:0,showCommitLabel:!0,showBranches:!0,rotateCommitLabel:!0},c4:{useWidth:void 0,diagramMarginX:50,diagramMarginY:10,c4ShapeMargin:50,c4ShapePadding:20,width:216,height:60,boxMargin:10,useMaxWidth:!0,c4ShapeInRow:4,nextLinePaddingX:0,c4BoundaryInRow:2,personFontSize:14,personFontFamily:'"Open Sans", sans-serif',personFontWeight:"normal",external_personFontSize:14,external_personFontFamily:'"Open Sans", sans-serif',external_personFontWeight:"normal",systemFontSize:14,systemFontFamily:'"Open Sans", sans-serif',systemFontWeight:"normal",external_systemFontSize:14,external_systemFontFamily:'"Open Sans", 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Dr=new Error(Er);throw Dr.hash=br,Dr}},parse:function(Er){var br=this,Dr=[0],Vn=[],qi=[null],yn=[],Bc=this.table,jn="",Ms=0,Pa=0,Ta=2,_a=1,ka=yn.slice.call(arguments,1),Qi=Object.create(this.lexer),ea={yy:{}};for(var Ca in this.yy)Object.prototype.hasOwnProperty.call(this.yy,Ca)&&(ea.yy[Ca]=this.yy[Ca]);Qi.setInput(Er,ea.yy),ea.yy.lexer=Qi,ea.yy.parser=this,typeof Qi.yylloc>"u"&&(Qi.yylloc={});var Sa=Qi.yylloc;yn.push(Sa);var Ka=Qi.options&&Qi.options.ranges;typeof ea.yy.parseError=="function"?this.parseError=ea.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function cg(){var Ns;return Ns=Vn.pop()||Qi.lex()||_a,typeof Ns!="number"&&(Ns instanceof Array&&(Vn=Ns,Ns=Vn.pop()),Ns=br.symbols_[Ns]||Ns),Ns}for(var Gc,Dh,Es,lp,sd={},sh,Ai,nn,Tr;;){if(Dh=Dr[Dr.length-1],this.defaultActions[Dh]?Es=this.defaultActions[Dh]:((Gc===null||typeof Gc>"u")&&(Gc=cg()),Es=Bc[Dh]&&Bc[Dh][Gc]),typeof Es>"u"||!Es.length||!Es[0]){var ai="";Tr=[];for(sh in 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qi=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:Dr?(Dr.length===Vn.length?this.yylloc.first_column:0)+Vn[Vn.length-Dr.length].length-Dr[0].length:this.yylloc.first_column-br},this.options.ranges&&(this.yylloc.range=[qi[0],qi[0]+this.yyleng-br]),this.yyleng=this.yytext.length,this},more:function(){return this._more=!0,this},reject:function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true). +`+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},less:function(Er){this.unput(this.match.slice(Er))},pastInput:function(){var Er=this.matched.substr(0,this.matched.length-this.match.length);return(Er.length>20?"...":"")+Er.substr(-20).replace(/\n/g,"")},upcomingInput:function(){var Er=this.match;return Er.length<20&&(Er+=this._input.substr(0,20-Er.length)),(Er.substr(0,20)+(Er.length>20?"...":"")).replace(/\n/g,"")},showPosition:function(){var Er=this.pastInput(),br=new Array(Er.length+1).join("-");return Er+this.upcomingInput()+` +`+br+"^"},test_match:function(Er,br){var Dr,Vn,qi;if(this.options.backtrack_lexer&&(qi={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(qi.yylloc.range=this.yylloc.range.slice(0))),Vn=Er[0].match(/(?:\r\n?|\n).*/g),Vn&&(this.yylineno+=Vn.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:Vn?Vn[Vn.length-1].length-Vn[Vn.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+Er[0].length},this.yytext+=Er[0],this.match+=Er[0],this.matches=Er,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(Er[0].length),this.matched+=Er[0],Dr=this.performAction.call(this,this.yy,this,br,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),Dr)return Dr;if(this._backtrack){for(var yn in qi)this[yn]=qi[yn];return!1}return!1},next:function(){if(this.done)return this.EOF;this._input||(this.done=!0);var Er,br,Dr,Vn;this._more||(this.yytext="",this.match="");for(var qi=this._currentRules(),yn=0;ynbr[0].length)){if(br=Dr,Vn=yn,this.options.backtrack_lexer){if(Er=this.test_match(Dr,qi[yn]),Er!==!1)return Er;if(this._backtrack){br=!1;continue}else return!1}else if(!this.options.flex)break}return br?(Er=this.test_match(br,qi[Vn]),Er!==!1?Er:!1):this._input===""?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+`. 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Gt=_t.length-1;switch(Rc){case 5:pi.parseDirective("%%{","open_directive");break;case 6:pi.parseDirective(_t[Gt],"type_directive");break;case 7:_t[Gt]=_t[Gt].trim().replace(/'/g,'"'),pi.parseDirective(_t[Gt],"arg_directive");break;case 8:pi.parseDirective("}%%","close_directive","flowchart");break;case 10:this.$=[];break;case 11:(!Array.isArray(_t[Gt])||_t[Gt].length>0)&&_t[Gt-1].push(_t[Gt]),this.$=_t[Gt-1];break;case 12:case 97:case 153:case 155:case 156:this.$=_t[Gt];break;case 19:pi.setDirection("TB"),this.$="TB";break;case 20:pi.setDirection(_t[Gt-1]),this.$=_t[Gt-1];break;case 35:this.$=_t[Gt-1].nodes;break;case 36:case 37:case 38:case 39:case 40:this.$=[];break;case 41:this.$=pi.addSubGraph(_t[Gt-6],_t[Gt-1],_t[Gt-4]);break;case 42:this.$=pi.addSubGraph(_t[Gt-3],_t[Gt-1],_t[Gt-3]);break;case 43:this.$=pi.addSubGraph(void 0,_t[Gt-1],void 0);break;case 45:this.$=_t[Gt].trim(),pi.setAccTitle(this.$);break;case 46:case 47:this.$=_t[Gt].trim(),pi.setAccDescription(this.$);break;case 51:pi.addLink(_t[Gt-2].stmt,_t[Gt],_t[Gt-1]),this.$={stmt:_t[Gt],nodes:_t[Gt].concat(_t[Gt-2].nodes)};break;case 52:pi.addLink(_t[Gt-3].stmt,_t[Gt-1],_t[Gt-2]),this.$={stmt:_t[Gt-1],nodes:_t[Gt-1].concat(_t[Gt-3].nodes)};break;case 53:this.$={stmt:_t[Gt-1],nodes:_t[Gt-1]};break;case 54:this.$={stmt:_t[Gt],nodes:_t[Gt]};break;case 55:this.$=[_t[Gt]];break;case 56:this.$=_t[Gt-4].concat(_t[Gt]);break;case 57:this.$=[_t[Gt-2]],pi.setClass(_t[Gt-2],_t[Gt]);break;case 58:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"square");break;case 59:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"doublecircle");break;case 60:this.$=_t[Gt-5],pi.addVertex(_t[Gt-5],_t[Gt-2],"circle");break;case 61:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"ellipse");break;case 62:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"stadium");break;case 63:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"subroutine");break;case 64:this.$=_t[Gt-7],pi.addVertex(_t[Gt-7],_t[Gt-1],"rect",void 0,void 0,void 0,Object.fromEntries([[_t[Gt-5],_t[Gt-3]]]));break;case 65:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"cylinder");break;case 66:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"round");break;case 67:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"diamond");break;case 68:this.$=_t[Gt-5],pi.addVertex(_t[Gt-5],_t[Gt-2],"hexagon");break;case 69:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"odd");break;case 70:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"trapezoid");break;case 71:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"inv_trapezoid");break;case 72:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"lean_right");break;case 73:this.$=_t[Gt-3],pi.addVertex(_t[Gt-3],_t[Gt-1],"lean_left");break;case 74:this.$=_t[Gt],pi.addVertex(_t[Gt]);break;case 75:_t[Gt-1].text=_t[Gt],this.$=_t[Gt-1];break;case 76:case 77:_t[Gt-2].text=_t[Gt-1],this.$=_t[Gt-2];break;case 78:this.$=_t[Gt];break;case 79:var ff=pi.destructLink(_t[Gt],_t[Gt-2]);this.$={type:ff.type,stroke:ff.stroke,length:ff.length,text:_t[Gt-1]};break;case 80:var ff=pi.destructLink(_t[Gt]);this.$={type:ff.type,stroke:ff.stroke,length:ff.length};break;case 81:this.$=_t[Gt-1];break;case 82:this.$={text:_t[Gt],type:"text"};break;case 83:this.$={text:_t[Gt-1].text+""+_t[Gt],type:_t[Gt-1].type};break;case 84:this.$={text:_t[Gt],type:"text"};break;case 85:this.$={text:_t[Gt],type:"markdown"};break;case 98:case 154:this.$=_t[Gt-1]+""+_t[Gt];break;case 99:case 100:this.$=_t[Gt-4],pi.addClass(_t[Gt-2],_t[Gt]);break;case 101:this.$=_t[Gt-4],pi.setClass(_t[Gt-2],_t[Gt]);break;case 102:case 110:this.$=_t[Gt-1],pi.setClickEvent(_t[Gt-1],_t[Gt]);break;case 103:case 111:this.$=_t[Gt-3],pi.setClickEvent(_t[Gt-3],_t[Gt-2]),pi.setTooltip(_t[Gt-3],_t[Gt]);break;case 104:this.$=_t[Gt-2],pi.setClickEvent(_t[Gt-2],_t[Gt-1],_t[Gt]);break;case 105:this.$=_t[Gt-4],pi.setClickEvent(_t[Gt-4],_t[Gt-3],_t[Gt-2]),pi.setTooltip(_t[Gt-4],_t[Gt]);break;case 106:case 112:this.$=_t[Gt-1],pi.setLink(_t[Gt-1],_t[Gt]);break;case 107:case 113:this.$=_t[Gt-3],pi.setLink(_t[Gt-3],_t[Gt-2]),pi.setTooltip(_t[Gt-3],_t[Gt]);break;case 108:case 114:this.$=_t[Gt-3],pi.setLink(_t[Gt-3],_t[Gt-2],_t[Gt]);break;case 109:case 115:this.$=_t[Gt-5],pi.setLink(_t[Gt-5],_t[Gt-4],_t[Gt]),pi.setTooltip(_t[Gt-5],_t[Gt-2]);break;case 116:this.$=_t[Gt-4],pi.addVertex(_t[Gt-2],void 0,void 0,_t[Gt]);break;case 117:case 119:this.$=_t[Gt-4],pi.updateLink(_t[Gt-2],_t[Gt]);break;case 118:this.$=_t[Gt-4],pi.updateLink([_t[Gt-2]],_t[Gt]);break;case 120:this.$=_t[Gt-8],pi.updateLinkInterpolate([_t[Gt-6]],_t[Gt-2]),pi.updateLink([_t[Gt-6]],_t[Gt]);break;case 121:this.$=_t[Gt-8],pi.updateLinkInterpolate(_t[Gt-6],_t[Gt-2]),pi.updateLink(_t[Gt-6],_t[Gt]);break;case 122:this.$=_t[Gt-6],pi.updateLinkInterpolate([_t[Gt-4]],_t[Gt]);break;case 123:this.$=_t[Gt-6],pi.updateLinkInterpolate(_t[Gt-4],_t[Gt]);break;case 124:case 126:this.$=[_t[Gt]];break;case 125:case 127:_t[Gt-2].push(_t[Gt]),this.$=_t[Gt-2];break;case 129:this.$=_t[Gt-1]+_t[Gt];break;case 151:this.$=_t[Gt];break;case 152:this.$=_t[Gt-1]+""+_t[Gt];break;case 157:this.$="v";break;case 158:this.$="-";break;case 159:this.$={stmt:"dir",value:"TB"};break;case 160:this.$={stmt:"dir",value:"BT"};break;case 161:this.$={stmt:"dir",value:"RL"};break;case 162:this.$={stmt:"dir",value:"LR"};break}},table:[{3:1,4:2,5:3,6:5,12:a,16:4,21:f,22:p,24:w},{1:[3]},{1:[2,1]},{3:10,4:2,5:3,6:5,12:a,16:4,21:f,22:p,24:w},i(y,b,{17:11}),{7:12,13:[1,13]},{16:14,21:f,22:p,24:w},{16:15,21:f,22:p,24:w},{25:[1,16],26:[1,17]},{13:[2,5]},{1:[2,2]},{1:[2,9],18:18,19:19,20:E,21:S,22:N,23:B,32:24,33:25,34:26,35:27,36:28,37:29,38:R,43:31,44:j,46:$,48:V,50:35,51:45,52:Q,54:46,66:oe,67:ce,87:se,88:ge,89:ye,90:ke,91:Ae,92:de,96:ve,106:te,107:xe,110:De,112:he,113:Ie,117:47,119:ee,120:rt,121:me,122:gt,123:pe,124:Et,125:wt,126:jt,127:At,128:Bt},{8:64,10:[1,65],15:cn},i([10,15],[2,6]),i(y,[2,17]),i(y,[2,18]),i(y,[2,19]),{20:[1,68],21:[1,69],22:Nn,27:67,30:70},i(Ot,[2,11]),i(Ot,[2,12]),i(Ot,[2,13]),i(Ot,[2,14]),i(Ot,[2,15]),i(Ot,[2,16]),{9:72,20:oi,21:kt,23:Dt,49:73,78:77,81:[1,78],82:[1,79]},{9:80,20:oi,21:kt,23:Dt},{9:81,20:oi,21:kt,23:Dt},{9:82,20:oi,21:kt,23:Dt},{9:83,20:oi,21:kt,23:Dt},{9:84,20:oi,21:kt,23:Dt},{9:86,20:oi,21:kt,22:[1,85],23:Dt},i(Ot,[2,44]),{45:[1,87]},{47:[1,88]},i(Ot,[2,47]),i(vt,[2,54],{30:89,22:Nn}),{22:[1,90]},{22:[1,91]},{22:[1,92]},{22:[1,93]},{26:Nt,52:ze,66:Xe,67:Lt,84:[1,97],92:Ge,98:96,99:[1,94],101:[1,95],106:Bn,107:Oe,110:Ri,112:tn,113:hi,116:100,118:98,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},i(Ot,[2,159]),i(Ot,[2,160]),i(Ot,[2,161]),i(Ot,[2,162]),i(ha,[2,55],{53:[1,116]}),i(Zs,[2,74],{117:129,40:[1,117],52:Q,55:[1,118],57:[1,119],59:[1,120],61:[1,121],63:[1,122],65:[1,123],66:oe,67:ce,69:[1,124],71:[1,125],73:[1,126],74:[1,127],76:[1,128],92:de,96:ve,106:te,107:xe,110:De,112:he,113:Ie,123:pe,124:Et,125:wt,126:jt,127:At,128:Bt}),i(ns,[2,151]),i(ns,[2,176]),i(ns,[2,177]),i(ns,[2,178]),i(ns,[2,179]),i(ns,[2,180]),i(ns,[2,181]),i(ns,[2,182]),i(ns,[2,183]),i(ns,[2,184]),i(ns,[2,185]),i(ns,[2,186]),i(ns,[2,187]),i(ns,[2,188]),i(ns,[2,189]),i(ns,[2,190]),i(ns,[2,191]),{9:130,20:oi,21:kt,23:Dt},{11:131,14:[1,132]},i(Hi,[2,8]),i(y,[2,20]),i(y,[2,26]),i(y,[2,27]),{21:[1,133]},i(Js,[2,34],{30:134,22:Nn}),i(Ot,[2,35]),{50:135,51:45,52:Q,54:46,66:oe,67:ce,92:de,96:ve,106:te,107:xe,110:De,112:he,113:Ie,117:47,123:pe,124:Et,125:wt,126:jt,127:At,128:Bt},i(Pc,[2,48]),i(Pc,[2,49]),i(Pc,[2,50]),i(Ga,[2,78],{79:136,68:[1,138],80:[1,137]}),{22:ws,24:Oi,26:Er,38:br,39:139,42:Dr,52:ze,66:Xe,67:Lt,73:Vn,81:qi,83:140,84:yn,85:Bc,86:152,87:jn,88:Ms,89:Pa,90:Ta,91:_a,92:ka,93:Qi,95:143,96:ea,106:Bn,107:Oe,110:Ca,112:tn,113:hi,114:Sa,115:Ka,116:149,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},i([52,66,67,68,80,92,96,106,107,110,112,113,123,124,125,126,127,128],[2,80]),i(Ot,[2,36]),i(Ot,[2,37]),i(Ot,[2,38]),i(Ot,[2,39]),i(Ot,[2,40]),{22:ws,24:Oi,26:Er,38:br,39:164,42:Dr,52:ze,66:Xe,67:Lt,73:Vn,81:qi,83:140,84:yn,85:Bc,86:152,87:jn,88:Ms,89:Pa,90:Ta,91:_a,92:ka,93:Qi,95:143,96:ea,106:Bn,107:Oe,110:Ca,112:tn,113:hi,114:Sa,115:Ka,116:149,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},i(cg,b,{17:165}),i(Ot,[2,45]),i(Ot,[2,46]),i(vt,[2,53],{52:Gc}),{26:Nt,52:ze,66:Xe,67:Lt,92:Ge,98:167,103:[1,168],106:Bn,107:Oe,110:Ri,112:tn,113:hi,116:100,118:98,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},{96:[1,169],104:170,106:[1,171]},{26:Nt,52:ze,66:Xe,67:Lt,92:Ge,96:[1,172],98:173,106:Bn,107:Oe,110:Ri,112:tn,113:hi,116:100,118:98,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},{26:Nt,52:ze,66:Xe,67:Lt,92:Ge,98:174,106:Bn,107:Oe,110:Ri,112:tn,113:hi,116:100,118:98,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},i(Hi,[2,102],{22:[1,175],100:[1,176]}),i(Hi,[2,106],{22:[1,177]}),i(Hi,[2,110],{116:100,118:179,22:[1,178],26:Nt,52:ze,66:Xe,67:Lt,92:Ge,106:Bn,107:Oe,110:Ri,112:tn,113:hi,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr}),i(Hi,[2,112],{22:[1,180]}),i(Dh,[2,153]),i(Dh,[2,155]),i(Dh,[2,156]),i(Dh,[2,157]),i(Dh,[2,158]),i(Es,[2,163]),i(Es,[2,164]),i(Es,[2,165]),i(Es,[2,166]),i(Es,[2,167]),i(Es,[2,168]),i(Es,[2,169]),i(Es,[2,170]),i(Es,[2,171]),i(Es,[2,172]),i(Es,[2,173]),i(Es,[2,174]),i(Es,[2,175]),{52:Q,54:181,66:oe,67:ce,92:de,96:ve,106:te,107:xe,110:De,112:he,113:Ie,117:47,123:pe,124:Et,125:wt,126:jt,127:At,128:Bt},{22:ws,24:Oi,26:Er,38:br,39:182,42:Dr,52:ze,66:Xe,67:Lt,73:Vn,81:qi,83:140,84:yn,85:Bc,86:152,87:jn,88:Ms,89:Pa,90:Ta,91:_a,92:ka,93:Qi,95:143,96:ea,106:Bn,107:Oe,110:Ca,112:tn,113:hi,114:Sa,115:Ka,116:149,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},{22:ws,24:Oi,26:Er,38:br,39:183,42:Dr,52:ze,66:Xe,67:Lt,73:Vn,81:qi,83:140,84:yn,85:Bc,86:152,87:jn,88:Ms,89:Pa,90:Ta,91:_a,92:ka,93:Qi,95:143,96:ea,106:Bn,107:Oe,110:Ca,112:tn,113:hi,114:Sa,115:Ka,116:149,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},{22:ws,24:Oi,26:Er,38:br,39:185,42:Dr,52:ze,57:[1,184],66:Xe,67:Lt,73:Vn,81:qi,83:140,84:yn,85:Bc,86:152,87:jn,88:Ms,89:Pa,90:Ta,91:_a,92:ka,93:Qi,95:143,96:ea,106:Bn,107:Oe,110:Ca,112:tn,113:hi,114:Sa,115:Ka,116:149,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},{22:ws,24:Oi,26:Er,38:br,39:186,42:Dr,52:ze,66:Xe,67:Lt,73:Vn,81:qi,83:140,84:yn,85:Bc,86:152,87:jn,88:Ms,89:Pa,90:Ta,91:_a,92:ka,93:Qi,95:143,96:ea,106:Bn,107:Oe,110:Ca,112:tn,113:hi,114:Sa,115:Ka,116:149,123:Sr,124:Zn,125:Xn,126:ir,127:Hn,128:tr},{22:ws,24:O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Aa=new Error(rs);throw Aa.hash=Ps,Aa}},parse:function(rs){var Ps=this,Aa=[0],pi=[],Rc=[null],_t=[],hp=this.table,Gt="",ff=0,sm=0,m9=2,fp=1,N5=_t.slice.call(arguments,1),ah=Object.create(this.lexer),od={yy:{}};for(var P5 in this.yy)Object.prototype.hasOwnProperty.call(this.yy,P5)&&(od.yy[P5]=this.yy[P5]);ah.setInput(rs,od.yy),od.yy.lexer=ah,od.yy.parser=this,typeof ah.yylloc>"u"&&(ah.yylloc={});var B5=ah.yylloc;_t.push(B5);var y9=ah.options&&ah.options.ranges;typeof od.yy.parseError=="function"?this.parseError=od.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function vL(){var oh;return oh=pi.pop()||ah.lex()||fp,typeof oh!="number"&&(oh instanceof Array&&(pi=oh,oh=pi.pop()),oh=Ps.symbols_[oh]||oh),oh}for(var v1,dp,cd,am,ev={},om,yc,hx,Vo;;){if(dp=Aa[Aa.length-1],this.defaultActions[dp]?cd=this.defaultActions[dp]:((v1===null||typeof v1>"u")&&(v1=vL()),cd=hp[dp]&&hp[dp][v1]),typeof cd>"u"||!cd.length||!cd[0]){var fx="";Vo=[];for(om in hp[dp])this.terminals_[om]&&om>m9&&Vo.push("'"+this.terminals_[om]+"'");ah.showPosition?fx="Parse error on line "+(ff+1)+`: +`+ah.showPosition()+` +Expecting `+Vo.join(", ")+", got '"+(this.terminals_[v1]||v1)+"'":fx="Parse error on line "+(ff+1)+": Unexpected "+(v1==fp?"end of input":"'"+(this.terminals_[v1]||v1)+"'"),this.parseError(fx,{text:ah.match,token:this.terminals_[v1]||v1,line:ah.yylineno,loc:B5,expected:Vo})}if(cd[0]instanceof Array&&cd.length>1)throw new Error("Parse Error: multiple actions possible at state: "+dp+", token: "+v1);switch(cd[0]){case 1:Aa.push(v1),Rc.push(ah.yytext),_t.push(ah.yylloc),Aa.push(cd[1]),v1=null,sm=ah.yyleng,Gt=ah.yytext,ff=ah.yylineno,B5=ah.yylloc;break;case 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this.yy=Ps||this.yy||{},this._input=rs,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},input:function(){var rs=this._input[0];this.yytext+=rs,this.yyleng++,this.offset++,this.match+=rs,this.matched+=rs;var Ps=rs.match(/(?:\r\n?|\n).*/g);return Ps?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),rs},unput:function(rs){var Ps=rs.length,Aa=rs.split(/(?:\r\n?|\n)/g);this._input=rs+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-Ps),this.offset-=Ps;var pi=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),Aa.length-1&&(this.yylineno-=Aa.length-1);var Rc=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:Aa?(Aa.length===pi.length?this.yylloc.first_column:0)+pi[pi.length-Aa.length].length-Aa[0].length:this.yylloc.first_column-Ps},this.options.ranges&&(this.yylloc.range=[Rc[0],Rc[0]+this.yyleng-Ps]),this.yyleng=this.yytext.length,this},more:function(){return this._more=!0,this},reject:function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true). +`+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},less:function(rs){this.unput(this.match.slice(rs))},pastInput:function(){var rs=this.matched.substr(0,this.matched.length-this.match.length);return(rs.length>20?"...":"")+rs.substr(-20).replace(/\n/g,"")},upcomingInput:function(){var rs=this.match;return rs.length<20&&(rs+=this._input.substr(0,20-rs.length)),(rs.substr(0,20)+(rs.length>20?"...":"")).replace(/\n/g,"")},showPosition:function(){var rs=this.pastInput(),Ps=new Array(rs.length+1).join("-");return rs+this.upcomingInput()+` +`+Ps+"^"},test_match:function(rs,Ps){var Aa,pi,Rc;if(this.options.backtrack_lexer&&(Rc={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(Rc.yylloc.range=this.yylloc.range.slice(0))),pi=rs[0].match(/(?:\r\n?|\n).*/g),pi&&(this.yylineno+=pi.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:pi?pi[pi.length-1].length-pi[pi.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+rs[0].length},this.yytext+=rs[0],this.match+=rs[0],this.matches=rs,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(rs[0].length),this.matched+=rs[0],Aa=this.performAction.call(this,this.yy,this,Ps,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),Aa)return Aa;if(this._backtrack){for(var _t in Rc)this[_t]=Rc[_t];return!1}return!1},next:function(){if(this.done)return this.EOF;this._input||(this.done=!0);var rs,Ps,Aa,pi;this._more||(this.yytext="",this.match="");for(var Rc=this._currentRules(),_t=0;_tPs[0].length)){if(Ps=Aa,pi=_t,this.options.backtrack_lexer){if(rs=this.test_match(Aa,Rc[_t]),rs!==!1)return rs;if(this._backtrack){Ps=!1;continue}else return!1}else if(!this.options.flex)break}return Ps?(rs=this.test_match(Ps,Rc[pi]),rs!==!1?rs:!1):this._input===""?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+`. Unrecognized text. +`+this.showPosition(),{text:"",token:null,line:this.yylineno})},lex:function(){var Ps=this.next();return Ps||this.lex()},begin:function(Ps){this.conditionStack.push(Ps)},popState:function(){var Ps=this.conditionStack.length-1;return Ps>0?this.conditionStack.pop():this.conditionStack[0]},_currentRules:function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},topState:function(Ps){return Ps=this.conditionStack.length-1-Math.abs(Ps||0),Ps>=0?this.conditionStack[Ps]:"INITIAL"},pushState:function(Ps){this.begin(Ps)},stateStackSize:function(){return this.conditionStack.length},options:{},performAction:function(Ps,Aa,pi,Rc){switch(pi){case 0:return this.begin("open_directive"),12;case 1:return this.begin("type_directive"),13;case 2:return this.popState(),this.begin("arg_directive"),10;case 3:return this.popState(),this.popState(),15;case 4:return 14;case 5:return this.begin("acc_title"),44;case 6:return this.popState(),"acc_title_value";case 7:return this.begin("acc_descr"),46;case 8:return this.popState(),"acc_descr_value";case 9:this.begin("acc_descr_multiline");break;case 10:this.popState();break;case 11:return"acc_descr_multiline_value";case 12:this.begin("md_string");break;case 13:return"MD_STR";case 14:this.popState();break;case 15:this.begin("string");break;case 16:this.popState();break;case 17:return"STR";case 18:return 87;case 19:return 96;case 20:return 88;case 21:return 105;case 22:return 89;case 23:return 90;case 24:this.begin("href");break;case 25:this.popState();break;case 26:return 101;case 27:this.begin("callbackname");break;case 28:this.popState();break;case 29:this.popState(),this.begin("callbackargs");break;case 30:return 99;case 31:this.popState();break;case 32:return 100;case 33:this.begin("click");break;case 34:this.popState();break;case 35:return 91;case 36:return Ps.lex.firstGraph()&&this.begin("dir"),24;case 37:return Ps.lex.firstGraph()&&this.begin("dir"),24;case 38:return Ps.lex.firstGraph()&&this.begin("dir"),24;case 39:return 38;case 40:return 42;case 41:return 102;case 42:return 102;case 43:return 102;case 44:return 102;case 45:return this.popState(),25;case 46:return this.popState(),26;case 47:return this.popState(),26;case 48:return this.popState(),26;case 49:return this.popState(),26;case 50:return this.popState(),26;case 51:return this.popState(),26;case 52:return this.popState(),26;case 53:return this.popState(),26;case 54:return this.popState(),26;case 55:return this.popState(),26;case 56:return 119;case 57:return 120;case 58:return 121;case 59:return 122;case 60:return 106;case 61:return 112;case 62:return 53;case 63:return 67;case 64:return 52;case 65:return 20;case 66:return 107;case 67:return 127;case 68:return 82;case 69:return 82;case 70:return 82;case 71:return 82;case 72:return 81;case 73:return 81;case 74:return 81;case 75:return 59;case 76:return 60;case 77:return 61;case 78:return 62;case 79:return 63;case 80:return 64;case 81:return 65;case 82:return 69;case 83:return 70;case 84:return 55;case 85:return 56;case 86:return 110;case 87:return 113;case 88:return 128;case 89:return 125;case 90:return 114;case 91:return 126;case 92:return 126;case 93:return 115;case 94:return 73;case 95:return 93;case 96:return"SEP";case 97:return 92;case 98:return 66;case 99:return 75;case 100:return 74;case 101:return 77;case 102:return 76;case 103:return 123;case 104:return 124;case 105:return 68;case 106:return 57;case 107:return 58;case 108:return 40;case 109:return 41;case 110:return 71;case 111:return 72;case 112:return 134;case 113:return 21;case 114:return 22;case 115:return 23}},rules:[/^(?:%%\{)/,/^(?:((?:(?!\}%%)[^:.])*))/,/^(?::)/,/^(?:\}%%)/,/^(?:((?:(?!\}%%).|\n)*))/,/^(?:accTitle\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*\{\s*)/,/^(?:[\}])/,/^(?:[^\}]*)/,/^(?:["][`])/,/^(?:[^`"]+)/,/^(?:[`]["])/,/^(?:["])/,/^(?:["])/,/^(?:[^"]*)/,/^(?:style\b)/,/^(?:default\b)/,/^(?:linkStyle\b)/,/^(?:interpolate\b)/,/^(?:classDef\b)/,/^(?:class\b)/,/^(?:href[\s]+["])/,/^(?:["])/,/^(?:[^"]*)/,/^(?:call[\s]+)/,/^(?:\([\s]*\))/,/^(?:\()/,/^(?:[^(]*)/,/^(?:\))/,/^(?:[^)]*)/,/^(?:click[\s]+)/,/^(?:[\s\n])/,/^(?:[^\s\n]*)/,/^(?:flowchart-elk\b)/,/^(?:graph\b)/,/^(?:flowchart\b)/,/^(?:subgraph\b)/,/^(?:end\b\s*)/,/^(?:_self\b)/,/^(?:_blank\b)/,/^(?:_parent\b)/,/^(?:_top\b)/,/^(?:(\r?\n)*\s*\n)/,/^(?:\s*LR\b)/,/^(?:\s*RL\b)/,/^(?:\s*TB\b)/,/^(?:\s*BT\b)/,/^(?:\s*TD\b)/,/^(?:\s*BR\b)/,/^(?:\s*<)/,/^(?:\s*>)/,/^(?:\s*\^)/,/^(?:\s*v\b)/,/^(?:.*direction\s+TB[^\n]*)/,/^(?:.*direction\s+BT[^\n]*)/,/^(?:.*direction\s+RL[^\n]*)/,/^(?:.*direction\s+LR[^\n]*)/,/^(?:[0-9]+)/,/^(?:#)/,/^(?::::)/,/^(?::)/,/^(?:&)/,/^(?:;)/,/^(?:,)/,/^(?:\*)/,/^(?:\s*[xo<]?--+[-xo>]\s*)/,/^(?:\s*[xo<]?==+[=xo>]\s*)/,/^(?:\s*[xo<]?-?\.+-[xo>]?\s*)/,/^(?:\s*~~[\~]+\s*)/,/^(?:\s*[xo<]?--\s*)/,/^(?:\s*[xo<]?==\s*)/,/^(?:\s*[xo<]?-\.\s*)/,/^(?:\(-)/,/^(?:-\))/,/^(?:\(\[)/,/^(?:\]\))/,/^(?:\[\[)/,/^(?:\]\])/,/^(?:\[\|)/,/^(?:\[\()/,/^(?:\)\])/,/^(?:\(\(\()/,/^(?:\)\)\))/,/^(?:-)/,/^(?:\.)/,/^(?:[\_])/,/^(?:\+)/,/^(?:%)/,/^(?:=)/,/^(?:=)/,/^(?:<)/,/^(?:>)/,/^(?:\^)/,/^(?:\\\|)/,/^(?:v\b)/,/^(?:[A-Za-z]+)/,/^(?:\\\])/,/^(?:\[\/)/,/^(?:\/\])/,/^(?:\[\\)/,/^(?:[!"#$%&'*+,-.`?\\_/])/,/^(?:[\u00AA\u00B5\u00BA\u00C0-\u00D6\u00D8-\u00F6]|[\u00F8-\u02C1\u02C6-\u02D1\u02E0-\u02E4\u02EC\u02EE\u0370-\u0374\u0376\u0377]|[\u037A-\u037D\u0386\u0388-\u038A\u038C\u038E-\u03A1\u03A3-\u03F5]|[\u03F7-\u0481\u048A-\u0527\u0531-\u0556\u0559\u0561-\u0587\u05D0-\u05EA]|[\u05F0-\u05F2\u0620-\u064A\u066E\u066F\u0671-\u06D3\u06D5\u06E5\u06E6\u06EE]|[\u06EF\u06FA-\u06FC\u06FF\u0710\u0712-\u072F\u074D-\u07A5\u07B1\u07CA-\u07EA]|[\u07F4\u07F5\u07FA\u0800-\u0815\u081A\u0824\u0828\u0840-\u0858\u08A0]|[\u08A2-\u08AC\u0904-\u0939\u093D\u0950\u0958-\u0961\u0971-\u0977]|[\u0979-\u097F\u0985-\u098C\u098F\u0990\u0993-\u09A8\u09AA-\u09B0\u09B2]|[\u09B6-\u09B9\u09BD\u09CE\u09DC\u09DD\u09DF-\u09E1\u09F0\u09F1\u0A05-\u0A0A]|[\u0A0F\u0A10\u0A13-\u0A28\u0A2A-\u0A30\u0A32\u0A33\u0A35\u0A36\u0A38\u0A39]|[\u0A59-\u0A5C\u0A5E\u0A72-\u0A74\u0A85-\u0A8D\u0A8F-\u0A91\u0A93-\u0AA8]|[\u0AAA-\u0AB0\u0AB2\u0AB3\u0AB5-\u0AB9\u0ABD\u0AD0\u0AE0\u0AE1\u0B05-\u0B0C]|[\u0B0F\u0B10\u0B13-\u0B28\u0B2A-\u0B30\u0B32\u0B33\u0B35-\u0B39\u0B3D\u0B5C]|[\u0B5D\u0B5F-\u0B61\u0B71\u0B83\u0B85-\u0B8A\u0B8E-\u0B90\u0B92-\u0B95\u0B99]|[\u0B9A\u0B9C\u0B9E\u0B9F\u0BA3\u0BA4\u0BA8-\u0BAA\u0BAE-\u0BB9\u0BD0]|[\u0C05-\u0C0C\u0C0E-\u0C10\u0C12-\u0C28\u0C2A-\u0C33\u0C35-\u0C39\u0C3D]|[\u0C58\u0C59\u0C60\u0C61\u0C85-\u0C8C\u0C8E-\u0C90\u0C92-\u0CA8\u0CAA-\u0CB3]|[\u0CB5-\u0CB9\u0CBD\u0CDE\u0CE0\u0CE1\u0CF1\u0CF2\u0D05-\u0D0C\u0D0E-\u0D10]|[\u0D12-\u0D3A\u0D3D\u0D4E\u0D60\u0D61\u0D7A-\u0D7F\u0D85-\u0D96\u0D9A-\u0DB1]|[\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6\u0E01-\u0E30\u0E32\u0E33\u0E40-\u0E46\u0E81]|[\u0E82\u0E84\u0E87\u0E88\u0E8A\u0E8D\u0E94-\u0E97\u0E99-\u0E9F\u0EA1-\u0EA3]|[\u0EA5\u0EA7\u0EAA\u0EAB\u0EAD-\u0EB0\u0EB2\u0EB3\u0EBD\u0EC0-\u0EC4\u0EC6]|[\u0EDC-\u0EDF\u0F00\u0F40-\u0F47\u0F49-\u0F6C\u0F88-\u0F8C\u1000-\u102A]|[\u103F\u1050-\u1055\u105A-\u105D\u1061\u1065\u1066\u106E-\u1070\u1075-\u1081]|[\u108E\u10A0-\u10C5\u10C7\u10CD\u10D0-\u10FA\u10FC-\u1248\u124A-\u124D]|[\u1250-\u1256\u1258\u125A-\u125D\u1260-\u1288\u128A-\u128D\u1290-\u12B0]|[\u12B2-\u12B5\u12B8-\u12BE\u12C0\u12C2-\u12C5\u12C8-\u12D6\u12D8-\u1310]|[\u1312-\u1315\u1318-\u135A\u1380-\u138F\u13A0-\u13F4\u1401-\u166C]|[\u166F-\u167F\u1681-\u169A\u16A0-\u16EA\u1700-\u170C\u170E-\u1711]|[\u1720-\u1731\u1740-\u1751\u1760-\u176C\u176E-\u1770\u1780-\u17B3\u17D7]|[\u17DC\u1820-\u1877\u1880-\u18A8\u18AA\u18B0-\u18F5\u1900-\u191C]|[\u1950-\u196D\u1970-\u1974\u1980-\u19AB\u19C1-\u19C7\u1A00-\u1A16]|[\u1A20-\u1A54\u1AA7\u1B05-\u1B33\u1B45-\u1B4B\u1B83-\u1BA0\u1BAE\u1BAF]|[\u1BBA-\u1BE5\u1C00-\u1C23\u1C4D-\u1C4F\u1C5A-\u1C7D\u1CE9-\u1CEC]|[\u1CEE-\u1CF1\u1CF5\u1CF6\u1D00-\u1DBF\u1E00-\u1F15\u1F18-\u1F1D]|[\u1F20-\u1F45\u1F48-\u1F4D\u1F50-\u1F57\u1F59\u1F5B\u1F5D\u1F5F-\u1F7D]|[\u1F80-\u1FB4\u1FB6-\u1FBC\u1FBE\u1FC2-\u1FC4\u1FC6-\u1FCC\u1FD0-\u1FD3]|[\u1FD6-\u1FDB\u1FE0-\u1FEC\u1FF2-\u1FF4\u1FF6-\u1FFC\u2071\u207F]|[\u2090-\u209C\u2102\u2107\u210A-\u2113\u2115\u2119-\u211D\u2124\u2126\u2128]|[\u212A-\u212D\u212F-\u2139\u213C-\u213F\u2145-\u2149\u214E\u2183\u2184]|[\u2C00-\u2C2E\u2C30-\u2C5E\u2C60-\u2CE4\u2CEB-\u2CEE\u2CF2\u2CF3]|[\u2D00-\u2D25\u2D27\u2D2D\u2D30-\u2D67\u2D6F\u2D80-\u2D96\u2DA0-\u2DA6]|[\u2DA8-\u2DAE\u2DB0-\u2DB6\u2DB8-\u2DBE\u2DC0-\u2DC6\u2DC8-\u2DCE]|[\u2DD0-\u2DD6\u2DD8-\u2DDE\u2E2F\u3005\u3006\u3031-\u3035\u303B\u303C]|[\u3041-\u3096\u309D-\u309F\u30A1-\u30FA\u30FC-\u30FF\u3105-\u312D]|[\u3131-\u318E\u31A0-\u31BA\u31F0-\u31FF\u3400-\u4DB5\u4E00-\u9FCC]|[\uA000-\uA48C\uA4D0-\uA4FD\uA500-\uA60C\uA610-\uA61F\uA62A\uA62B]|[\uA640-\uA66E\uA67F-\uA697\uA6A0-\uA6E5\uA717-\uA71F\uA722-\uA788]|[\uA78B-\uA78E\uA790-\uA793\uA7A0-\uA7AA\uA7F8-\uA801\uA803-\uA805]|[\uA807-\uA80A\uA80C-\uA822\uA840-\uA873\uA882-\uA8B3\uA8F2-\uA8F7\uA8FB]|[\uA90A-\uA925\uA930-\uA946\uA960-\uA97C\uA984-\uA9B2\uA9CF\uAA00-\uAA28]|[\uAA40-\uAA42\uAA44-\uAA4B\uAA60-\uAA76\uAA7A\uAA80-\uAAAF\uAAB1\uAAB5]|[\uAAB6\uAAB9-\uAABD\uAAC0\uAAC2\uAADB-\uAADD\uAAE0-\uAAEA\uAAF2-\uAAF4]|[\uAB01-\uAB06\uAB09-\uAB0E\uAB11-\uAB16\uAB20-\uAB26\uAB28-\uAB2E]|[\uABC0-\uABE2\uAC00-\uD7A3\uD7B0-\uD7C6\uD7CB-\uD7FB\uF900-\uFA6D]|[\uFA70-\uFAD9\uFB00-\uFB06\uFB13-\uFB17\uFB1D\uFB1F-\uFB28\uFB2A-\uFB36]|[\uFB38-\uFB3C\uFB3E\uFB40\uFB41\uFB43\uFB44\uFB46-\uFBB1\uFBD3-\uFD3D]|[\uFD50-\uFD8F\uFD92-\uFDC7\uFDF0-\uFDFB\uFE70-\uFE74\uFE76-\uFEFC]|[\uFF21-\uFF3A\uFF41-\uFF5A\uFF66-\uFFBE\uFFC2-\uFFC7\uFFCA-\uFFCF]|[\uFFD2-\uFFD7\uFFDA-\uFFDC])/,/^(?:\|)/,/^(?:\()/,/^(?:\))/,/^(?:\[)/,/^(?:\])/,/^(?:\{)/,/^(?:\})/,/^(?:")/,/^(?:(\r?\n)+)/,/^(?:\s)/,/^(?:$)/],conditions:{close_directive:{rules:[],inclusive:!1},arg_directive:{rules:[3,4],inclusive:!1},type_directive:{rules:[2,3],inclusive:!1},open_directive:{rules:[1],inclusive:!1},callbackargs:{rules:[31,32],inclusive:!1},callbackname:{rules:[28,29,30],inclusive:!1},href:{rules:[25,26],inclusive:!1},click:{rules:[34,35],inclusive:!1},vertex:{rules:[],inclusive:!1},dir:{rules:[45,46,47,48,49,50,51,52,53,54,55],inclusive:!1},acc_descr_multiline:{rules:[10,11],inclusive:!1},acc_descr:{rules:[8],inclusive:!1},acc_title:{rules:[6],inclusive:!1},md_string:{rules:[13,14],inclusive:!1},string:{rules:[16,17],inclusive:!1},INITIAL:{rules:[0,5,7,9,12,15,18,19,20,21,22,23,24,27,33,36,37,38,39,40,41,42,43,44,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115],inclusive:!0}}};return 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86:he.commit(ee[me-2],ee[me-4],he.commitType.NORMAL,ee[me]);break;case 87:he.commit(ee[me-6],ee[me-4],ee[me-2],ee[me]);break;case 88:he.commit(ee[me-6],ee[me-4],ee[me],ee[me-2]);break;case 89:he.commit(ee[me-6],ee[me-2],ee[me-4],ee[me]);break;case 90:he.commit(ee[me-6],ee[me],ee[me-4],ee[me-2]);break;case 91:he.commit(ee[me-6],ee[me-2],ee[me],ee[me-4]);break;case 92:he.commit(ee[me-6],ee[me],ee[me-2],ee[me-4]);break;case 93:he.commit(ee[me-4],ee[me-6],ee[me-2],ee[me]);break;case 94:he.commit(ee[me-4],ee[me-6],ee[me],ee[me-2]);break;case 95:he.commit(ee[me-2],ee[me-6],ee[me-4],ee[me]);break;case 96:he.commit(ee[me],ee[me-6],ee[me-4],ee[me-2]);break;case 97:he.commit(ee[me-2],ee[me-6],ee[me],ee[me-4]);break;case 98:he.commit(ee[me],ee[me-6],ee[me-2],ee[me-4]);break;case 99:he.commit(ee[me],ee[me-4],ee[me-2],ee[me-6]);break;case 100:he.commit(ee[me-2],ee[me-4],ee[me],ee[me-6]);break;case 101:he.commit(ee[me],ee[me-2],ee[me-4],ee[me-6]);break;case 102:he.commit(ee[me-2],ee[me],ee[me-4],ee[me-6]);break;case 103:he.commit(ee[me-4],ee[me-2],ee[me],ee[me-6]);break;case 104:he.commit(ee[me-4],ee[me],ee[me-2],ee[me-6]);break;case 105:he.commit(ee[me-2],ee[me-4],ee[me-6],ee[me]);break;case 106:he.commit(ee[me],ee[me-4],ee[me-6],ee[me-2]);break;case 107:he.commit(ee[me-2],ee[me],ee[me-6],ee[me-4]);break;case 108:he.commit(ee[me],ee[me-2],ee[me-6],ee[me-4]);break;case 109:he.commit(ee[me-4],ee[me-2],ee[me-6],ee[me]);break;case 110:he.commit(ee[me-4],ee[me],ee[me-6],ee[me-2]);break;case 111:this.$="";break;case 112:this.$=ee[me];break;case 113:this.$=he.commitType.NORMAL;break;case 114:this.$=he.commitType.REVERSE;break;case 115:this.$=he.commitType.HIGHLIGHT;break;case 118:he.parseDirective("%%{","open_directive");break;case 119:he.parseDirective(ee[me],"type_directive");break;case 120:ee[me]=ee[me].trim().replace(/'/g,'"'),he.parseDirective(ee[me],"arg_directive");break;case 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Unrecognized text. +`+this.showPosition(),{text:"",token:null,line:this.yylineno})},lex:function(){var xe=this.next();return xe||this.lex()},begin:function(xe){this.conditionStack.push(xe)},popState:function(){var xe=this.conditionStack.length-1;return xe>0?this.conditionStack.pop():this.conditionStack[0]},_currentRules:function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},topState:function(xe){return xe=this.conditionStack.length-1-Math.abs(xe||0),xe>=0?this.conditionStack[xe]:"INITIAL"},pushState:function(xe){this.begin(xe)},stateStackSize:function(){return this.conditionStack.length},options:{"case-insensitive":!0},performAction:function(xe,De,he,Ie){switch(he){case 0:return this.begin("open_directive"),40;case 1:return this.begin("type_directive"),41;case 2:return this.popState(),this.begin("arg_directive"),33;case 3:return this.popState(),this.popState(),43;case 4:return 42;case 5:return this.begin("acc_title"),21;case 6:return this.popState(),"acc_title_value";case 7:return this.begin("acc_descr"),23;case 8:return this.popState(),"acc_descr_value";case 9:this.begin("acc_descr_multiline");break;case 10:this.popState();break;case 11:return"acc_descr_multiline_value";case 12:break;case 13:break;case 14:break;case 15:return 11;case 16:break;case 17:break;case 18:break;case 19:this.begin("href");break;case 20:this.popState();break;case 21:return 38;case 22:this.begin("callbackname");break;case 23:this.popState();break;case 24:this.popState(),this.begin("callbackargs");break;case 25:return 36;case 26:this.popState();break;case 27:return 37;case 28:this.begin("click");break;case 29:this.popState();break;case 30:return 35;case 31:return 5;case 32:return 12;case 33:return 13;case 34:return 14;case 35:return 15;case 36:return 16;case 37:return 18;case 38:return 17;case 39:return 19;case 40:return"date";case 41:return 20;case 42:return"accDescription";case 43:return 26;case 44:return 28;case 45:return 29;case 46:return 33;case 47:return 7;case 48:return"INVALID"}},rules:[/^(?:%%\{)/i,/^(?:((?:(?!\}%%)[^:.])*))/i,/^(?::)/i,/^(?:\}%%)/i,/^(?:((?:(?!\}%%).|\n)*))/i,/^(?:accTitle\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*\{\s*)/i,/^(?:[\}])/i,/^(?:[^\}]*)/i,/^(?:%%(?!\{)*[^\n]*)/i,/^(?:[^\}]%%*[^\n]*)/i,/^(?:%%*[^\n]*[\n]*)/i,/^(?:[\n]+)/i,/^(?:\s+)/i,/^(?:#[^\n]*)/i,/^(?:%[^\n]*)/i,/^(?:href[\s]+["])/i,/^(?:["])/i,/^(?:[^"]*)/i,/^(?:call[\s]+)/i,/^(?:\([\s]*\))/i,/^(?:\()/i,/^(?:[^(]*)/i,/^(?:\))/i,/^(?:[^)]*)/i,/^(?:click[\s]+)/i,/^(?:[\s\n])/i,/^(?:[^\s\n]*)/i,/^(?:gantt\b)/i,/^(?:dateFormat\s[^#\n;]+)/i,/^(?:inclusiveEndDates\b)/i,/^(?:topAxis\b)/i,/^(?:axisFormat\s[^#\n;]+)/i,/^(?:tickInterval\s[^#\n;]+)/i,/^(?:includes\s[^#\n;]+)/i,/^(?:excludes\s[^#\n;]+)/i,/^(?:todayMarker\s[^\n;]+)/i,/^(?:\d\d\d\d-\d\d-\d\d\b)/i,/^(?:title\s[^#\n;]+)/i,/^(?:accDescription\s[^#\n;]+)/i,/^(?:section\s[^#:\n;]+)/i,/^(?:[^#:\n;]+)/i,/^(?::[^#\n;]+)/i,/^(?::)/i,/^(?:$)/i,/^(?:.)/i],conditions:{acc_descr_multiline:{rules:[10,11],inclusive:!1},acc_descr:{rules:[8],inclusive:!1},acc_title:{rules:[6],inclusive:!1},close_directive:{rules:[],inclusive:!1},arg_directive:{rules:[3,4],inclusive:!1},type_directive:{rules:[2,3],inclusive:!1},open_directive:{rules:[1],inclusive:!1},callbackargs:{rules:[26,27],inclusive:!1},callbackname:{rules:[23,24,25],inclusive:!1},href:{rules:[20,21],inclusive:!1},click:{rules:[29,30],inclusive:!1},INITIAL:{rules:[0,5,7,9,12,13,14,15,16,17,18,19,22,28,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48],inclusive:!0}}};return ve}();ke.lexer=Ae;function de(){this.yy={}}return de.prototype=ke,ke.Parser=de,new de}();N0e.parser=N0e;const Ejt=N0e;var Tjt="isoweek";const _jt=function(i,a,f){var p=function(S,N){var B=(N?f.utc:f)().year(S).startOf(o5),R=4-B.isoWeekday();return B.isoWeekday()>4&&(R+=7),B.add(R,Fw)},w=function(S){return S.add(4-S.isoWeekday(),Fw)},y=a.prototype;y.isoWeekYear=function(){var E=w(this);return E.year()},y.isoWeek=function(E){if(!this.$utils().u(E))return this.add((E-this.isoWeek())*7,Fw);var S=w(this),N=p(this.isoWeekYear(),this.$u);return S.diff(N,yN)+1},y.isoWeekday=function(E){return this.$utils().u(E)?this.day()||7:this.day(this.day()%7?E:E-7)};var b=y.startOf;y.startOf=function(E,S){var N=this.$utils(),B=N.u(S)?!0:S,R=N.p(E);return R===Tjt?B?this.date(this.date()-(this.isoWeekday()-1)).startOf("day"):this.date(this.date()-1-(this.isoWeekday()-1)+7).endOf("day"):b.bind(this)(E,S)}};var Cjt=function(a){return a.replace(/(\[[^\]]+])|(MMMM|MM|DD|dddd)/g,function(f,p,w){return 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line */ + + .crit0, + .crit1, + .crit2, + .crit3 { + stroke: ${i.critBorderColor}; + fill: ${i.critBkgColor}; + stroke-width: 2; + } + + .activeCrit0, + .activeCrit1, + .activeCrit2, + .activeCrit3 { + stroke: ${i.critBorderColor}; + fill: ${i.activeTaskBkgColor}; + stroke-width: 2; + } + + .doneCrit0, + .doneCrit1, + .doneCrit2, + .doneCrit3 { + stroke: ${i.critBorderColor}; + fill: ${i.doneTaskBkgColor}; + stroke-width: 2; + cursor: pointer; + shape-rendering: crispEdges; + } + + .milestone { + transform: rotate(45deg) scale(0.8,0.8); + } + + .milestoneText { + font-style: italic; + } + .doneCritText0, + .doneCritText1, + .doneCritText2, + .doneCritText3 { + fill: ${i.taskTextDarkColor} !important; + } + + .activeCritText0, + .activeCritText1, + .activeCritText2, + .activeCritText3 { + fill: ${i.taskTextDarkColor} !important; + } + + .titleText { + text-anchor: middle; + font-size: 18px; + fill: ${i.textColor} ; + font-family: 'trebuchet ms', verdana, arial, sans-serif; + 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Unrecognized text. +`+this.showPosition(),{text:"",token:null,line:this.yylineno})},lex:function(){var E=this.next();return E||this.lex()},begin:function(E){this.conditionStack.push(E)},popState:function(){var E=this.conditionStack.length-1;return E>0?this.conditionStack.pop():this.conditionStack[0]},_currentRules:function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},topState:function(E){return E=this.conditionStack.length-1-Math.abs(E||0),E>=0?this.conditionStack[E]:"INITIAL"},pushState:function(E){this.begin(E)},stateStackSize:function(){return this.conditionStack.length},options:{"case-insensitive":!0},performAction:function(E,S,N,B){switch(N){case 0:return 4;case 1:return 9;case 2:return"space";case 3:return 10;case 4:return 6;case 5:return"TXT"}},rules:[/^(?:info\b)/i,/^(?:[\s\n\r]+)/i,/^(?:[\s]+)/i,/^(?:showInfo\b)/i,/^(?:$)/i,/^(?:.)/i],conditions:{INITIAL:{rules:[0,1,2,3,4,5],inclusive:!0}}};return y}();f.lexer=p;function w(){this.yy={}}return w.prototype=f,f.Parser=w,new w}();W0e.parser=W0e;const E$t=W0e;var ARe="",LRe=!1;const T$t=Object.freeze(Object.defineProperty({__proto__:null,diagram:{parser:E$t,db:{setMessage:i=>{Fe.debug("Setting message to: "+i),ARe=i},getMessage:()=>ARe,setInfo:i=>{LRe=i},getInfo:()=>LRe,clear:rp},renderer:{draw:(i,a,f)=>{try{Fe.debug(`Rendering info diagram +`+i);const p=Tt().securityLevel;let w;p==="sandbox"&&(w=Cr("#i"+a));const b=Cr(p==="sandbox"?w.nodes()[0].contentDocument.body:"body").select("#"+a);b.append("g").append("text").attr("x",100).attr("y",40).attr("class","version").attr("font-size","32px").style("text-anchor","middle").text("v "+f),b.attr("height",100),b.attr("width",400)}catch(p){Fe.error("Error while rendering info diagram"),Fe.error(p.message)}}},styles:()=>""}},Symbol.toStringTag,{value:"Module"}));var K0e=function(){var i=function(Ae,de,ve,te){for(ve=ve||{},te=Ae.length;te--;ve[Ae[te]]=de);return ve},a=[1,4],f=[1,5],p=[1,6],w=[1,7],y=[1,9],b=[1,11,13,15,17,19,20,26,27,28,29],E=[2,5],S=[1,6,11,13,15,17,19,20,26,27,28,29],N=[26,27,28],B=[2,8],R=[1,18],j=[1,19],$=[1,20],V=[1,21],Q=[1,22],oe=[1,23],ce=[1,28],se=[6,26,27,28,29],ge={trace:function(){},yy:{},symbols_:{error:2,start:3,eol:4,directive:5,PIE:6,document:7,showData:8,line:9,statement:10,txt:11,value:12,title:13,title_value:14,acc_title:15,acc_title_value:16,acc_descr:17,acc_descr_value:18,acc_descr_multiline_value:19,section:20,openDirective:21,typeDirective:22,closeDirective:23,":":24,argDirective:25,NEWLINE:26,";":27,EOF:28,open_directive:29,type_directive:30,arg_directive:31,close_directive:32,$accept:0,$end:1},terminals_:{2:"error",6:"PIE",8:"showData",11:"txt",12:"value",13:"title",14:"title_value",15:"acc_title",16:"acc_title_value",17:"acc_descr",18:"acc_descr_value",19:"acc_descr_multiline_value",20:"section",24:":",26:"NEWLINE",27:";",28:"EOF",29:"open_directive",30:"type_directive",31:"arg_directive",32:"close_directive"},productions_:[0,[3,2],[3,2],[3,2],[3,3],[7,0],[7,2],[9,2],[10,0],[10,2],[10,2],[10,2],[10,2],[10,1],[10,1],[10,1],[5,3],[5,5],[4,1],[4,1],[4,1],[21,1],[22,1],[25,1],[23,1]],performAction:function(de,ve,te,xe,De,he,Ie){var ee=he.length-1;switch(De){case 4:xe.setShowData(!0);break;case 7:this.$=he[ee-1];break;case 9:xe.addSection(he[ee-1],xe.cleanupValue(he[ee]));break;case 10:this.$=he[ee].trim(),xe.setDiagramTitle(this.$);break;case 11:this.$=he[ee].trim(),xe.setAccTitle(this.$);break;case 12:case 13:this.$=he[ee].trim(),xe.setAccDescription(this.$);break;case 14:xe.addSection(he[ee].substr(8)),this.$=he[ee].substr(8);break;case 21:xe.parseDirective("%%{","open_directive");break;case 22:xe.parseDirective(he[ee],"type_directive");break;case 23:he[ee]=he[ee].trim().replace(/'/g,'"'),xe.parseDirective(he[ee],"arg_directive");break;case 24:xe.parseDirective("}%%","close_directive","pie");break}},table:[{3:1,4:2,5:3,6:a,21:8,26:f,27:p,28:w,29:y},{1:[3]},{3:10,4:2,5:3,6:a,21:8,26:f,27:p,28:w,29:y},{3:11,4:2,5:3,6:a,21:8,26:f,27:p,28:w,29:y},i(b,E,{7:12,8:[1,13]}),i(S,[2,18]),i(S,[2,19]),i(S,[2,20]),{22:14,30:[1,15]},{30:[2,21]},{1:[2,1]},{1:[2,2]},i(N,B,{21:8,9:16,10:17,5:24,1:[2,3],11:R,13:j,15:$,17:V,19:Q,20:oe,29:y}),i(b,E,{7:25}),{23:26,24:[1,27],32:ce},i([24,32],[2,22]),i(b,[2,6]),{4:29,26:f,27:p,28:w},{12:[1,30]},{14:[1,31]},{16:[1,32]},{18:[1,33]},i(N,[2,13]),i(N,[2,14]),i(N,[2,15]),i(N,B,{21:8,9:16,10:17,5:24,1:[2,4],11:R,13:j,15:$,17:V,19:Q,20:oe,29:y}),i(se,[2,16]),{25:34,31:[1,35]},i(se,[2,24]),i(b,[2,7]),i(N,[2,9]),i(N,[2,10]),i(N,[2,11]),i(N,[2,12]),{23:36,32:ce},{32:[2,23]},i(se,[2,17])],defaultActions:{9:[2,21],10:[2,1],11:[2,2],35:[2,23]},parseError:function(de,ve){if(ve.recoverable)this.trace(de);else{var te=new Error(de);throw te.hash=ve,te}},parse:function(de){var ve=this,te=[0],xe=[],De=[null],he=[],Ie=this.table,ee="",rt=0,me=0,gt=2,pe=1,Et=he.slice.call(arguments,1),wt=Object.create(this.lexer),jt={yy:{}};for(var At in this.yy)Object.prototype.hasOwnProperty.call(this.yy,At)&&(jt.yy[At]=this.yy[At]);wt.setInput(de,jt.yy),jt.yy.lexer=wt,jt.yy.parser=this,typeof wt.yylloc>"u"&&(wt.yylloc={});var Bt=wt.yylloc;he.push(Bt);var cn=wt.options&&wt.options.ranges;typeof jt.yy.parseError=="function"?this.parseError=jt.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function Nn(){var Bn;return Bn=xe.pop()||wt.lex()||pe,typeof Bn!="number"&&(Bn instanceof Array&&(xe=Bn,Bn=xe.pop()),Bn=ve.symbols_[Bn]||Bn),Bn}for(var Ot,oi,kt,Dt,vt={},Nt,ze,Xe,Lt;;){if(oi=te[te.length-1],this.defaultActions[oi]?kt=this.defaultActions[oi]:((Ot===null||typeof Ot>"u")&&(Ot=Nn()),kt=Ie[oi]&&Ie[oi][Ot]),typeof kt>"u"||!kt.length||!kt[0]){var Ge="";Lt=[];for(Nt in Ie[oi])this.terminals_[Nt]&&Nt>gt&&Lt.push("'"+this.terminals_[Nt]+"'");wt.showPosition?Ge="Parse error on line "+(rt+1)+`: +`+wt.showPosition()+` +Expecting `+Lt.join(", ")+", got '"+(this.terminals_[Ot]||Ot)+"'":Ge="Parse error on line "+(rt+1)+": Unexpected "+(Ot==pe?"end of input":"'"+(this.terminals_[Ot]||Ot)+"'"),this.parseError(Ge,{text:wt.match,token:this.terminals_[Ot]||Ot,line:wt.yylineno,loc:Bt,expected:Lt})}if(kt[0]instanceof Array&&kt.length>1)throw new Error("Parse Error: multiple actions possible at state: "+oi+", token: "+Ot);switch(kt[0]){case 1:te.push(Ot),De.push(wt.yytext),he.push(wt.yylloc),te.push(kt[1]),Ot=null,me=wt.yyleng,ee=wt.yytext,rt=wt.yylineno,Bt=wt.yylloc;break;case 2:if(ze=this.productions_[kt[1]][1],vt.$=De[De.length-ze],vt._$={first_line:he[he.length-(ze||1)].first_line,last_line:he[he.length-1].last_line,first_column:he[he.length-(ze||1)].first_column,last_column:he[he.length-1].last_column},cn&&(vt._$.range=[he[he.length-(ze||1)].range[0],he[he.length-1].range[1]]),Dt=this.performAction.apply(vt,[ee,me,rt,jt.yy,kt[1],De,he].concat(Et)),typeof Dt<"u")return Dt;ze&&(te=te.slice(0,-1*ze*2),De=De.slice(0,-1*ze),he=he.slice(0,-1*ze)),te.push(this.productions_[kt[1]][0]),De.push(vt.$),he.push(vt._$),Xe=Ie[te[te.length-2]][te[te.length-1]],te.push(Xe);break;case 3:return!0}}return!0}},ye=function(){var Ae={EOF:1,parseError:function(ve,te){if(this.yy.parser)this.yy.parser.parseError(ve,te);else throw new Error(ve)},setInput:function(de,ve){return this.yy=ve||this.yy||{},this._input=de,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},input:function(){var de=this._input[0];this.yytext+=de,this.yyleng++,this.offset++,this.match+=de,this.matched+=de;var ve=de.match(/(?:\r\n?|\n).*/g);return ve?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),de},unput:function(de){var ve=de.length,te=de.split(/(?:\r\n?|\n)/g);this._input=de+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-ve),this.offset-=ve;var xe=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),te.length-1&&(this.yylineno-=te.length-1);var De=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:te?(te.length===xe.length?this.yylloc.first_column:0)+xe[xe.length-te.length].length-te[0].length:this.yylloc.first_column-ve},this.options.ranges&&(this.yylloc.range=[De[0],De[0]+this.yyleng-ve]),this.yyleng=this.yytext.length,this},more:function(){return this._more=!0,this},reject:function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true). +`+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},less:function(de){this.unput(this.match.slice(de))},pastInput:function(){var de=this.matched.substr(0,this.matched.length-this.match.length);return(de.length>20?"...":"")+de.substr(-20).replace(/\n/g,"")},upcomingInput:function(){var de=this.match;return de.length<20&&(de+=this._input.substr(0,20-de.length)),(de.substr(0,20)+(de.length>20?"...":"")).replace(/\n/g,"")},showPosition:function(){var de=this.pastInput(),ve=new Array(de.length+1).join("-");return de+this.upcomingInput()+` +`+ve+"^"},test_match:function(de,ve){var te,xe,De;if(this.options.backtrack_lexer&&(De={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(De.yylloc.range=this.yylloc.range.slice(0))),xe=de[0].match(/(?:\r\n?|\n).*/g),xe&&(this.yylineno+=xe.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:xe?xe[xe.length-1].length-xe[xe.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+de[0].length},this.yytext+=de[0],this.match+=de[0],this.matches=de,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(de[0].length),this.matched+=de[0],te=this.performAction.call(this,this.yy,this,ve,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),te)return te;if(this._backtrack){for(var he in De)this[he]=De[he];return!1}return!1},next:function(){if(this.done)return this.EOF;this._input||(this.done=!0);var de,ve,te,xe;this._more||(this.yytext="",this.match="");for(var De=this._currentRules(),he=0;heve[0].length)){if(ve=te,xe=he,this.options.backtrack_lexer){if(de=this.test_match(te,De[he]),de!==!1)return de;if(this._backtrack){ve=!1;continue}else return!1}else if(!this.options.flex)break}return ve?(de=this.test_match(ve,De[xe]),de!==!1?de:!1):this._input===""?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+`. 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28}},rules:[/^(?:%%\{)/i,/^(?:((?:(?!\}%%)[^:.])*))/i,/^(?::)/i,/^(?:\}%%)/i,/^(?:((?:(?!\}%%).|\n)*))/i,/^(?:%%(?!\{)[^\n]*)/i,/^(?:[^\}]%%[^\n]*)/i,/^(?:[\n\r]+)/i,/^(?:%%[^\n]*)/i,/^(?:[\s]+)/i,/^(?:title\b)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accTitle\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*\{\s*)/i,/^(?:[\}])/i,/^(?:[^\}]*)/i,/^(?:["])/i,/^(?:["])/i,/^(?:[^"]*)/i,/^(?:pie\b)/i,/^(?:showData\b)/i,/^(?::[\s]*[\d]+(?:\.[\d]+)?)/i,/^(?:$)/i],conditions:{acc_descr_multiline:{rules:[17,18],inclusive:!1},acc_descr:{rules:[15],inclusive:!1},acc_title:{rules:[13],inclusive:!1},close_directive:{rules:[],inclusive:!1},arg_directive:{rules:[3,4],inclusive:!1},type_directive:{rules:[2,3],inclusive:!1},open_directive:{rules:[1],inclusive:!1},title:{rules:[11],inclusive:!1},string:{rules:[20,21],inclusive:!1},INITIAL:{rules:[0,5,6,7,8,9,10,12,14,16,19,22,23,24,25],inclusive:!0}}};return Ae}();ge.lexer=ye;function ke(){this.yy={}}return 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${i.fontFamily}; + } + .slice { + font-family: ${i.fontFamily}; + fill: ${i.pieSectionTextColor}; + font-size:${i.pieSectionTextSize}; + // fill: white; + } + .legend text { + fill: ${i.pieLegendTextColor}; + font-family: ${i.fontFamily}; + font-size: ${i.pieLegendTextSize}; + } +`;let d3=Tt(),A5;const CP=450,A$t=Object.freeze(Object.defineProperty({__proto__:null,diagram:{parser:_$t,db:C$t,renderer:{draw:(i,a,f,p)=>{var ge;try{d3=Tt(),Fe.debug(`Rendering info diagram +`+i);const ye=Tt().securityLevel;let ke;ye==="sandbox"&&(ke=Cr("#i"+a));const Ae=Cr(ye==="sandbox"?ke.nodes()[0].contentDocument.body:"body"),de=ye==="sandbox"?ke.nodes()[0].contentDocument:document;p.db.clear(),p.parser.parse(i),Fe.debug("Parsed info diagram");const ve=de.getElementById(a);A5=ve.parentElement.offsetWidth,A5===void 0&&(A5=1200),d3.useWidth!==void 0&&(A5=d3.useWidth),d3.pie.useWidth!==void 0&&(A5=d3.pie.useWidth);const te=Ae.select("#"+a);Vw(te,CP,A5,d3.pie.useMaxWidth),ve.setAttribute("viewBox","0 0 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You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true). +`+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},less:function(kt){this.unput(this.match.slice(kt))},pastInput:function(){var kt=this.matched.substr(0,this.matched.length-this.match.length);return(kt.length>20?"...":"")+kt.substr(-20).replace(/\n/g,"")},upcomingInput:function(){var kt=this.match;return kt.length<20&&(kt+=this._input.substr(0,20-kt.length)),(kt.substr(0,20)+(kt.length>20?"...":"")).replace(/\n/g,"")},showPosition:function(){var kt=this.pastInput(),Dt=new Array(kt.length+1).join("-");return kt+this.upcomingInput()+` +`+Dt+"^"},test_match:function(kt,Dt){var vt,Nt,ze;if(this.options.backtrack_lexer&&(ze={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(ze.yylloc.range=this.yylloc.range.slice(0))),Nt=kt[0].match(/(?:\r\n?|\n).*/g),Nt&&(this.yylineno+=Nt.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:Nt?Nt[Nt.length-1].length-Nt[Nt.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+kt[0].length},this.yytext+=kt[0],this.match+=kt[0],this.matches=kt,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(kt[0].length),this.matched+=kt[0],vt=this.performAction.call(this,this.yy,this,Dt,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),vt)return vt;if(this._backtrack){for(var Xe in ze)this[Xe]=ze[Xe];return!1}return!1},next:function(){if(this.done)return this.EOF;this._input||(this.done=!0);var kt,Dt,vt,Nt;this._more||(this.yytext="",this.match="");for(var ze=this._currentRules(),Xe=0;XeDt[0].length)){if(Dt=vt,Nt=Xe,this.options.backtrack_lexer){if(kt=this.test_match(vt,ze[Xe]),kt!==!1)return kt;if(this._backtrack){Dt=!1;continue}else return!1}else if(!this.options.flex)break}return Dt?(kt=this.test_match(Dt,ze[Nt]),kt!==!1?kt:!1):this._input===""?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+`. Unrecognized text. +`+this.showPosition(),{text:"",token:null,line:this.yylineno})},lex:function(){var Dt=this.next();return Dt||this.lex()},begin:function(Dt){this.conditionStack.push(Dt)},popState:function(){var Dt=this.conditionStack.length-1;return Dt>0?this.conditionStack.pop():this.conditionStack[0]},_currentRules:function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},topState:function(Dt){return Dt=this.conditionStack.length-1-Math.abs(Dt||0),Dt>=0?this.conditionStack[Dt]:"INITIAL"},pushState:function(Dt){this.begin(Dt)},stateStackSize:function(){return this.conditionStack.length},options:{"case-insensitive":!0},performAction:function(Dt,vt,Nt,ze){switch(Nt){case 0:return this.begin("open_directive"),19;case 1:return this.begin("type_directive"),20;case 2:return this.popState(),this.begin("arg_directive"),12;case 3:return this.popState(),this.popState(),22;case 4:return 21;case 5:return"title";case 6:return this.begin("acc_title"),14;case 7:return this.popState(),"acc_title_value";case 8:return this.begin("acc_descr"),16;case 9:return this.popState(),"acc_descr_value";case 10:this.begin("acc_descr_multiline");break;case 11:this.popState();break;case 12:return"acc_descr_multiline_value";case 13:return 5;case 14:break;case 15:break;case 16:break;case 17:return 8;case 18:return 6;case 19:return 28;case 20:return 39;case 21:return 31;case 22:return 30;case 23:return 33;case 24:return 35;case 25:return 37;case 26:return 40;case 27:return 41;case 28:return 42;case 29:return 43;case 30:return 44;case 31:return 45;case 32:return 46;case 33:return 47;case 34:return 48;case 35:return 49;case 36:return 50;case 37:return 51;case 38:return 52;case 39:return 53;case 40:return 64;case 41:return 65;case 42:return 66;case 43:return 67;case 44:return 68;case 45:return 69;case 46:return 70;case 47:return 56;case 48:return 58;case 49:return 60;case 50:return 63;case 51:return 62;case 52:this.begin("string");break;case 53:this.popState();break;case 54:return"qString";case 55:return vt.yytext=vt.yytext.trim(),71}},rules:[/^(?:%%\{)/i,/^(?:((?:(?!\}%%)[^:.])*))/i,/^(?::)/i,/^(?:\}%%)/i,/^(?:((?:(?!\}%%).|\n)*))/i,/^(?:title\s[^#\n;]+)/i,/^(?:accTitle\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*\{\s*)/i,/^(?:[\}])/i,/^(?:[^\}]*)/i,/^(?:(\r?\n)+)/i,/^(?:\s+)/i,/^(?:#[^\n]*)/i,/^(?:%[^\n]*)/i,/^(?:$)/i,/^(?:requirementDiagram\b)/i,/^(?:\{)/i,/^(?:\})/i,/^(?::)/i,/^(?:id\b)/i,/^(?:text\b)/i,/^(?:risk\b)/i,/^(?:verifyMethod\b)/i,/^(?:requirement\b)/i,/^(?:functionalRequirement\b)/i,/^(?:interfaceRequirement\b)/i,/^(?:performanceRequirement\b)/i,/^(?:physicalRequirement\b)/i,/^(?:designConstraint\b)/i,/^(?:low\b)/i,/^(?:medium\b)/i,/^(?:high\b)/i,/^(?:analysis\b)/i,/^(?:demonstration\b)/i,/^(?:inspection\b)/i,/^(?:test\b)/i,/^(?:element\b)/i,/^(?:contains\b)/i,/^(?:copies\b)/i,/^(?:derives\b)/i,/^(?:satisfies\b)/i,/^(?:verifies\b)/i,/^(?:refines\b)/i,/^(?:traces\b)/i,/^(?:type\b)/i,/^(?:docref\b)/i,/^(?:<-)/i,/^(?:->)/i,/^(?:-)/i,/^(?:["])/i,/^(?:["])/i,/^(?:[^"]*)/i,/^(?:[\w][^\r\n\{\<\>\-\=]*)/i],conditions:{acc_descr_multiline:{rules:[11,12],inclusive:!1},acc_descr:{rules:[9],inclusive:!1},acc_title:{rules:[7],inclusive:!1},close_directive:{rules:[],inclusive:!1},arg_directive:{rules:[3,4],inclusive:!1},type_directive:{rules:[2,3],inclusive:!1},open_directive:{rules:[1],inclusive:!1},unqString:{rules:[],inclusive:!1},token:{rules:[],inclusive:!1},string:{rules:[53,54],inclusive:!1},INITIAL:{rules:[0,5,6,8,10,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,55],inclusive:!0}}};return oi}();cn.lexer=Nn;function Ot(){this.yy={}}return Ot.prototype=cn,cn.Parser=Ot,new Ot}();X0e.parser=X0e;const L$t=X0e;let Q0e=[],up={},SP={},ox={},AP={};const M$t={RequirementType:{REQUIREMENT:"Requirement",FUNCTIONAL_REQUIREMENT:"Functional Requirement",INTERFACE_REQUIREMENT:"Interface Requirement",PERFORMANCE_REQUIREMENT:"Performance Requirement",PHYSICAL_REQUIREMENT:"Physical Requirement",DESIGN_CONSTRAINT:"Design Constraint"},RiskLevel:{LOW_RISK:"Low",MED_RISK:"Medium",HIGH_RISK:"High"},VerifyType:{VERIFY_ANALYSIS:"Analysis",VERIFY_DEMONSTRATION:"Demonstration",VERIFY_INSPECTION:"Inspection",VERIFY_TEST:"Test"},Relationships:{CONTAINS:"contains",COPIES:"copies",DERIVES:"derives",SATISFIES:"satisfies",VERIFIES:"verifies",REFINES:"refines",TRACES:"traces"},parseDirective:function(i,a,f){rd.parseDirective(this,i,a,f)},getConfig:()=>Tt().req,addRequirement:(i,a)=>(SP[i]===void 0&&(SP[i]={name:i,type:a,id:up.id,text:up.text,risk:up.risk,verifyMethod:up.verifyMethod}),up={},SP[i]),getRequirements:()=>SP,setNewReqId:i=>{up!==void 0&&(up.id=i)},setNewReqText:i=>{up!==void 0&&(up.text=i)},setNewReqRisk:i=>{up!==void 0&&(up.risk=i)},setNewReqVerifyMethod:i=>{up!==void 0&&(up.verifyMethod=i)},setAccTitle:ip,getAccTitle:L2,setAccDescription:M2,getAccDescription:D2,addElement:i=>(AP[i]===void 0&&(AP[i]={name:i,type:ox.type,docRef:ox.docRef},Fe.info("Added new requirement: ",i)),ox={},AP[i]),getElements:()=>AP,setNewElementType:i=>{ox!==void 0&&(ox.type=i)},setNewElementDocRef:i=>{ox!==void 0&&(ox.docRef=i)},addRelationship:(i,a,f)=>{Q0e.push({type:i,src:a,dst:f})},getRelationships:()=>Q0e,clear:()=>{Q0e=[],up={},SP={},ox={},AP={},rp()}},D$t=i=>` + + marker { + fill: ${i.relationColor}; + stroke: ${i.relationColor}; + } + + marker.cross { + stroke: ${i.lineColor}; + } + + svg { + font-family: ${i.fontFamily}; + font-size: ${i.fontSize}; + } + + .reqBox { + fill: ${i.requirementBackground}; + fill-opacity: 1.0; + stroke: ${i.requirementBorderColor}; + stroke-width: ${i.requirementBorderSize}; + } + + .reqTitle, .reqLabel{ + fill: ${i.requirementTextColor}; + } + .reqLabelBox { + fill: ${i.relationLabelBackground}; + fill-opacity: 1.0; + } + + .req-title-line { + stroke: ${i.requirementBorderColor}; + stroke-width: ${i.requirementBorderSize}; + } + .relationshipLine { + stroke: ${i.relationColor}; + stroke-width: 1; + } + .relationshipLabel { + fill: ${i.relationLabelColor}; + } + +`,Z0e={CONTAINS:"contains",ARROW:"arrow"},MRe={ReqMarkers:Z0e,insertLineEndings:(i,a)=>{let f=i.append("defs").append("marker").attr("id",Z0e.CONTAINS+"_line_ending").attr("refX",0).attr("refY",a.line_height/2).attr("markerWidth",a.line_height).attr("markerHeight",a.line_height).attr("orient","auto").append("g");f.append("circle").attr("cx",a.line_height/2).attr("cy",a.line_height/2).attr("r",a.line_height/2).attr("fill","none"),f.append("line").attr("x1",0).attr("x2",a.line_height).attr("y1",a.line_height/2).attr("y2",a.line_height/2).attr("stroke-width",1),f.append("line").attr("y1",0).attr("y2",a.line_height).attr("x1",a.line_height/2).attr("x2",a.line_height/2).attr("stroke-width",1),i.append("defs").append("marker").attr("id",Z0e.ARROW+"_line_ending").attr("refX",a.line_height).attr("refY",.5*a.line_height).attr("markerWidth",a.line_height).attr("markerHeight",a.line_height).attr("orient","auto").append("path").attr("d",`M0,0 + L${a.line_height},${a.line_height/2} + M${a.line_height},${a.line_height/2} + L0,${a.line_height}`).attr("stroke-width",1)}};let Mh={},DRe=0;const IRe=(i,a)=>i.insert("rect","#"+a).attr("class","req reqBox").attr("x",0).attr("y",0).attr("width",Mh.rect_min_width+"px").attr("height",Mh.rect_min_height+"px"),ORe=(i,a,f)=>{let p=Mh.rect_min_width/2,w=i.append("text").attr("class","req reqLabel reqTitle").attr("id",a).attr("x",p).attr("y",Mh.rect_padding).attr("dominant-baseline","hanging"),y=0;f.forEach(N=>{y==0?w.append("tspan").attr("text-anchor","middle").attr("x",Mh.rect_min_width/2).attr("dy",0).text(N):w.append("tspan").attr("text-anchor","middle").attr("x",Mh.rect_min_width/2).attr("dy",Mh.line_height*.75).text(N),y++});let b=1.5*Mh.rect_padding,E=y*Mh.line_height*.75,S=b+E;return i.append("line").attr("class","req-title-line").attr("x1","0").attr("x2",Mh.rect_min_width).attr("y1",S).attr("y2",S),{titleNode:w,y:S}},NRe=(i,a,f,p)=>{let w=i.append("text").attr("class","req reqLabel").attr("id",a).attr("x",Mh.rect_padding).attr("y",p).attr("dominant-baseline","hanging"),y=0;const b=30;let E=[];return f.forEach(S=>{let N=S.length;for(;N>b&&y<3;){let B=S.substring(0,b);S=S.substring(b,S.length),N=S.length,E[E.length]=B,y++}if(y==3){let B=E[E.length-1];E[E.length-1]=B.substring(0,B.length-4)+"..."}else E[E.length]=S;y=0}),E.forEach(S=>{w.append("tspan").attr("x",Mh.rect_padding).attr("dy",Mh.line_height).text(S)}),w},I$t=(i,a,f,p)=>{const w=a.node().getTotalLength(),y=a.node().getPointAtLength(w*.5),b="rel"+DRe;DRe++;const S=i.append("text").attr("class","req relationshipLabel").attr("id",b).attr("x",y.x).attr("y",y.y).attr("text-anchor","middle").attr("dominant-baseline","middle").text(p).node().getBBox();i.insert("rect","#"+b).attr("class","req reqLabelBox").attr("x",y.x-S.width/2).attr("y",y.y-S.height/2).attr("width",S.width).attr("height",S.height).attr("fill","white").attr("fill-opacity","85%")},O$t=function(i,a,f,p,w){const y=f.edge(oL(a.src),oL(a.dst)),b=WE().x(function(S){return S.x}).y(function(S){return S.y}),E=i.insert("path","#"+p).attr("class","er relationshipLine").attr("d",b(y.points)).attr("fill","none");a.type==w.db.Relationships.CONTAINS?E.attr("marker-start","url("+Wa.getUrl(Mh.arrowMarkerAbsolute)+"#"+a.type+"_line_ending)"):(E.attr("stroke-dasharray","10,7"),E.attr("marker-end","url("+Wa.getUrl(Mh.arrowMarkerAbsolute)+"#"+MRe.ReqMarkers.ARROW+"_line_ending)")),I$t(i,E,Mh,`<<${a.type}>>`)},N$t=(i,a,f)=>{Object.keys(i).forEach(p=>{let w=i[p];p=oL(p),Fe.info("Added new requirement: ",p);const y=f.append("g").attr("id",p),b="req-"+p,E=IRe(y,b);let S=ORe(y,p+"_title",[`<<${w.type}>>`,`${w.name}`]);NRe(y,p+"_body",[`Id: ${w.id}`,`Text: ${w.text}`,`Risk: ${w.risk}`,`Verification: ${w.verifyMethod}`],S.y);const N=E.node().getBBox();a.setNode(p,{width:N.width,height:N.height,shape:"rect",id:p})})},P$t=(i,a,f)=>{Object.keys(i).forEach(p=>{let w=i[p];const y=oL(p),b=f.append("g").attr("id",y),E="element-"+y,S=IRe(b,E);let N=ORe(b,E+"_title",["<>",`${p}`]);NRe(b,E+"_body",[`Type: ${w.type||"Not Specified"}`,`Doc Ref: 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zf({multigraph:!1,compound:!1,directed:!0}).setGraph({rankdir:Mh.layoutDirection,marginx:20,marginy:20,nodesep:100,edgesep:100,ranksep:100}).setDefaultEdgeLabel(function(){return{}});let N=p.db.getRequirements(),B=p.db.getElements(),R=p.db.getRelationships();N$t(N,S,E),P$t(B,S,E),B$t(R,S),tL(S),R$t(E,S),R.forEach(function(oe){O$t(E,oe,S,a,p)});const j=Mh.rect_padding,$=E.node().getBBox(),V=$.width+j*2,Q=$.height+j*2;Vw(E,Q,V,Mh.useMaxWidth),E.attr("viewBox",`${$.x-j} ${$.y-j} ${V} ${Q}`)}},styles:D$t}},Symbol.toStringTag,{value:"Module"}));var J0e=function(){var i=function(Dt,vt,Nt,ze){for(Nt=Nt||{},ze=Dt.length;ze--;Nt[Dt[ze]]=vt);return 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66:this.$=[Ge[Oe-4],Ge[Oe-1],{type:"addMessage",from:Ge[Oe-4].actor,to:Ge[Oe-1].actor,signalType:Ge[Oe-3],msg:Ge[Oe]},{type:"activeStart",signalType:Xe.LINETYPE.ACTIVE_START,actor:Ge[Oe-1]}];break;case 67:this.$=[Ge[Oe-4],Ge[Oe-1],{type:"addMessage",from:Ge[Oe-4].actor,to:Ge[Oe-1].actor,signalType:Ge[Oe-3],msg:Ge[Oe]},{type:"activeEnd",signalType:Xe.LINETYPE.ACTIVE_END,actor:Ge[Oe-4]}];break;case 68:this.$=[Ge[Oe-3],Ge[Oe-1],{type:"addMessage",from:Ge[Oe-3].actor,to:Ge[Oe-1].actor,signalType:Ge[Oe-2],msg:Ge[Oe]}];break;case 69:this.$={type:"addParticipant",actor:Ge[Oe]};break;case 70:this.$=Xe.LINETYPE.SOLID_OPEN;break;case 71:this.$=Xe.LINETYPE.DOTTED_OPEN;break;case 72:this.$=Xe.LINETYPE.SOLID;break;case 73:this.$=Xe.LINETYPE.DOTTED;break;case 74:this.$=Xe.LINETYPE.SOLID_CROSS;break;case 75:this.$=Xe.LINETYPE.DOTTED_CROSS;break;case 76:this.$=Xe.LINETYPE.SOLID_POINT;break;case 77:this.$=Xe.LINETYPE.DOTTED_POINT;break;case 78:this.$=Xe.parseMessage(Ge[Oe].trim().substring(1));break;case 79:Xe.parseDirective("%%{","open_directive");break;case 80:Xe.parseDirective(Ge[Oe],"type_directive");break;case 81:Ge[Oe]=Ge[Oe].trim().replace(/'/g,'"'),Xe.parseDirective(Ge[Oe],"arg_directive");break;case 82:Xe.parseDirective("}%%","close_directive","sequence");break}},table:[{3:1,4:a,5:f,6:4,7:p,14:6,83:w},{1:[3]},{3:8,4:a,5:f,6:4,7:p,14:6,83:w},{3:9,4:a,5:f,6:4,7:p,14:6,83:w},{3:10,4:a,5:f,6:4,7:p,14:6,83:w},i([1,4,5,19,23,26,28,34,35,36,38,40,41,42,43,44,46,48,50,54,56,57,62,63,64,65,73,83],y,{8:11}),{15:12,84:[1,13]},{84:[2,79]},{1:[2,1]},{1:[2,2]},{1:[2,3]},{1:[2,4],4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{16:51,17:[1,52],86:me},i([17,86],[2,80]),i(gt,[2,6]),{6:41,10:54,13:18,14:6,19:S,22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},i(gt,[2,8]),i(gt,[2,9]),i(gt,[2,17]),{20:[1,55]},{5:[1,56]},{5:[1,59],24:[1,57],25:[1,58]},{27:60,73:rt},{27:61,73:rt},{5:[1,62]},{5:[1,63]},{5:[1,64]},{5:[1,65]},{5:[1,66]},i(gt,[2,31]),i(gt,[2,32]),{37:[1,67]},{39:[1,68]},i(gt,[2,35]),{20:[1,69]},{20:[1,70]},{20:[1,71]},{20:[1,72]},{20:[1,73]},{20:[1,74]},{20:[1,75]},i(gt,[2,43]),{27:76,73:rt},{27:77,73:rt},{70:78,74:[1,79],75:[1,80],76:[1,81],77:[1,82],78:[1,83],79:[1,84],80:[1,85],81:[1,86]},{58:87,60:[1,88],68:[1,89],69:[1,90]},{27:91,73:rt},{27:92,73:rt},{27:93,73:rt},{27:94,73:rt},i([5,55,67,74,75,76,77,78,79,80,81,82],[2,69]),{5:[1,95]},{18:96,85:[1,97]},{5:[2,82]},i(gt,[2,7]),i(pe,[2,10],{11:98}),i(gt,[2,19]),{5:[1,100],24:[1,99]},{5:[1,101]},i(gt,[2,23]),{5:[1,102]},{5:[1,103]},i(gt,[2,26]),i(gt,[2,27]),i(gt,[2,28]),i(gt,[2,29]),i(gt,[2,30]),i(gt,[2,33]),i(gt,[2,34]),i(Et,y,{8:104}),i(Et,y,{8:105}),i(Et,y,{8:106}),i(wt,y,{45:107,8:108}),i(jt,y,{47:109,8:110}),i(At,y,{49:111,8:112}),i(Et,y,{8:113}),{5:[1,115],55:[1,114]},{5:[1,117],55:[1,116]},{27:120,71:[1,118],72:[1,119],73:rt},i(Bt,[2,70]),i(Bt,[2,71]),i(Bt,[2,72]),i(Bt,[2,73]),i(Bt,[2,74]),i(Bt,[2,75]),i(Bt,[2,76]),i(Bt,[2,77]),{27:121,73:rt},{27:123,61:122,73:rt},{73:[2,64]},{73:[2,65]},{59:124,82:cn},{59:126,82:cn},{59:127,82:cn},{59:128,82:cn},i(Nn,[2,15]),{16:129,86:me},{86:[2,81]},{4:[1,132],5:[1,134],12:131,13:133,21:[1,130],54:ve,56:te},{5:[1,135]},i(gt,[2,21]),i(gt,[2,22]),i(gt,[2,24]),i(gt,[2,25]),{4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,21:[1,136],22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,21:[1,137],22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,21:[1,138],22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{21:[1,139]},{4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,21:[2,48],22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,53:[1,140],54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{21:[1,141]},{4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,21:[2,46],22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,52:[1,142],54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{21:[1,143]},{4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,21:[2,44],22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,51:[1,144],54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{4:b,5:E,6:41,9:14,10:16,13:18,14:6,19:S,21:[1,145],22:20,23:N,26:B,27:44,28:R,29:24,30:25,31:26,32:27,33:28,34:j,35:$,36:V,38:Q,40:oe,41:ce,42:se,43:ge,44:ye,46:ke,48:Ae,50:de,54:ve,56:te,57:xe,62:De,63:he,64:Ie,65:ee,73:rt,83:w},{20:[1,146]},i(gt,[2,51]),{20:[1,147]},i(gt,[2,53]),{27:148,73:rt},{27:149,73:rt},{59:150,82:cn},{59:151,82:cn},{59:152,82:cn},{67:[1,153],82:[2,63]},{5:[2,56]},{5:[2,78]},{5:[2,57]},{5:[2,58]},{5:[2,59]},{5:[1,154]},i(gt,[2,18]),i(pe,[2,11]),{13:155,54:ve,56:te},i(pe,[2,13]),i(pe,[2,14]),i(gt,[2,20]),i(gt,[2,36]),i(gt,[2,37]),i(gt,[2,38]),i(gt,[2,39]),{20:[1,156]},i(gt,[2,40]),{20:[1,157]},i(gt,[2,41]),{20:[1,158]},i(gt,[2,42]),{5:[1,159]},{5:[1,160]},{59:161,82:cn},{59:162,82:cn},{5:[2,68]},{5:[2,54]},{5:[2,55]},{27:163,73:rt},i(Nn,[2,16]),i(pe,[2,12]),i(wt,y,{8:108,45:164}),i(jt,y,{8:110,47:165}),i(At,y,{8:112,49:166}),i(gt,[2,50]),i(gt,[2,52]),{5:[2,66]},{5:[2,67]},{82:[2,62]},{21:[2,49]},{21:[2,47]},{21:[2,45]}],defaultActions:{7:[2,79],8:[2,1],9:[2,2],10:[2,3],53:[2,82],89:[2,64],90:[2,65],97:[2,81],124:[2,56],125:[2,78],126:[2,57],127:[2,58],128:[2,59],150:[2,68],151:[2,54],152:[2,55],161:[2,66],162:[2,67],163:[2,62],164:[2,49],165:[2,47],166:[2,45]},parseError:function(vt,Nt){if(Nt.recoverable)this.trace(vt);else{var ze=new Error(vt);throw ze.hash=Nt,ze}},parse:function(vt){var Nt=this,ze=[0],Xe=[],Lt=[null],Ge=[],Bn=this.table,Oe="",Ri=0,tn=0,hi=2,Sr=1,Zn=Ge.slice.call(arguments,1),Xn=Object.create(this.lexer),ir={yy:{}};for(var Hn in this.yy)Object.prototype.hasOwnProperty.call(this.yy,Hn)&&(ir.yy[Hn]=this.yy[Hn]);Xn.setInput(vt,ir.yy),ir.yy.lexer=Xn,ir.yy.parser=this,typeof Xn.yylloc>"u"&&(Xn.yylloc={});var tr=Xn.yylloc;Ge.push(tr);var ha=Xn.options&&Xn.options.ranges;typeof ir.yy.parseError=="function"?this.parseError=ir.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function Zs(){var Vn;return Vn=Xe.pop()||Xn.lex()||Sr,typeof Vn!="number"&&(Vn instanceof Array&&(Xe=Vn,Vn=Xe.pop()),Vn=Nt.symbols_[Vn]||Vn),Vn}for(var ns,Hi,Js,Pc,Ga={},ws,Oi,Er,br;;){if(Hi=ze[ze.length-1],this.defaultActions[Hi]?Js=this.defaultActions[Hi]:((ns===null||typeof ns>"u")&&(ns=Zs()),Js=Bn[Hi]&&Bn[Hi][ns]),typeof Js>"u"||!Js.length||!Js[0]){var Dr="";br=[];for(ws in Bn[Hi])this.terminals_[ws]&&ws>hi&&br.push("'"+this.terminals_[ws]+"'");Xn.showPosition?Dr="Parse error on line "+(Ri+1)+`: +`+Xn.showPosition()+` +Expecting `+br.join(", ")+", got '"+(this.terminals_[ns]||ns)+"'":Dr="Parse error on line "+(Ri+1)+": Unexpected "+(ns==Sr?"end of input":"'"+(this.terminals_[ns]||ns)+"'"),this.parseError(Dr,{text:Xn.match,token:this.terminals_[ns]||ns,line:Xn.yylineno,loc:tr,expected:br})}if(Js[0]instanceof Array&&Js.length>1)throw new Error("Parse Error: multiple actions possible at state: "+Hi+", token: "+ns);switch(Js[0]){case 1:ze.push(ns),Lt.push(Xn.yytext),Ge.push(Xn.yylloc),ze.push(Js[1]),ns=null,tn=Xn.yyleng,Oe=Xn.yytext,Ri=Xn.yylineno,tr=Xn.yylloc;break;case 2:if(Oi=this.productions_[Js[1]][1],Ga.$=Lt[Lt.length-Oi],Ga._$={first_line:Ge[Ge.length-(Oi||1)].first_line,last_line:Ge[Ge.length-1].last_line,first_column:Ge[Ge.length-(Oi||1)].first_column,last_column:Ge[Ge.length-1].last_column},ha&&(Ga._$.range=[Ge[Ge.length-(Oi||1)].range[0],Ge[Ge.length-1].range[1]]),Pc=this.performAction.apply(Ga,[Oe,tn,Ri,ir.yy,Js[1],Lt,Ge].concat(Zn)),typeof Pc<"u")return Pc;Oi&&(ze=ze.slice(0,-1*Oi*2),Lt=Lt.slice(0,-1*Oi),Ge=Ge.slice(0,-1*Oi)),ze.push(this.productions_[Js[1]][0]),Lt.push(Ga.$),Ge.push(Ga._$),Er=Bn[ze[ze.length-2]][ze[ze.length-1]],ze.push(Er);break;case 3:return!0}}return!0}},oi=function(){var Dt={EOF:1,parseError:function(Nt,ze){if(this.yy.parser)this.yy.parser.parseError(Nt,ze);else throw new Error(Nt)},setInput:function(vt,Nt){return this.yy=Nt||this.yy||{},this._input=vt,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},input:function(){var vt=this._input[0];this.yytext+=vt,this.yyleng++,this.offset++,this.match+=vt,this.matched+=vt;var Nt=vt.match(/(?:\r\n?|\n).*/g);return Nt?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),vt},unput:function(vt){var Nt=vt.length,ze=vt.split(/(?:\r\n?|\n)/g);this._input=vt+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-Nt),this.offset-=Nt;var Xe=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),ze.length-1&&(this.yylineno-=ze.length-1);var Lt=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:ze?(ze.length===Xe.length?this.yylloc.first_column:0)+Xe[Xe.length-ze.length].length-ze[0].length:this.yylloc.first_column-Nt},this.options.ranges&&(this.yylloc.range=[Lt[0],Lt[0]+this.yyleng-Nt]),this.yyleng=this.yytext.length,this},more:function(){return this._more=!0,this},reject:function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true). +`+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},less:function(vt){this.unput(this.match.slice(vt))},pastInput:function(){var vt=this.matched.substr(0,this.matched.length-this.match.length);return(vt.length>20?"...":"")+vt.substr(-20).replace(/\n/g,"")},upcomingInput:function(){var vt=this.match;return vt.length<20&&(vt+=this._input.substr(0,20-vt.length)),(vt.substr(0,20)+(vt.length>20?"...":"")).replace(/\n/g,"")},showPosition:function(){var vt=this.pastInput(),Nt=new Array(vt.length+1).join("-");return vt+this.upcomingInput()+` +`+Nt+"^"},test_match:function(vt,Nt){var ze,Xe,Lt;if(this.options.backtrack_lexer&&(Lt={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(Lt.yylloc.range=this.yylloc.range.slice(0))),Xe=vt[0].match(/(?:\r\n?|\n).*/g),Xe&&(this.yylineno+=Xe.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:Xe?Xe[Xe.length-1].length-Xe[Xe.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+vt[0].length},this.yytext+=vt[0],this.match+=vt[0],this.matches=vt,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(vt[0].length),this.matched+=vt[0],ze=this.performAction.call(this,this.yy,this,Nt,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),ze)return ze;if(this._backtrack){for(var Ge in Lt)this[Ge]=Lt[Ge];return!1}return!1},next:function(){if(this.done)return this.EOF;this._input||(this.done=!0);var vt,Nt,ze,Xe;this._more||(this.yytext="",this.match="");for(var Lt=this._currentRules(),Ge=0;GeNt[0].length)){if(Nt=ze,Xe=Ge,this.options.backtrack_lexer){if(vt=this.test_match(ze,Lt[Ge]),vt!==!1)return vt;if(this._backtrack){Nt=!1;continue}else return!1}else if(!this.options.flex)break}return Nt?(vt=this.test_match(Nt,Lt[Xe]),vt!==!1?vt:!1):this._input===""?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+`. Unrecognized text. +`+this.showPosition(),{text:"",token:null,line:this.yylineno})},lex:function(){var Nt=this.next();return Nt||this.lex()},begin:function(Nt){this.conditionStack.push(Nt)},popState:function(){var Nt=this.conditionStack.length-1;return Nt>0?this.conditionStack.pop():this.conditionStack[0]},_currentRules:function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},topState:function(Nt){return Nt=this.conditionStack.length-1-Math.abs(Nt||0),Nt>=0?this.conditionStack[Nt]:"INITIAL"},pushState:function(Nt){this.begin(Nt)},stateStackSize:function(){return this.conditionStack.length},options:{"case-insensitive":!0},performAction:function(Nt,ze,Xe,Lt){switch(Xe){case 0:return this.begin("open_directive"),83;case 1:return this.begin("type_directive"),84;case 2:return this.popState(),this.begin("arg_directive"),17;case 3:return this.popState(),this.popState(),86;case 4:return 85;case 5:return 5;case 6:break;case 7:break;case 8:break;case 9:break;case 10:break;case 11:return 24;case 12:return this.begin("LINE"),19;case 13:return this.begin("ID"),54;case 14:return this.begin("ID"),56;case 15:return ze.yytext=ze.yytext.trim(),this.begin("ALIAS"),73;case 16:return this.popState(),this.popState(),this.begin("LINE"),55;case 17:return this.popState(),this.popState(),5;case 18:return this.begin("LINE"),41;case 19:return this.begin("LINE"),42;case 20:return this.begin("LINE"),43;case 21:return this.begin("LINE"),44;case 22:return this.begin("LINE"),53;case 23:return this.begin("LINE"),46;case 24:return this.begin("LINE"),52;case 25:return this.begin("LINE"),48;case 26:return this.begin("LINE"),51;case 27:return this.begin("LINE"),50;case 28:return this.popState(),20;case 29:return 21;case 30:return 68;case 31:return 69;case 32:return 62;case 33:return 63;case 34:return 64;case 35:return 65;case 36:return 60;case 37:return 57;case 38:return this.begin("ID"),26;case 39:return this.begin("ID"),28;case 40:return 34;case 41:return 35;case 42:return this.begin("acc_title"),36;case 43:return this.popState(),"acc_title_value";case 44:return this.begin("acc_descr"),38;case 45:return this.popState(),"acc_descr_value";case 46:this.begin("acc_descr_multiline");break;case 47:this.popState();break;case 48:return"acc_descr_multiline_value";case 49:return 7;case 50:return 23;case 51:return 25;case 52:return 67;case 53:return 5;case 54:return ze.yytext=ze.yytext.trim(),73;case 55:return 76;case 56:return 77;case 57:return 74;case 58:return 75;case 59:return 78;case 60:return 79;case 61:return 80;case 62:return 81;case 63:return 82;case 64:return 71;case 65:return 72;case 66:return 5;case 67:return"INVALID"}},rules:[/^(?:%%\{)/i,/^(?:((?:(?!\}%%)[^:.])*))/i,/^(?::)/i,/^(?:\}%%)/i,/^(?:((?:(?!\}%%).|\n)*))/i,/^(?:[\n]+)/i,/^(?:\s+)/i,/^(?:((?!\n)\s)+)/i,/^(?:#[^\n]*)/i,/^(?:%(?!\{)[^\n]*)/i,/^(?:[^\}]%%[^\n]*)/i,/^(?:[0-9]+(?=[ \n]+))/i,/^(?:box\b)/i,/^(?:participant\b)/i,/^(?:actor\b)/i,/^(?:[^\->:\n,;]+?([\-]*[^\->:\n,;]+?)*?(?=((?!\n)\s)+as(?!\n)\s|[#\n;]|$))/i,/^(?:as\b)/i,/^(?:(?:))/i,/^(?:loop\b)/i,/^(?:rect\b)/i,/^(?:opt\b)/i,/^(?:alt\b)/i,/^(?:else\b)/i,/^(?:par\b)/i,/^(?:and\b)/i,/^(?:critical\b)/i,/^(?:option\b)/i,/^(?:break\b)/i,/^(?:(?:[:]?(?:no)?wrap)?[^#\n;]*)/i,/^(?:end\b)/i,/^(?:left of\b)/i,/^(?:right of\b)/i,/^(?:links\b)/i,/^(?:link\b)/i,/^(?:properties\b)/i,/^(?:details\b)/i,/^(?:over\b)/i,/^(?:note\b)/i,/^(?:activate\b)/i,/^(?:deactivate\b)/i,/^(?:title\s[^#\n;]+)/i,/^(?:title:\s[^#\n;]+)/i,/^(?:accTitle\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*\{\s*)/i,/^(?:[\}])/i,/^(?:[^\}]*)/i,/^(?:sequenceDiagram\b)/i,/^(?:autonumber\b)/i,/^(?:off\b)/i,/^(?:,)/i,/^(?:;)/i,/^(?:[^\+\->:\n,;]+((?!(-x|--x|-\)|--\)))[\-]*[^\+\->:\n,;]+)*)/i,/^(?:->>)/i,/^(?:-->>)/i,/^(?:->)/i,/^(?:-->)/i,/^(?:-[x])/i,/^(?:--[x])/i,/^(?:-[\)])/i,/^(?:--[\)])/i,/^(?::(?:(?:no)?wrap)?[^#\n;]+)/i,/^(?:\+)/i,/^(?:-)/i,/^(?:$)/i,/^(?:.)/i],conditions:{acc_descr_multiline:{rules:[47,48],inclusive:!1},acc_descr:{rules:[45],inclusive:!1},acc_title:{rules:[43],inclusive:!1},open_directive:{rules:[1,8],inclusive:!1},type_directive:{rules:[2,3,8],inclusive:!1},arg_directive:{rules:[3,4,8],inclusive:!1},ID:{rules:[7,8,15],inclusive:!1},ALIAS:{rules:[7,8,16,17],inclusive:!1},LINE:{rules:[7,8,28],inclusive:!1},INITIAL:{rules:[0,5,6,8,9,10,11,12,13,14,18,19,20,21,22,23,24,25,26,27,29,30,31,32,33,34,35,36,37,38,39,40,41,42,44,46,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],inclusive:!0}}};return Dt}();Ot.lexer=oi;function kt(){this.yy={}}return kt.prototype=Ot,Ot.Parser=kt,new kt}();J0e.parser=J0e;const j$t=J0e;let LP,cx={},cL=[],rm=[],LK=!1,ege,L5;const $$t=function(i,a,f){rd.parseDirective(this,i,a,f)},H$t=function(i){cL.push({name:i.text,wrap:i.wrap===void 0&&d9()||!!i.wrap,fill:i.color,actorKeys:[]}),L5=cL.slice(-1)[0]},tge=function(i,a,f,p){let w=L5;const y=cx[i];if(y){if(L5&&y.box&&L5!==y.box)throw new Error("A same participant should only be defined in one Box: "+y.name+" can't be in '"+y.box.name+"' and in '"+L5.name+"' at the same time.");if(w=y.box?y.box:L5,y.box=w,y&&a===y.name&&f==null)return}(f==null||f.text==null)&&(f={text:a,wrap:null,type:p}),(p==null||f.text==null)&&(f={text:a,wrap:null,type:p}),cx[i]={box:w,name:a,description:f.text,wrap:f.wrap===void 0&&d9()||!!f.wrap,prevActor:LP,links:{},properties:{},actorCnt:null,rectData:null,type:p||"participant"},LP&&cx[LP]&&(cx[LP].nextActor=i),L5&&L5.actorKeys.push(i),LP=i},z$t=i=>{let a,f=0;for(a=0;a>-",token:"->>-",line:"1",loc:{first_line:1,last_line:1,first_column:1,last_column:1},expected:["'ACTIVE_PARTICIPANT'"]},y}return rm.push({from:i,to:a,message:f.text,wrap:f.wrap===void 0&&d9()||!!f.wrap,type:p}),!0},q$t=function(){return cL.length>0},V$t=function(){return cL.some(i=>i.name)},U$t=function(){return rm},W$t=function(){return cL},K$t=function(){return cx},MP=function(i){return cx[i]},Y$t=function(){return Object.keys(cx)},X$t=function(){LK=!0},Q$t=function(){LK=!1},Z$t=()=>LK,J$t=function(i){ege=i},d9=()=>ege!==void 0?ege:Tt().sequence.wrap,eHt=function(){cx={},cL=[],rm=[],LK=!1,rp()},tHt=function(i){const a=i.trim(),f={text:a.replace(/^:?(?:no)?wrap:/,"").trim(),wrap:a.match(/^:?wrap:/)!==null?!0:a.match(/^:?nowrap:/)!==null?!1:void 0};return Fe.debug("parseMessage:",f),f},nHt=function(i){const a=i.match(/^((?:rgba?|hsla?)\s*\(.*\)|\w*)(.*)$/);let f=a!=null&&a[1]?a[1].trim():"transparent",p=a!=null&&a[2]?a[2].trim():void 0;if(window&&window.CSS)window.CSS.supports("color",f)||(f="transparent",p=i.trim());else{const y=new Option().style;y.color=f,y.color!==f&&(f="transparent",p=i.trim())}return{color:f,text:p!==void 0?ep(p.replace(/^:?(?:no)?wrap:/,""),Tt()):void 0,wrap:p!==void 0?p.match(/^:?wrap:/)!==null?!0:p.match(/^:?nowrap:/)!==null?!1:void 0:void 0}},DP={SOLID:0,DOTTED:1,NOTE:2,SOLID_CROSS:3,DOTTED_CROSS:4,SOLID_OPEN:5,DOTTED_OPEN:6,LOOP_START:10,LOOP_END:11,ALT_START:12,ALT_ELSE:13,ALT_END:14,OPT_START:15,OPT_END:16,ACTIVE_START:17,ACTIVE_END:18,PAR_START:19,PAR_AND:20,PAR_END:21,RECT_START:22,RECT_END:23,SOLID_POINT:24,DOTTED_POINT:25,AUTONUMBER:26,CRITICAL_START:27,CRITICAL_OPTION:28,CRITICAL_END:29,BREAK_START:30,BREAK_END:31},rHt={FILLED:0,OPEN:1},iHt={LEFTOF:0,RIGHTOF:1,OVER:2},PRe=function(i,a,f){f.text,f.wrap===void 0&&d9()||f.wrap;const p=[].concat(i,i);rm.push({from:p[0],to:p[1],message:f.text,wrap:f.wrap===void 0&&d9()||!!f.wrap,type:DP.NOTE,placement:a})},BRe=function(i,a){const f=MP(i);try{let p=ep(a.text,Tt());p=p.replace(/&/g,"&"),p=p.replace(/=/g,"=");const w=JSON.parse(p);nge(f,w)}catch(p){Fe.error("error while parsing actor link text",p)}},sHt=function(i,a){const f=MP(i);try{const b={};let E=ep(a.text,Tt());var p=E.indexOf("@");E=E.replace(/&/g,"&"),E=E.replace(/=/g,"=");var w=E.slice(0,p-1).trim(),y=E.slice(p+1).trim();b[w]=y,nge(f,b)}catch(b){Fe.error("error while parsing actor link text",b)}};function nge(i,a){if(i.links==null)i.links=a;else for(let f in a)i.links[f]=a[f]}const RRe=function(i,a){const f=MP(i);try{let p=ep(a.text,Tt());const w=JSON.parse(p);FRe(f,w)}catch(p){Fe.error("error while parsing actor properties text",p)}};function FRe(i,a){if(i.properties==null)i.properties=a;else for(let f in a)i.properties[f]=a[f]}function aHt(){L5=void 0}const jRe=function(i,a){const f=MP(i),p=document.getElementById(a.text);try{const w=p.innerHTML,y=JSON.parse(w);y.properties&&FRe(f,y.properties),y.links&&nge(f,y.links)}catch(w){Fe.error("error while 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0,void 0,i.loopText,i.signalType);break;case"loopEnd":lf(void 0,void 0,void 0,i.signalType);break;case"rectStart":lf(void 0,void 0,i.color,i.signalType);break;case"rectEnd":lf(void 0,void 0,void 0,i.signalType);break;case"optStart":lf(void 0,void 0,i.optText,i.signalType);break;case"optEnd":lf(void 0,void 0,void 0,i.signalType);break;case"altStart":lf(void 0,void 0,i.altText,i.signalType);break;case"else":lf(void 0,void 0,i.altText,i.signalType);break;case"altEnd":lf(void 0,void 0,void 0,i.signalType);break;case"setAccTitle":ip(i.text);break;case"parStart":lf(void 0,void 0,i.parText,i.signalType);break;case"and":lf(void 0,void 0,i.parText,i.signalType);break;case"parEnd":lf(void 0,void 0,void 0,i.signalType);break;case"criticalStart":lf(void 0,void 0,i.criticalText,i.signalType);break;case"option":lf(void 0,void 0,i.optionText,i.signalType);break;case"criticalEnd":lf(void 0,void 0,void 0,i.signalType);break;case"breakStart":lf(void 0,void 0,i.breakText,i.signalType);break;case"breakEnd":lf(void 0,void 0,void 0,i.signalType);break}},cHt={addActor:tge,addMessage:G$t,addSignal:lf,addLinks:BRe,addDetails:jRe,addProperties:RRe,autoWrap:d9,setWrap:J$t,enableSequenceNumbers:X$t,disableSequenceNumbers:Q$t,showSequenceNumbers:Z$t,getMessages:U$t,getActors:K$t,getActor:MP,getActorKeys:Y$t,getActorProperty:oHt,getAccTitle:L2,getBoxes:W$t,getDiagramTitle:Ww,setDiagramTitle:Uw,parseDirective:$$t,getConfig:()=>Tt().sequence,clear:eHt,parseMessage:tHt,parseBoxData:nHt,LINETYPE:DP,ARROWTYPE:rHt,PLACEMENT:iHt,addNote:PRe,setAccTitle:ip,apply:$Re,setAccDescription:M2,getAccDescription:D2,hasAtLeastOneBox:q$t,hasAtLeastOneBoxWithTitle:V$t},uHt=i=>`.actor { + stroke: ${i.actorBorder}; + fill: ${i.actorBkg}; + } + + text.actor > tspan { + fill: ${i.actorTextColor}; + stroke: none; + } + + .actor-line { + stroke: ${i.actorLineColor}; + } + + .messageLine0 { + stroke-width: 1.5; + stroke-dasharray: none; + stroke: ${i.signalColor}; + } + + .messageLine1 { + stroke-width: 1.5; + stroke-dasharray: 2, 2; + stroke: ${i.signalColor}; + } + + #arrowhead path { + fill: ${i.signalColor}; + stroke: ${i.signalColor}; + } + + .sequenceNumber { + fill: ${i.sequenceNumberColor}; + } + + #sequencenumber { + fill: ${i.signalColor}; + } + + #crosshead path { + fill: ${i.signalColor}; + stroke: ${i.signalColor}; + } + + .messageText { + fill: ${i.signalTextColor}; + stroke: none; + } + + .labelBox { + stroke: ${i.labelBoxBorderColor}; + fill: ${i.labelBoxBkgColor}; + } + + .labelText, .labelText > tspan { + fill: ${i.labelTextColor}; + stroke: none; + } + + .loopText, .loopText > tspan { + fill: ${i.loopTextColor}; + stroke: none; + } + + .loopLine { + stroke-width: 2px; + stroke-dasharray: 2, 2; + stroke: ${i.labelBoxBorderColor}; + fill: ${i.labelBoxBorderColor}; + } + + .note { + //stroke: #decc93; + stroke: ${i.noteBorderColor}; + fill: ${i.noteBkgColor}; + } + + .noteText, .noteText > tspan { + fill: ${i.noteTextColor}; + stroke: none; + } + + .activation0 { + fill: ${i.activationBkgColor}; + stroke: ${i.activationBorderColor}; + } + + .activation1 { + fill: ${i.activationBkgColor}; + stroke: ${i.activationBorderColor}; + } + + .activation2 { + fill: ${i.activationBkgColor}; + stroke: ${i.activationBorderColor}; + } + + .actorPopupMenu { + position: absolute; + } + + .actorPopupMenuPanel { + position: absolute; + fill: ${i.actorBkg}; + box-shadow: 0px 8px 16px 0px rgba(0,0,0,0.2); + filter: drop-shadow(3px 5px 2px rgb(0 0 0 / 0.4)); +} + .actor-man line { + stroke: ${i.actorBorder}; + fill: ${i.actorBkg}; + } + .actor-man circle, line { + stroke: ${i.actorBorder}; + fill: ${i.actorBkg}; + stroke-width: 2px; + } +`,MK=function(i,a){const f=i.append("rect");return f.attr("x",a.x),f.attr("y",a.y),f.attr("fill",a.fill),f.attr("stroke",a.stroke),f.attr("width",a.width),f.attr("height",a.height),f.attr("rx",a.rx),f.attr("ry",a.ry),a.class!==void 0&&f.attr("class",a.class),f},HRe=(i,a)=>{ISt(()=>{const 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z")},CHt=function(i){i.append("defs").append("marker").attr("id","filled-head").attr("refX",18).attr("refY",7).attr("markerWidth",20).attr("markerHeight",28).attr("orient","auto").append("path").attr("d","M 18,7 L9,13 L14,7 L9,1 Z")},SHt=function(i){i.append("defs").append("marker").attr("id","sequencenumber").attr("refX",15).attr("refY",15).attr("markerWidth",60).attr("markerHeight",40).attr("orient","auto").append("circle").attr("cx",15).attr("cy",15).attr("r",6)},AHt=function(i){i.append("defs").append("marker").attr("id","crosshead").attr("markerWidth",15).attr("markerHeight",8).attr("orient","auto").attr("refX",4).attr("refY",5).append("path").attr("fill","none").attr("stroke","#000000").style("stroke-dasharray","0, 0").attr("stroke-width","1pt").attr("d","M 1,2 L 6,7 M 6,2 L 1,7")},rge=function(){return{x:0,y:0,fill:void 0,anchor:void 0,style:"#666",width:void 0,height:void 0,textMargin:0,rx:0,ry:0,tspan:!0,valign:void 0}},DK=function(){return{x:0,y:0,fill:"#EDF2AE",stroke:"#666",width:100,anchor:"start",height:100,rx:0,ry:0}},ige=function(){function i(w,y,b,E,S,N,B){const R=y.append("text").attr("x",b+S/2).attr("y",E+N/2+5).style("text-anchor","middle").text(w);p(R,B)}function a(w,y,b,E,S,N,B,R){const{actorFontSize:j,actorFontFamily:$,actorFontWeight:V}=R,[Q,oe]=$A(j),ce=w.split(Wa.lineBreakRegex);for(let se=0;sei.height||0))+(this.loops.length===0?0:this.loops.map(i=>i.height||0).reduce((i,a)=>i+a))+(this.messages.length===0?0:this.messages.map(i=>i.height||0).reduce((i,a)=>i+a))+(this.notes.length===0?0:this.notes.map(i=>i.height||0).reduce((i,a)=>i+a))},clear:function(){this.actors=[],this.boxes=[],this.loops=[],this.messages=[],this.notes=[]},addBox:function(i){this.boxes.push(i)},addActor:function(i){this.actors.push(i)},addLoop:function(i){this.loops.push(i)},addMessage:function(i){this.messages.push(i)},addNote:function(i){this.notes.push(i)},lastActor:function(){return this.actors[this.actors.length-1]},lastLoop:function(){return this.loops[this.loops.length-1]},lastMessage:function(){return this.messages[this.messages.length-1]},lastNote:function(){return this.notes[this.notes.length-1]},actors:[],boxes:[],loops:[],messages:[],notes:[]},init:function(){this.sequenceItems=[],this.activations=[],this.models.clear(),this.data={startx:void 0,stopx:void 0,starty:void 0,stopy:void 0},this.verticalPos=0,KRe(Tt())},updateVal:function(i,a,f,p){i[a]===void 0?i[a]=f:i[a]=p(f,i[a])},updateBounds:function(i,a,f,p){const w=this;let y=0;function b(E){return function(N){y++;const B=w.sequenceItems.length-y+1;w.updateVal(N,"starty",a-B*ln.boxMargin,Math.min),w.updateVal(N,"stopy",p+B*ln.boxMargin,Math.max),w.updateVal(si.data,"startx",i-B*ln.boxMargin,Math.min),w.updateVal(si.data,"stopx",f+B*ln.boxMargin,Math.max),E!=="activation"&&(w.updateVal(N,"startx",i-B*ln.boxMargin,Math.min),w.updateVal(N,"stopx",f+B*ln.boxMargin,Math.max),w.updateVal(si.data,"starty",a-B*ln.boxMargin,Math.min),w.updateVal(si.data,"stopy",p+B*ln.boxMargin,Math.max))}}this.sequenceItems.forEach(b()),this.activations.forEach(b("activation"))},insert:function(i,a,f,p){const w=Math.min(i,f),y=Math.max(i,f),b=Math.min(a,p),E=Math.max(a,p);this.updateVal(si.data,"startx",w,Math.min),this.updateVal(si.data,"starty",b,Math.min),this.updateVal(si.data,"stopx",y,Math.max),this.updateVal(si.data,"stopy",E,Math.max),this.updateBounds(w,b,y,E)},newActivation:function(i,a,f){const p=f[i.from.actor],w=IK(i.from.actor).length||0,y=p.x+p.width/2+(w-1)*ln.activationWidth/2;this.activations.push({startx:y,starty:this.verticalPos+2,stopx:y+ln.activationWidth,stopy:void 0,actor:i.from.actor,anchored:ih.anchorElement(a)})},endActivation:function(i){const a=this.activations.map(function(f){return f.actor}).lastIndexOf(i.from.actor);return this.activations.splice(a,1)[0]},createLoop:function(i={message:void 0,wrap:!1,width:void 0},a){return{startx:void 0,starty:this.verticalPos,stopx:void 0,stopy:void 0,title:i.message,wrap:i.wrap,width:i.width,height:0,fill:a}},newLoop:function(i={message:void 0,wrap:!1,width:void 0},a){this.sequenceItems.push(this.createLoop(i,a))},endLoop:function(){return this.sequenceItems.pop()},addSectionToLoop:function(i){const a=this.sequenceItems.pop();a.sections=a.sections||[],a.sectionTitles=a.sectionTitles||[],a.sections.push({y:si.getVerticalPos(),height:0}),a.sectionTitles.push(i),this.sequenceItems.push(a)},bumpVerticalPos:function(i){this.verticalPos=this.verticalPos+i,this.data.stopy=this.verticalPos},getVerticalPos:function(){return this.verticalPos},getBounds:function(){return{bounds:this.data,models:this.models}}},MHt=function(i,a){si.bumpVerticalPos(ln.boxMargin),a.height=ln.boxMargin,a.starty=si.getVerticalPos();const f=ih.getNoteRect();f.x=a.startx,f.y=a.starty,f.width=a.width||ln.width,f.class="note";const p=i.append("g"),w=ih.drawRect(p,f),y=ih.getTextObj();y.x=a.startx,y.y=a.starty,y.width=f.width,y.dy="1em",y.text=a.message,y.class="noteText",y.fontFamily=ln.noteFontFamily,y.fontSize=ln.noteFontSize,y.fontWeight=ln.noteFontWeight,y.anchor=ln.noteAlign,y.textMargin=ln.noteMargin,y.valign="center";const b=uL(p,y),E=Math.round(b.map(S=>(S._groups||S)[0][0].getBBox().height).reduce((S,N)=>S+N));w.attr("height",E+2*ln.noteMargin),a.height+=E+2*ln.noteMargin,si.bumpVerticalPos(E+2*ln.noteMargin),a.stopy=a.starty+E+2*ln.noteMargin,a.stopx=a.startx+f.width,si.insert(a.startx,a.starty,a.stopx,a.stopy),si.models.addNote(a)},g9=i=>({fontFamily:i.messageFontFamily,fontSize:i.messageFontSize,fontWeight:i.messageFontWeight}),lL=i=>({fontFamily:i.noteFontFamily,fontSize:i.noteFontSize,fontWeight:i.noteFontWeight}),sge=i=>({fontFamily:i.actorFontFamily,fontSize:i.actorFontSize,fontWeight:i.actorFontWeight});function DHt(i,a){si.bumpVerticalPos(10);const{startx:f,stopx:p,message:w}=a,y=Wa.splitBreaks(w).length,b=co.calculateTextDimensions(w,g9(ln)),E=b.height/y;a.height+=E,si.bumpVerticalPos(E);let S,N=b.height-10;const B=b.width;if(f===p){S=si.getVerticalPos()+N,ln.rightAngles||(N+=ln.boxMargin,S=si.getVerticalPos()+N),N+=30;const R=Math.max(B/2,ln.width/2);si.insert(f-R,si.getVerticalPos()-10+N,p+R,si.getVerticalPos()+30+N)}else N+=ln.boxMargin,S=si.getVerticalPos()+N,si.insert(f,S-10,p,S);return si.bumpVerticalPos(N),a.height+=N,a.stopy=a.starty+a.height,si.insert(a.fromBounds,a.starty,a.toBounds,a.stopy),S}const IHt=function(i,a,f,p){const{startx:w,stopx:y,starty:b,message:E,type:S,sequenceIndex:N,sequenceVisible:B}=a,R=co.calculateTextDimensions(E,g9(ln)),j=ih.getTextObj();j.x=w,j.y=b+10,j.width=y-w,j.class="messageText",j.dy="1em",j.text=E,j.fontFamily=ln.messageFontFamily,j.fontSize=ln.messageFontSize,j.fontWeight=ln.messageFontWeight,j.anchor=ln.messageAlign,j.valign="center",j.textMargin=ln.wrapPadding,j.tspan=!1,uL(i,j);const $=R.width;let V;w===y?ln.rightAngles?V=i.append("path").attr("d",`M ${w},${f} H ${w+Math.max(ln.width/2,$/2)} V ${f+25} H ${w}`):V=i.append("path").attr("d","M "+w+","+f+" C "+(w+60)+","+(f-10)+" "+(w+60)+","+(f+30)+" "+w+","+(f+20)):(V=i.append("line"),V.attr("x1",w),V.attr("y1",f),V.attr("x2",y),V.attr("y2",f)),S===p.db.LINETYPE.DOTTED||S===p.db.LINETYPE.DOTTED_CROSS||S===p.db.LINETYPE.DOTTED_POINT||S===p.db.LINETYPE.DOTTED_OPEN?(V.style("stroke-dasharray","3, 3"),V.attr("class","messageLine1")):V.attr("class","messageLine0");let Q="";ln.arrowMarkerAbsolute&&(Q=window.location.protocol+"//"+window.location.host+window.location.pathname+window.location.search,Q=Q.replace(/\(/g,"\\("),Q=Q.replace(/\)/g,"\\)")),V.attr("stroke-width",2),V.attr("stroke","none"),V.style("fill","none"),(S===p.db.LINETYPE.SOLID||S===p.db.LINETYPE.DOTTED)&&V.attr("marker-end","url("+Q+"#arrowhead)"),(S===p.db.LINETYPE.SOLID_POINT||S===p.db.LINETYPE.DOTTED_POINT)&&V.attr("marker-end","url("+Q+"#filled-head)"),(S===p.db.LINETYPE.SOLID_CROSS||S===p.db.LINETYPE.DOTTED_CROSS)&&V.attr("marker-end","url("+Q+"#crosshead)"),(B||ln.showSequenceNumbers)&&(V.attr("marker-start","url("+Q+"#sequencenumber)"),i.append("text").attr("x",w).attr("y",f+4).attr("font-family","sans-serif").attr("font-size","12px").attr("text-anchor","middle").attr("class","sequenceNumber").text(N))},age=function(i,a,f,p,w,y,b){if(w.hideUnusedParticipants===!0){const R=new Set;y.forEach(j=>{R.add(j.from),R.add(j.to)}),f=f.filter(j=>R.has(j))}let E=0,S=0,N=0,B;for(const R of f){const j=a[R],$=j.box;B&&B!=$&&(b||si.models.addBox(B),S+=ln.boxMargin+B.margin),$&&$!=B&&(b||($.x=E+S,$.y=p),S+=$.margin),j.width=j.width||ln.width,j.height=Math.max(j.height||ln.height,ln.height),j.margin=j.margin||ln.actorMargin,j.x=E+S,j.y=si.getVerticalPos();const V=ih.drawActor(i,j,ln,b);N=Math.max(N,V),si.insert(j.x,p,j.x+j.width,j.height),E+=j.width+S,j.box&&(j.box.width=E+$.margin-j.box.x),S=j.margin,B=j.box,si.models.addActor(j)}B&&!b&&si.models.addBox(B),si.bumpVerticalPos(N)},WRe=function(i,a,f,p){let w=0,y=0;for(const b of f){const E=a[b],S=PHt(E),N=ih.drawPopup(i,E,S,ln,ln.forceMenus,p);N.height>w&&(w=N.height),N.width+E.x>y&&(y=N.width+E.x)}return{maxHeight:w,maxWidth:y}},KRe=function(i){nd(ln,i),i.fontFamily&&(ln.actorFontFamily=ln.noteFontFamily=ln.messageFontFamily=i.fontFamily),i.fontSize&&(ln.actorFontSize=ln.noteFontSize=ln.messageFontSize=i.fontSize),i.fontWeight&&(ln.actorFontWeight=ln.noteFontWeight=ln.messageFontWeight=i.fontWeight)},IK=function(i){return si.activations.filter(function(a){return a.actor===i})},YRe=function(i,a){const f=a[i],p=IK(i),w=p.reduce(function(b,E){return Math.min(b,E.startx)},f.x+f.width/2),y=p.reduce(function(b,E){return Math.max(b,E.stopx)},f.x+f.width/2);return[w,y]};function p3(i,a,f,p,w){si.bumpVerticalPos(f);let y=p;if(a.id&&a.message&&i[a.id]){const b=i[a.id].width,E=g9(ln);a.message=co.wrapLabel(`[${a.message}]`,b-2*ln.wrapPadding,E),a.width=b,a.wrap=!0;const S=co.calculateTextDimensions(a.message,E),N=Math.max(S.height,ln.labelBoxHeight);y=p+N,Fe.debug(`${N} - ${a.message}`)}w(a),si.bumpVerticalPos(y)}const OHt=function(i,a,f,p){const{securityLevel:w,sequence:y}=Tt();ln=y,p.db.clear(),p.parser.parse(i);let b;w==="sandbox"&&(b=Cr("#i"+a));const E=Cr(w==="sandbox"?b.nodes()[0].contentDocument.body:"body"),S=w==="sandbox"?b.nodes()[0].contentDocument:document;si.init(),Fe.debug(p.db);const N=w==="sandbox"?E.select(`[id="${a}"]`):Cr(`[id="${a}"]`),B=p.db.getActors(),R=p.db.getBoxes(),j=p.db.getActorKeys(),$=p.db.getMessages(),V=p.db.getDiagramTitle(),Q=p.db.hasAtLeastOneBox(),oe=p.db.hasAtLeastOneBoxWithTitle(),ce=NHt(B,$,p);ln.height=BHt(B,ce,R),ih.insertComputerIcon(N),ih.insertDatabaseIcon(N),ih.insertClockIcon(N),Q&&(si.bumpVerticalPos(ln.boxMargin),oe&&si.bumpVerticalPos(R[0].textMaxHeight)),age(N,B,j,0,ln,$,!1);const se=jHt($,B,ce,p);ih.insertArrowHead(N),ih.insertArrowCrossHead(N),ih.insertArrowFilledHead(N),ih.insertSequenceNumber(N);function ge(rt,me){const gt=si.endActivation(rt);gt.starty+18>me&&(gt.starty=me-6,me+=12),ih.drawActivation(N,gt,me,ln,IK(rt.from.actor).length),si.insert(gt.startx,me-10,gt.stopx,me)}let ye=1,ke=1;const Ae=[];$.forEach(function(rt){let me,gt,pe;switch(rt.type){case p.db.LINETYPE.NOTE:gt=rt.noteModel,MHt(N,gt);break;case p.db.LINETYPE.ACTIVE_START:si.newActivation(rt,N,B);break;case p.db.LINETYPE.ACTIVE_END:ge(rt,si.getVerticalPos());break;case p.db.LINETYPE.LOOP_START:p3(se,rt,ln.boxMargin,ln.boxMargin+ln.boxTextMargin,Et=>si.newLoop(Et));break;case p.db.LINETYPE.LOOP_END:me=si.endLoop(),ih.drawLoop(N,me,"loop",ln),si.bumpVerticalPos(me.stopy-si.getVerticalPos()),si.models.addLoop(me);break;case p.db.LINETYPE.RECT_START:p3(se,rt,ln.boxMargin,ln.boxMargin,Et=>si.newLoop(void 0,Et.message));break;case p.db.LINETYPE.RECT_END:me=si.endLoop(),ih.drawBackgroundRect(N,me),si.models.addLoop(me),si.bumpVerticalPos(me.stopy-si.getVerticalPos());break;case p.db.LINETYPE.OPT_START:p3(se,rt,ln.boxMargin,ln.boxMargin+ln.boxTextMargin,Et=>si.newLoop(Et));break;case p.db.LINETYPE.OPT_END:me=si.endLoop(),ih.drawLoop(N,me,"opt",ln),si.bumpVerticalPos(me.stopy-si.getVerticalPos()),si.models.addLoop(me);break;case p.db.LINETYPE.ALT_START:p3(se,rt,ln.boxMargin,ln.boxMargin+ln.boxTextMargin,Et=>si.newLoop(Et));break;case p.db.LINETYPE.ALT_ELSE:p3(se,rt,ln.boxMargin+ln.boxTextMargin,ln.boxMargin,Et=>si.addSectionToLoop(Et));break;case p.db.LINETYPE.ALT_END:me=si.endLoop(),ih.drawLoop(N,me,"alt",ln),si.bumpVerticalPos(me.stopy-si.getVerticalPos()),si.models.addLoop(me);break;case p.db.LINETYPE.PAR_START:p3(se,rt,ln.boxMargin,ln.boxMargin+ln.boxTextMargin,Et=>si.newLoop(Et));break;case p.db.LINETYPE.PAR_AND:p3(se,rt,ln.boxMargin+ln.boxTextMargin,ln.boxMargin,Et=>si.addSectionToLoop(Et));break;case p.db.LINETYPE.PAR_END:me=si.endLoop(),ih.drawLoop(N,me,"par",ln),si.bumpVerticalPos(me.stopy-si.getVerticalPos()),si.models.addLoop(me);break;case p.db.LINETYPE.AUTONUMBER:ye=rt.message.start||ye,ke=rt.message.step||ke,rt.message.visible?p.db.enableSequenceNumbers():p.db.disableSequenceNumbers();break;case p.db.LINETYPE.CRITICAL_START:p3(se,rt,ln.boxMargin,ln.boxMargin+ln.boxTextMargin,Et=>si.newLoop(Et));break;case p.db.LINETYPE.CRITICAL_OPTION:p3(se,rt,ln.boxMargin+ln.boxTextMargin,ln.boxMargin,Et=>si.addSectionToLoop(Et));break;case p.db.LINETYPE.CRITICAL_END:me=si.endLoop(),ih.drawLoop(N,me,"critical",ln),si.bumpVerticalPos(me.stopy-si.getVerticalPos()),si.models.addLoop(me);break;case p.db.LINETYPE.BREAK_START:p3(se,rt,ln.boxMargin,ln.boxMargin+ln.boxTextMargin,Et=>si.newLoop(Et));break;case p.db.LINETYPE.BREAK_END:me=si.endLoop(),ih.drawLoop(N,me,"break",ln),si.bumpVerticalPos(me.stopy-si.getVerticalPos()),si.models.addLoop(me);break;default:try{pe=rt.msgModel,pe.starty=si.getVerticalPos(),pe.sequenceIndex=ye,pe.sequenceVisible=p.db.showSequenceNumbers();const Et=DHt(N,pe);Ae.push({messageModel:pe,lineStartY:Et}),si.models.addMessage(pe)}catch(Et){Fe.error("error while drawing message",Et)}}[p.db.LINETYPE.SOLID_OPEN,p.db.LINETYPE.DOTTED_OPEN,p.db.LINETYPE.SOLID,p.db.LINETYPE.DOTTED,p.db.LINETYPE.SOLID_CROSS,p.db.LINETYPE.DOTTED_CROSS,p.db.LINETYPE.SOLID_POINT,p.db.LINETYPE.DOTTED_POINT].includes(rt.type)&&(ye=ye+ke)}),Ae.forEach(rt=>IHt(N,rt.messageModel,rt.lineStartY,p)),ln.mirrorActors&&(si.bumpVerticalPos(ln.boxMargin*2),age(N,B,j,si.getVerticalPos(),ln,$,!0),si.bumpVerticalPos(ln.boxMargin),VRe(N,si.getVerticalPos())),si.models.boxes.forEach(function(rt){rt.height=si.getVerticalPos()-rt.y,si.insert(rt.x,rt.y,rt.x+rt.width,rt.height),rt.startx=rt.x,rt.starty=rt.y,rt.stopx=rt.startx+rt.width,rt.stopy=rt.starty+rt.height,rt.stroke="rgb(0,0,0, 0.5)",ih.drawBox(N,rt,ln)}),Q&&si.bumpVerticalPos(ln.boxMargin);const de=WRe(N,B,j,S),{bounds:ve}=si.getBounds();Fe.debug("For line height fix Querying: #"+a+" .actor-line"),Jfe("#"+a+" .actor-line").attr("y2",ve.stopy);let xe=ve.stopy-ve.starty;xe{const b=i[y];b.wrap&&(b.description=co.wrapLabel(b.description,ln.width-2*ln.wrapPadding,sge(ln)));const E=co.calculateTextDimensions(b.description,sge(ln));b.width=b.wrap?ln.width:Math.max(ln.width,E.width+2*ln.wrapPadding),b.height=b.wrap?Math.max(E.height,ln.height):ln.height,p=Math.max(p,b.height)});for(const y in a){const b=i[y];if(!b)continue;const E=i[b.nextActor];if(!E){const R=a[y]+ln.actorMargin-b.width/2;b.margin=Math.max(R,ln.actorMargin);continue}const N=a[y]+ln.actorMargin-b.width/2-E.width/2;b.margin=Math.max(N,ln.actorMargin)}let w=0;return f.forEach(y=>{const b=g9(ln);let E=y.actorKeys.reduce((B,R)=>B+=i[R].width+(i[R].margin||0),0);E-=2*ln.boxTextMargin,y.wrap&&(y.name=co.wrapLabel(y.name,E-2*ln.wrapPadding,b));const S=co.calculateTextDimensions(y.name,b);w=Math.max(S.height,w);const N=Math.max(E,S.width+2*ln.wrapPadding);if(y.margin=ln.boxTextMargin,Ey.textMaxHeight=w),Math.max(p,ln.height)}const RHt=function(i,a,f){const p=a[i.from].x,w=a[i.to].x,y=i.wrap&&i.message;let b=co.calculateTextDimensions(y?co.wrapLabel(i.message,ln.width,lL(ln)):i.message,lL(ln));const E={width:y?ln.width:Math.max(ln.width,b.width+2*ln.noteMargin),height:0,startx:a[i.from].x,stopx:0,starty:0,stopy:0,message:i.message};return i.placement===f.db.PLACEMENT.RIGHTOF?(E.width=y?Math.max(ln.width,b.width):Math.max(a[i.from].width/2+a[i.to].width/2,b.width+2*ln.noteMargin),E.startx=p+(a[i.from].width+ln.actorMargin)/2):i.placement===f.db.PLACEMENT.LEFTOF?(E.width=Math.max(y?ln.width:a[i.from].width/2+a[i.to].width/2,b.width+2*ln.noteMargin),E.startx=p-E.width+(a[i.from].width-ln.actorMargin)/2):i.to===i.from?(b=co.calculateTextDimensions(y?co.wrapLabel(i.message,Math.max(ln.width,a[i.from].width),lL(ln)):i.message,lL(ln)),E.width=y?Math.max(ln.width,a[i.from].width):Math.max(a[i.from].width,ln.width,b.width+2*ln.noteMargin),E.startx=p+(a[i.from].width-E.width)/2):(E.width=Math.abs(p+a[i.from].width/2-(w+a[i.to].width/2))+ln.actorMargin,E.startx=pj.actor).lastIndexOf(N.from.actor);delete si.activations.splice(R,1)[0]}break}N.placement!==void 0?(E=RHt(N,a,p),N.noteModel=E,y.forEach(R=>{b=R,b.from=Math.min(b.from,E.startx),b.to=Math.max(b.to,E.startx+E.width),b.width=Math.max(b.width,Math.abs(b.from-b.to))-ln.labelBoxWidth})):(S=FHt(N,a,p),N.msgModel=S,S.startx&&S.stopx&&y.length>0&&y.forEach(R=>{if(b=R,S.startx===S.stopx){const j=a[N.from],$=a[N.to];b.from=Math.min(j.x-S.width/2,j.x-j.width/2,b.from),b.to=Math.max($.x+S.width/2,$.x+j.width/2,b.to),b.width=Math.max(b.width,Math.abs(b.to-b.from))-ln.labelBoxWidth}else b.from=Math.min(S.startx,b.from),b.to=Math.max(S.stopx,b.to),b.width=Math.max(b.width,S.width)-ln.labelBoxWidth}))}),si.activations=[],Fe.debug("Loop type widths:",w),w},$Ht=Object.freeze(Object.defineProperty({__proto__:null,diagram:{parser:j$t,db:cHt,renderer:{bounds:si,drawActors:age,drawActorsPopup:WRe,setConf:KRe,draw:OHt},styles:uHt}},Symbol.toStringTag,{value:"Module"}));var oge=function(){var i=function(Nt,ze,Xe,Lt){for(Xe=Xe||{},Lt=Nt.length;Lt--;Xe[Nt[Lt]]=ze);return Xe},a=[1,32],f=[1,33],p=[1,34],w=[1,35],y=[1,9],b=[1,8],E=[1,18],S=[1,19],N=[1,20],B=[1,38],R=[1,25],j=[1,23],$=[1,24],V=[1,30],Q=[1,31],oe=[1,26],ce=[1,27],se=[1,28],ge=[1,29],ye=[1,42],ke=[1,39],Ae=[1,40],de=[1,41],ve=[1,43],te=[1,16,24],xe=[1,57],De=[1,58],he=[1,59],Ie=[1,60],ee=[1,61],rt=[1,62],me=[1,63],gt=[1,73],pe=[1,16,24,27,28,35,48,49,63,64,65,66,67,68,69,74,76],Et=[1,16,24,27,28,33,35,48,49,54,63,64,65,66,67,68,69,74,76,89,91,92,93,94],wt=[1,80],jt=[28,89,91,92,93,94],At=[28,68,69,89,91,92,93,94],Bt=[28,63,64,65,66,67,89,91,92,93,94],cn=[1,90],Nn=[1,16,24,48,49],Ot=[1,16,24,35],oi=[8,9,10,11,19,23,42,44,46,52,53,55,56,58,60,70,71,73,77,89,91,92,93,94],kt={trace:function(){},yy:{},symbols_:{error:2,start:3,mermaidDoc:4,directive:5,statements:6,direction:7,direction_tb:8,direction_bt:9,direction_rl:10,direction_lr:11,graphConfig:12,openDirective:13,typeDirective:14,closeDirective:15,NEWLINE:16,":":17,argDirective:18,open_directive:19,type_directive:20,arg_directive:21,close_directive:22,CLASS_DIAGRAM:23,EOF:24,statement:25,classLabel:26,SQS:27,STR:28,SQE:29,className:30,alphaNumToken:31,classLiteralName:32,GENERICTYPE:33,relationStatement:34,LABEL:35,classStatement:36,methodStatement:37,annotationStatement:38,clickStatement:39,cssClassStatement:40,noteStatement:41,acc_title:42,acc_title_value:43,acc_descr:44,acc_descr_value:45,acc_descr_multiline_value:46,classIdentifier:47,STYLE_SEPARATOR:48,STRUCT_START:49,members:50,STRUCT_STOP:51,CLASS:52,ANNOTATION_START:53,ANNOTATION_END:54,MEMBER:55,SEPARATOR:56,relation:57,NOTE_FOR:58,noteText:59,NOTE:60,relationType:61,lineType:62,AGGREGATION:63,EXTENSION:64,COMPOSITION:65,DEPENDENCY:66,LOLLIPOP:67,LINE:68,DOTTED_LINE:69,CALLBACK:70,LINK:71,LINK_TARGET:72,CLICK:73,CALLBACK_NAME:74,CALLBACK_ARGS:75,HREF:76,CSSCLASS:77,commentToken:78,textToken:79,graphCodeTokens:80,textNoTagsToken:81,TAGSTART:82,TAGEND:83,"==":84,"--":85,PCT:86,DEFAULT:87,SPACE:88,MINUS:89,keywords:90,UNICODE_TEXT:91,NUM:92,ALPHA:93,BQUOTE_STR:94,$accept:0,$end:1},terminals_:{2:"error",8:"direction_tb",9:"direction_bt",10:"direction_rl",11:"direction_lr",16:"NEWLINE",17:":",19:"open_directive",20:"type_directive",21:"arg_directive",22:"close_directive",23:"CLASS_DIAGRAM",24:"EOF",27:"SQS",28:"STR",29:"SQE",33:"GENERICTYPE",35:"LABEL",42:"acc_title",43:"acc_title_value",44:"acc_descr",45:"acc_descr_value",46:"acc_descr_multiline_value",48:"STYLE_SEPARATOR",49:"STRUCT_START",51:"STRUCT_STOP",52:"CLASS",53:"ANNOTATION_START",54:"ANNOTATION_END",55:"MEMBER",56:"SEPARATOR",58:"NOTE_FOR",60:"NOTE",63:"AGGREGATION",64:"EXTENSION",65:"COMPOSITION",66:"DEPENDENCY",67:"LOLLIPOP",68:"LINE",69:"DOTTED_LINE",70:"CALLBACK",71:"LINK",72:"LINK_TARGET",73:"CLICK",74:"CALLBACK_NAME",75:"CALLBACK_ARGS",76:"HREF",77:"CSSCLASS",80:"graphCodeTokens",82:"TAGSTART",83:"TAGEND",84:"==",85:"--",86:"PCT",87:"DEFAULT",88:"SPACE",89:"MINUS",90:"keywords",91:"UNICODE_TEXT",92:"NUM",93:"ALPHA",94:"BQUOTE_STR"},productions_:[0,[3,1],[3,2],[3,1],[7,1],[7,1],[7,1],[7,1],[4,1],[5,4],[5,6],[13,1],[14,1],[18,1],[15,1],[12,4],[6,1],[6,2],[6,3],[26,3],[30,1],[30,1],[30,2],[30,2],[30,2],[25,1],[25,2],[25,1],[25,1],[25,1],[25,1],[25,1],[25,1],[25,1],[25,2],[25,2],[25,1],[36,1],[36,3],[36,4],[36,6],[47,2],[47,3],[38,4],[50,1],[50,2],[37,1],[37,2],[37,1],[37,1],[34,3],[34,4],[34,4],[34,5],[41,3],[41,2],[57,3],[57,2],[57,2],[57,1],[61,1],[61,1],[61,1],[61,1],[61,1],[62,1],[62,1],[39,3],[39,4],[39,3],[39,4],[39,4],[39,5],[39,3],[39,4],[39,4],[39,5],[39,3],[39,4],[39,4],[39,5],[40,3],[78,1],[78,1],[79,1],[79,1],[79,1],[79,1],[79,1],[79,1],[79,1],[81,1],[81,1],[81,1],[81,1],[31,1],[31,1],[31,1],[31,1],[32,1],[59,1]],performAction:function(ze,Xe,Lt,Ge,Bn,Oe,Ri){var tn=Oe.length-1;switch(Bn){case 4:Ge.setDirection("TB");break;case 5:Ge.setDirection("BT");break;case 6:Ge.setDirection("RL");break;case 7:Ge.setDirection("LR");break;case 11:Ge.parseDirective("%%{","open_directive");break;case 12:Ge.parseDirective(Oe[tn],"type_directive");break;case 13:Oe[tn]=Oe[tn].trim().replace(/'/g,'"'),Ge.parseDirective(Oe[tn],"arg_directive");break;case 14:Ge.parseDirective("}%%","close_directive","class");break;case 19:this.$=Oe[tn-1];break;case 20:case 21:this.$=Oe[tn];break;case 22:this.$=Oe[tn-1]+Oe[tn];break;case 23:case 24:this.$=Oe[tn-1]+"~"+Oe[tn]+"~";break;case 25:Ge.addRelation(Oe[tn]);break;case 26:Oe[tn-1].title=Ge.cleanupLabel(Oe[tn]),Ge.addRelation(Oe[tn-1]);break;case 34:this.$=Oe[tn].trim(),Ge.setAccTitle(this.$);break;case 35:case 36:this.$=Oe[tn].trim(),Ge.setAccDescription(this.$);break;case 38:Ge.setCssClass(Oe[tn-2],Oe[tn]);break;case 39:Ge.addMembers(Oe[tn-3],Oe[tn-1]);break;case 40:Ge.setCssClass(Oe[tn-5],Oe[tn-3]),Ge.addMembers(Oe[tn-5],Oe[tn-1]);break;case 41:this.$=Oe[tn],Ge.addClass(Oe[tn]);break;case 42:this.$=Oe[tn-1],Ge.addClass(Oe[tn-1]),Ge.setClassLabel(Oe[tn-1],Oe[tn]);break;case 43:Ge.addAnnotation(Oe[tn],Oe[tn-2]);break;case 44:this.$=[Oe[tn]];break;case 45:Oe[tn].push(Oe[tn-1]),this.$=Oe[tn];break;case 46:break;case 47:Ge.addMember(Oe[tn-1],Ge.cleanupLabel(Oe[tn]));break;case 48:break;case 49:break;case 50:this.$={id1:Oe[tn-2],id2:Oe[tn],relation:Oe[tn-1],relationTitle1:"none",relationTitle2:"none"};break;case 51:this.$={id1:Oe[tn-3],id2:Oe[tn],relation:Oe[tn-1],relationTitle1:Oe[tn-2],relationTitle2:"none"};break;case 52:this.$={id1:Oe[tn-3],id2:Oe[tn],relation:Oe[tn-2],relationTitle1:"none",relationTitle2:Oe[tn-1]};break;case 53:this.$={id1:Oe[tn-4],id2:Oe[tn],relation:Oe[tn-2],relationTitle1:Oe[tn-3],relationTitle2:Oe[tn-1]};break;case 54:Ge.addNote(Oe[tn],Oe[tn-1]);break;case 55:Ge.addNote(Oe[tn]);break;case 56:this.$={type1:Oe[tn-2],type2:Oe[tn],lineType:Oe[tn-1]};break;case 57:this.$={type1:"none",type2:Oe[tn],lineType:Oe[tn-1]};break;case 58:this.$={type1:Oe[tn-1],type2:"none",lineType:Oe[tn]};break;case 59:this.$={type1:"none",type2:"none",lineType:Oe[tn]};break;case 60:this.$=Ge.relationType.AGGREGATION;break;case 61:this.$=Ge.relationType.EXTENSION;break;case 62:this.$=Ge.relationType.COMPOSITION;break;case 63:this.$=Ge.relationType.DEPENDENCY;break;case 64:this.$=Ge.relationType.LOLLIPOP;break;case 65:this.$=Ge.lineType.LINE;break;case 66:this.$=Ge.lineType.DOTTED_LINE;break;case 67:case 73:this.$=Oe[tn-2],Ge.setClickEvent(Oe[tn-1],Oe[tn]);break;case 68:case 74:this.$=Oe[tn-3],Ge.setClickEvent(Oe[tn-2],Oe[tn-1]),Ge.setTooltip(Oe[tn-2],Oe[tn]);break;case 69:case 77:this.$=Oe[tn-2],Ge.setLink(Oe[tn-1],Oe[tn]);break;case 70:this.$=Oe[tn-3],Ge.setLink(Oe[tn-2],Oe[tn-1],Oe[tn]);break;case 71:case 79:this.$=Oe[tn-3],Ge.setLink(Oe[tn-2],Oe[tn-1]),Ge.setTooltip(Oe[tn-2],Oe[tn]);break;case 72:case 80:this.$=Oe[tn-4],Ge.setLink(Oe[tn-3],Oe[tn-2],Oe[tn]),Ge.setTooltip(Oe[tn-3],Oe[tn-1]);break;case 75:this.$=Oe[tn-3],Ge.setClickEvent(Oe[tn-2],Oe[tn-1],Oe[tn]);break;case 76:this.$=Oe[tn-4],Ge.setClickEvent(Oe[tn-3],Oe[tn-2],Oe[tn-1]),Ge.setTooltip(Oe[tn-3],Oe[tn]);break;case 78:this.$=Oe[tn-3],Ge.setLink(Oe[tn-2],Oe[tn-1],Oe[tn]);break;case 81:Ge.setCssClass(Oe[tn-1],Oe[tn]);break}},table:[{3:1,4:2,5:3,6:4,7:17,8:a,9:f,10:p,11:w,12:5,13:6,19:y,23:b,25:7,30:21,31:36,32:37,34:10,36:11,37:12,38:13,39:14,40:15,41:16,42:E,44:S,46:N,47:22,52:B,53:R,55:j,56:$,58:V,60:Q,70:oe,71:ce,73:se,77:ge,89:ye,91:ke,92:Ae,93:de,94:ve},{1:[3]},{1:[2,1]},{3:44,4:2,5:3,6:4,7:17,8:a,9:f,10:p,11:w,12:5,13:6,19:y,23:b,25:7,30:21,31:36,32:37,34:10,36:11,37:12,38:13,39:14,40:15,41:16,42:E,44:S,46:N,47:22,52:B,53:R,55:j,56:$,58:V,60:Q,70:oe,71:ce,73:se,77:ge,89:ye,91:ke,92:Ae,93:de,94:ve},{1:[2,3]},{1:[2,8]},{14:45,20:[1,46]},i($,[2,16],{16:[1,47]}),{16:[1,48]},{20:[2,11]},i(te,[2,25],{35:[1,49]}),i(te,[2,27]),i(te,[2,28]),i(te,[2,29]),i(te,[2,30]),i(te,[2,31]),i(te,[2,32]),i(te,[2,33]),{43:[1,50]},{45:[1,51]},i(te,[2,36]),i(te,[2,46],{57:52,61:55,62:56,28:[1,53],35:[1,54],63:xe,64:De,65:he,66:Ie,67:ee,68:rt,69:me}),i(te,[2,37],{48:[1,64],49:[1,65]}),i(te,[2,48]),i(te,[2,49]),{31:66,89:ye,91:ke,92:Ae,93:de},{30:67,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},{30:68,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},{30:69,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},{28:[1,70]},{30:71,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},{28:gt,59:72},i(te,[2,4]),i(te,[2,5]),i(te,[2,6]),i(te,[2,7]),i(pe,[2,20],{31:36,32:37,30:74,33:[1,75],89:ye,91:ke,92:Ae,93:de,94:ve}),i(pe,[2,21],{33:[1,76]}),{30:77,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},i(Et,[2,95]),i(Et,[2,96]),i(Et,[2,97]),i(Et,[2,98]),i([1,16,24,27,28,33,35,48,49,63,64,65,66,67,68,69,74,76],[2,99]),{1:[2,2]},{15:78,17:[1,79],22:wt},i([17,22],[2,12]),i($,[2,17],{25:7,34:10,36:11,37:12,38:13,39:14,40:15,41:16,7:17,30:21,47:22,31:36,32:37,6:81,8:a,9:f,10:p,11:w,42:E,44:S,46:N,52:B,53:R,55:j,56:$,58:V,60:Q,70:oe,71:ce,73:se,77:ge,89:ye,91:ke,92:Ae,93:de,94:ve}),{6:82,7:17,8:a,9:f,10:p,11:w,25:7,30:21,31:36,32:37,34:10,36:11,37:12,38:13,39:14,40:15,41:16,42:E,44:S,46:N,47:22,52:B,53:R,55:j,56:$,58:V,60:Q,70:oe,71:ce,73:se,77:ge,89:ye,91:ke,92:Ae,93:de,94:ve},i(te,[2,26]),i(te,[2,34]),i(te,[2,35]),{28:[1,84],30:83,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},{57:85,61:55,62:56,63:xe,64:De,65:he,66:Ie,67:ee,68:rt,69:me},i(te,[2,47]),{62:86,68:rt,69:me},i(jt,[2,59],{61:87,63:xe,64:De,65:he,66:Ie,67:ee}),i(At,[2,60]),i(At,[2,61]),i(At,[2,62]),i(At,[2,63]),i(At,[2,64]),i(Bt,[2,65]),i(Bt,[2,66]),{31:88,89:ye,91:ke,92:Ae,93:de},{50:89,55:cn},{54:[1,91]},{28:[1,92]},{28:[1,93]},{74:[1,94],76:[1,95]},{31:96,89:ye,91:ke,92:Ae,93:de},{28:gt,59:97},i(te,[2,55]),i(te,[2,100]),i(pe,[2,22]),i(pe,[2,23]),i(pe,[2,24]),i(Nn,[2,41],{26:98,27:[1,99]}),{16:[1,100]},{18:101,21:[1,102]},{16:[2,14]},i($,[2,18]),{24:[1,103]},i(Ot,[2,50]),{30:104,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},{28:[1,106],30:105,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},i(jt,[2,58],{61:107,63:xe,64:De,65:he,66:Ie,67:ee}),i(jt,[2,57]),i(te,[2,38],{49:[1,108]}),{51:[1,109]},{50:110,51:[2,44],55:cn},{30:111,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},i(te,[2,67],{28:[1,112]}),i(te,[2,69],{28:[1,114],72:[1,113]}),i(te,[2,73],{28:[1,115],75:[1,116]}),i(te,[2,77],{28:[1,118],72:[1,117]}),i(te,[2,81]),i(te,[2,54]),i(Nn,[2,42]),{28:[1,119]},i(oi,[2,9]),{15:120,22:wt},{22:[2,13]},{1:[2,15]},i(Ot,[2,52]),i(Ot,[2,51]),{30:121,31:36,32:37,89:ye,91:ke,92:Ae,93:de,94:ve},i(jt,[2,56]),{50:122,55:cn},i(te,[2,39]),{51:[2,45]},i(te,[2,43]),i(te,[2,68]),i(te,[2,70]),i(te,[2,71],{72:[1,123]}),i(te,[2,74]),i(te,[2,75],{28:[1,124]}),i(te,[2,78]),i(te,[2,79],{72:[1,125]}),{29:[1,126]},{16:[1,127]},i(Ot,[2,53]),{51:[1,128]},i(te,[2,72]),i(te,[2,76]),i(te,[2,80]),i(Nn,[2,19]),i(oi,[2,10]),i(te,[2,40])],defaultActions:{2:[2,1],4:[2,3],5:[2,8],9:[2,11],44:[2,2],80:[2,14],102:[2,13],103:[2,15],110:[2,45]},parseError:function(ze,Xe){if(Xe.recoverable)this.trace(ze);else{var Lt=new Error(ze);throw Lt.hash=Xe,Lt}},parse:function(ze){var Xe=this,Lt=[0],Ge=[],Bn=[null],Oe=[],Ri=this.table,tn="",hi=0,Sr=0,Zn=2,Xn=1,ir=Oe.slice.call(arguments,1),Hn=Object.create(this.lexer),tr={yy:{}};for(var ha in this.yy)Object.prototype.hasOwnProperty.call(this.yy,ha)&&(tr.yy[ha]=this.yy[ha]);Hn.setInput(ze,tr.yy),tr.yy.lexer=Hn,tr.yy.parser=this,typeof Hn.yylloc>"u"&&(Hn.yylloc={});var Zs=Hn.yylloc;Oe.push(Zs);var ns=Hn.options&&Hn.options.ranges;typeof tr.yy.parseError=="function"?this.parseError=tr.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function Hi(){var yn;return yn=Ge.pop()||Hn.lex()||Xn,typeof yn!="number"&&(yn instanceof Array&&(Ge=yn,yn=Ge.pop()),yn=Xe.symbols_[yn]||yn),yn}for(var Js,Pc,Ga,ws,Oi={},Er,br,Dr,Vn;;){if(Pc=Lt[Lt.length-1],this.defaultActions[Pc]?Ga=this.defaultActions[Pc]:((Js===null||typeof Js>"u")&&(Js=Hi()),Ga=Ri[Pc]&&Ri[Pc][Js]),typeof Ga>"u"||!Ga.length||!Ga[0]){var qi="";Vn=[];for(Er in Ri[Pc])this.terminals_[Er]&&Er>Zn&&Vn.push("'"+this.terminals_[Er]+"'");Hn.showPosition?qi="Parse error on line "+(hi+1)+`: +`+Hn.showPosition()+` +Expecting `+Vn.join(", ")+", got '"+(this.terminals_[Js]||Js)+"'":qi="Parse error on line "+(hi+1)+": Unexpected "+(Js==Xn?"end of input":"'"+(this.terminals_[Js]||Js)+"'"),this.parseError(qi,{text:Hn.match,token:this.terminals_[Js]||Js,line:Hn.yylineno,loc:Zs,expected:Vn})}if(Ga[0]instanceof Array&&Ga.length>1)throw new Error("Parse Error: multiple actions possible at state: "+Pc+", token: "+Js);switch(Ga[0]){case 1:Lt.push(Js),Bn.push(Hn.yytext),Oe.push(Hn.yylloc),Lt.push(Ga[1]),Js=null,Sr=Hn.yyleng,tn=Hn.yytext,hi=Hn.yylineno,Zs=Hn.yylloc;break;case 2:if(br=this.productions_[Ga[1]][1],Oi.$=Bn[Bn.length-br],Oi._$={first_line:Oe[Oe.length-(br||1)].first_line,last_line:Oe[Oe.length-1].last_line,first_column:Oe[Oe.length-(br||1)].first_column,last_column:Oe[Oe.length-1].last_column},ns&&(Oi._$.range=[Oe[Oe.length-(br||1)].range[0],Oe[Oe.length-1].range[1]]),ws=this.performAction.apply(Oi,[tn,Sr,hi,tr.yy,Ga[1],Bn,Oe].concat(ir)),typeof ws<"u")return ws;br&&(Lt=Lt.slice(0,-1*br*2),Bn=Bn.slice(0,-1*br),Oe=Oe.slice(0,-1*br)),Lt.push(this.productions_[Ga[1]][0]),Bn.push(Oi.$),Oe.push(Oi._$),Dr=Ri[Lt[Lt.length-2]][Lt[Lt.length-1]],Lt.push(Dr);break;case 3:return!0}}return!0}},Dt=function(){var Nt={EOF:1,parseError:function(Xe,Lt){if(this.yy.parser)this.yy.parser.parseError(Xe,Lt);else throw new Error(Xe)},setInput:function(ze,Xe){return this.yy=Xe||this.yy||{},this._input=ze,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},input:function(){var ze=this._input[0];this.yytext+=ze,this.yyleng++,this.offset++,this.match+=ze,this.matched+=ze;var Xe=ze.match(/(?:\r\n?|\n).*/g);return Xe?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),ze},unput:function(ze){var Xe=ze.length,Lt=ze.split(/(?:\r\n?|\n)/g);this._input=ze+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-Xe),this.offset-=Xe;var Ge=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),Lt.length-1&&(this.yylineno-=Lt.length-1);var Bn=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:Lt?(Lt.length===Ge.length?this.yylloc.first_column:0)+Ge[Ge.length-Lt.length].length-Lt[0].length:this.yylloc.first_column-Xe},this.options.ranges&&(this.yylloc.range=[Bn[0],Bn[0]+this.yyleng-Xe]),this.yyleng=this.yytext.length,this},more:function(){return this._more=!0,this},reject:function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true). +`+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},less:function(ze){this.unput(this.match.slice(ze))},pastInput:function(){var ze=this.matched.substr(0,this.matched.length-this.match.length);return(ze.length>20?"...":"")+ze.substr(-20).replace(/\n/g,"")},upcomingInput:function(){var ze=this.match;return ze.length<20&&(ze+=this._input.substr(0,20-ze.length)),(ze.substr(0,20)+(ze.length>20?"...":"")).replace(/\n/g,"")},showPosition:function(){var ze=this.pastInput(),Xe=new Array(ze.length+1).join("-");return ze+this.upcomingInput()+` +`+Xe+"^"},test_match:function(ze,Xe){var Lt,Ge,Bn;if(this.options.backtrack_lexer&&(Bn={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(Bn.yylloc.range=this.yylloc.range.slice(0))),Ge=ze[0].match(/(?:\r\n?|\n).*/g),Ge&&(this.yylineno+=Ge.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:Ge?Ge[Ge.length-1].length-Ge[Ge.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+ze[0].length},this.yytext+=ze[0],this.match+=ze[0],this.matches=ze,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(ze[0].length),this.matched+=ze[0],Lt=this.performAction.call(this,this.yy,this,Xe,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),Lt)return Lt;if(this._backtrack){for(var Oe in Bn)this[Oe]=Bn[Oe];return!1}return!1},next:function(){if(this.done)return this.EOF;this._input||(this.done=!0);var ze,Xe,Lt,Ge;this._more||(this.yytext="",this.match="");for(var Bn=this._currentRules(),Oe=0;OeXe[0].length)){if(Xe=Lt,Ge=Oe,this.options.backtrack_lexer){if(ze=this.test_match(Lt,Bn[Oe]),ze!==!1)return ze;if(this._backtrack){Xe=!1;continue}else return!1}else if(!this.options.flex)break}return Xe?(ze=this.test_match(Xe,Bn[Ge]),ze!==!1?ze:!1):this._input===""?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+`. Unrecognized text. +`+this.showPosition(),{text:"",token:null,line:this.yylineno})},lex:function(){var Xe=this.next();return Xe||this.lex()},begin:function(Xe){this.conditionStack.push(Xe)},popState:function(){var Xe=this.conditionStack.length-1;return Xe>0?this.conditionStack.pop():this.conditionStack[0]},_currentRules:function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},topState:function(Xe){return Xe=this.conditionStack.length-1-Math.abs(Xe||0),Xe>=0?this.conditionStack[Xe]:"INITIAL"},pushState:function(Xe){this.begin(Xe)},stateStackSize:function(){return this.conditionStack.length},options:{},performAction:function(Xe,Lt,Ge,Bn){switch(Ge){case 0:return this.begin("open_directive"),19;case 1:return 8;case 2:return 9;case 3:return 10;case 4:return 11;case 5:return this.begin("type_directive"),20;case 6:return this.popState(),this.begin("arg_directive"),17;case 7:return this.popState(),this.popState(),22;case 8:return 21;case 9:break;case 10:break;case 11:return this.begin("acc_title"),42;case 12:return this.popState(),"acc_title_value";case 13:return this.begin("acc_descr"),44;case 14:return this.popState(),"acc_descr_value";case 15:this.begin("acc_descr_multiline");break;case 16:this.popState();break;case 17:return"acc_descr_multiline_value";case 18:return 16;case 19:break;case 20:return 23;case 21:return 23;case 22:return this.begin("struct"),49;case 23:return"EDGE_STATE";case 24:return"EOF_IN_STRUCT";case 25:return"OPEN_IN_STRUCT";case 26:return this.popState(),51;case 27:break;case 28:return"MEMBER";case 29:return 52;case 30:return 77;case 31:return 70;case 32:return 71;case 33:return 73;case 34:return 58;case 35:return 60;case 36:return 53;case 37:return 54;case 38:this.begin("generic");break;case 39:this.popState();break;case 40:return"GENERICTYPE";case 41:this.begin("string");break;case 42:this.popState();break;case 43:return"STR";case 44:this.begin("bqstring");break;case 45:this.popState();break;case 46:return"BQUOTE_STR";case 47:this.begin("href");break;case 48:this.popState();break;case 49:return 76;case 50:this.begin("callback_name");break;case 51:this.popState();break;case 52:this.popState(),this.begin("callback_args");break;case 53:return 74;case 54:this.popState();break;case 55:return 75;case 56:return 72;case 57:return 72;case 58:return 72;case 59:return 72;case 60:return 64;case 61:return 64;case 62:return 66;case 63:return 66;case 64:return 65;case 65:return 63;case 66:return 67;case 67:return 68;case 68:return 69;case 69:return 35;case 70:return 48;case 71:return 89;case 72:return"DOT";case 73:return"PLUS";case 74:return 86;case 75:return"EQUALS";case 76:return"EQUALS";case 77:return 93;case 78:return 27;case 79:return 29;case 80:return"PUNCTUATION";case 81:return 92;case 82:return 91;case 83:return 88;case 84:return 24}},rules:[/^(?:%%\{)/,/^(?:.*direction\s+TB[^\n]*)/,/^(?:.*direction\s+BT[^\n]*)/,/^(?:.*direction\s+RL[^\n]*)/,/^(?:.*direction\s+LR[^\n]*)/,/^(?:((?:(?!\}%%)[^:.])*))/,/^(?::)/,/^(?:\}%%)/,/^(?:((?:(?!\}%%).|\n)*))/,/^(?:%%(?!\{)*[^\n]*(\r?\n?)+)/,/^(?:%%[^\n]*(\r?\n)*)/,/^(?:accTitle\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*\{\s*)/,/^(?:[\}])/,/^(?:[^\}]*)/,/^(?:\s*(\r?\n)+)/,/^(?:\s+)/,/^(?:classDiagram-v2\b)/,/^(?:classDiagram\b)/,/^(?:[{])/,/^(?:\[\*\])/,/^(?:$)/,/^(?:[{])/,/^(?:[}])/,/^(?:[\n])/,/^(?:[^{}\n]*)/,/^(?:class\b)/,/^(?:cssClass\b)/,/^(?:callback\b)/,/^(?:link\b)/,/^(?:click\b)/,/^(?:note for\b)/,/^(?:note\b)/,/^(?:<<)/,/^(?:>>)/,/^(?:[~])/,/^(?:[~])/,/^(?:[^~]*)/,/^(?:["])/,/^(?:["])/,/^(?:[^"]*)/,/^(?:[`])/,/^(?:[`])/,/^(?:[^`]+)/,/^(?:href[\s]+["])/,/^(?:["])/,/^(?:[^"]*)/,/^(?:call[\s]+)/,/^(?:\([\s]*\))/,/^(?:\()/,/^(?:[^(]*)/,/^(?:\))/,/^(?:[^)]*)/,/^(?:_self\b)/,/^(?:_blank\b)/,/^(?:_parent\b)/,/^(?:_top\b)/,/^(?:\s*<\|)/,/^(?:\s*\|>)/,/^(?:\s*>)/,/^(?:\s*<)/,/^(?:\s*\*)/,/^(?:\s*o\b)/,/^(?:\s*\(\))/,/^(?:--)/,/^(?:\.\.)/,/^(?::{1}[^:\n;]+)/,/^(?::{3})/,/^(?:-)/,/^(?:\.)/,/^(?:\+)/,/^(?:%)/,/^(?:=)/,/^(?:=)/,/^(?:\w+)/,/^(?:\[)/,/^(?:\])/,/^(?:[!"#$%&'*+,-.`?\\/])/,/^(?:[0-9]+)/,/^(?:[\u00AA\u00B5\u00BA\u00C0-\u00D6\u00D8-\u00F6]|[\u00F8-\u02C1\u02C6-\u02D1\u02E0-\u02E4\u02EC\u02EE\u0370-\u0374\u0376\u0377]|[\u037A-\u037D\u0386\u0388-\u038A\u038C\u038E-\u03A1\u03A3-\u03F5]|[\u03F7-\u0481\u048A-\u0527\u0531-\u0556\u0559\u0561-\u0587\u05D0-\u05EA]|[\u05F0-\u05F2\u0620-\u064A\u066E\u066F\u0671-\u06D3\u06D5\u06E5\u06E6\u06EE]|[\u06EF\u06FA-\u06FC\u06FF\u0710\u0712-\u072F\u074D-\u07A5\u07B1\u07CA-\u07EA]|[\u07F4\u07F5\u07FA\u0800-\u0815\u081A\u0824\u0828\u0840-\u0858\u08A0]|[\u08A2-\u08AC\u0904-\u0939\u093D\u0950\u0958-\u0961\u0971-\u0977]|[\u0979-\u097F\u0985-\u098C\u098F\u0990\u0993-\u09A8\u09AA-\u09B0\u09B2]|[\u09B6-\u09B9\u09BD\u09CE\u09DC\u09DD\u09DF-\u09E1\u09F0\u09F1\u0A05-\u0A0A]|[\u0A0F\u0A10\u0A13-\u0A28\u0A2A-\u0A30\u0A32\u0A33\u0A35\u0A36\u0A38\u0A39]|[\u0A59-\u0A5C\u0A5E\u0A72-\u0A74\u0A85-\u0A8D\u0A8F-\u0A91\u0A93-\u0AA8]|[\u0AAA-\u0AB0\u0AB2\u0AB3\u0AB5-\u0AB9\u0ABD\u0AD0\u0AE0\u0AE1\u0B05-\u0B0C]|[\u0B0F\u0B10\u0B13-\u0B28\u0B2A-\u0B30\u0B32\u0B33\u0B35-\u0B39\u0B3D\u0B5C]|[\u0B5D\u0B5F-\u0B61\u0B71\u0B83\u0B85-\u0B8A\u0B8E-\u0B90\u0B92-\u0B95\u0B99]|[\u0B9A\u0B9C\u0B9E\u0B9F\u0BA3\u0BA4\u0BA8-\u0BAA\u0BAE-\u0BB9\u0BD0]|[\u0C05-\u0C0C\u0C0E-\u0C10\u0C12-\u0C28\u0C2A-\u0C33\u0C35-\u0C39\u0C3D]|[\u0C58\u0C59\u0C60\u0C61\u0C85-\u0C8C\u0C8E-\u0C90\u0C92-\u0CA8\u0CAA-\u0CB3]|[\u0CB5-\u0CB9\u0CBD\u0CDE\u0CE0\u0CE1\u0CF1\u0CF2\u0D05-\u0D0C\u0D0E-\u0D10]|[\u0D12-\u0D3A\u0D3D\u0D4E\u0D60\u0D61\u0D7A-\u0D7F\u0D85-\u0D96\u0D9A-\u0DB1]|[\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6\u0E01-\u0E30\u0E32\u0E33\u0E40-\u0E46\u0E81]|[\u0E82\u0E84\u0E87\u0E88\u0E8A\u0E8D\u0E94-\u0E97\u0E99-\u0E9F\u0EA1-\u0EA3]|[\u0EA5\u0EA7\u0EAA\u0EAB\u0EAD-\u0EB0\u0EB2\u0EB3\u0EBD\u0EC0-\u0EC4\u0EC6]|[\u0EDC-\u0EDF\u0F00\u0F40-\u0F47\u0F49-\u0F6C\u0F88-\u0F8C\u1000-\u102A]|[\u103F\u1050-\u1055\u105A-\u105D\u1061\u1065\u1066\u106E-\u1070\u1075-\u1081]|[\u108E\u10A0-\u10C5\u10C7\u10CD\u10D0-\u10FA\u10FC-\u1248\u124A-\u124D]|[\u1250-\u1256\u1258\u125A-\u125D\u1260-\u1288\u128A-\u128D\u1290-\u12B0]|[\u12B2-\u12B5\u12B8-\u12BE\u12C0\u12C2-\u12C5\u12C8-\u12D6\u12D8-\u1310]|[\u1312-\u1315\u1318-\u135A\u1380-\u138F\u13A0-\u13F4\u1401-\u166C]|[\u166F-\u167F\u1681-\u169A\u16A0-\u16EA\u1700-\u170C\u170E-\u1711]|[\u1720-\u1731\u1740-\u1751\u1760-\u176C\u176E-\u1770\u1780-\u17B3\u17D7]|[\u17DC\u1820-\u1877\u1880-\u18A8\u18AA\u18B0-\u18F5\u1900-\u191C]|[\u1950-\u196D\u1970-\u1974\u1980-\u19AB\u19C1-\u19C7\u1A00-\u1A16]|[\u1A20-\u1A54\u1AA7\u1B05-\u1B33\u1B45-\u1B4B\u1B83-\u1BA0\u1BAE\u1BAF]|[\u1BBA-\u1BE5\u1C00-\u1C23\u1C4D-\u1C4F\u1C5A-\u1C7D\u1CE9-\u1CEC]|[\u1CEE-\u1CF1\u1CF5\u1CF6\u1D00-\u1DBF\u1E00-\u1F15\u1F18-\u1F1D]|[\u1F20-\u1F45\u1F48-\u1F4D\u1F50-\u1F57\u1F59\u1F5B\u1F5D\u1F5F-\u1F7D]|[\u1F80-\u1FB4\u1FB6-\u1FBC\u1FBE\u1FC2-\u1FC4\u1FC6-\u1FCC\u1FD0-\u1FD3]|[\u1FD6-\u1FDB\u1FE0-\u1FEC\u1FF2-\u1FF4\u1FF6-\u1FFC\u2071\u207F]|[\u2090-\u209C\u2102\u2107\u210A-\u2113\u2115\u2119-\u211D\u2124\u2126\u2128]|[\u212A-\u212D\u212F-\u2139\u213C-\u213F\u2145-\u2149\u214E\u2183\u2184]|[\u2C00-\u2C2E\u2C30-\u2C5E\u2C60-\u2CE4\u2CEB-\u2CEE\u2CF2\u2CF3]|[\u2D00-\u2D25\u2D27\u2D2D\u2D30-\u2D67\u2D6F\u2D80-\u2D96\u2DA0-\u2DA6]|[\u2DA8-\u2DAE\u2DB0-\u2DB6\u2DB8-\u2DBE\u2DC0-\u2DC6\u2DC8-\u2DCE]|[\u2DD0-\u2DD6\u2DD8-\u2DDE\u2E2F\u3005\u3006\u3031-\u3035\u303B\u303C]|[\u3041-\u3096\u309D-\u309F\u30A1-\u30FA\u30FC-\u30FF\u3105-\u312D]|[\u3131-\u318E\u31A0-\u31BA\u31F0-\u31FF\u3400-\u4DB5\u4E00-\u9FCC]|[\uA000-\uA48C\uA4D0-\uA4FD\uA500-\uA60C\uA610-\uA61F\uA62A\uA62B]|[\uA640-\uA66E\uA67F-\uA697\uA6A0-\uA6E5\uA717-\uA71F\uA722-\uA788]|[\uA78B-\uA78E\uA790-\uA793\uA7A0-\uA7AA\uA7F8-\uA801\uA803-\uA805]|[\uA807-\uA80A\uA80C-\uA822\uA840-\uA873\uA882-\uA8B3\uA8F2-\uA8F7\uA8FB]|[\uA90A-\uA925\uA930-\uA946\uA960-\uA97C\uA984-\uA9B2\uA9CF\uAA00-\uAA28]|[\uAA40-\uAA42\uAA44-\uAA4B\uAA60-\uAA76\uAA7A\uAA80-\uAAAF\uAAB1\uAAB5]|[\uAAB6\uAAB9-\uAABD\uAAC0\uAAC2\uAADB-\uAADD\uAAE0-\uAAEA\uAAF2-\uAAF4]|[\uAB01-\uAB06\uAB09-\uAB0E\uAB11-\uAB16\uAB20-\uAB26\uAB28-\uAB2E]|[\uABC0-\uABE2\uAC00-\uD7A3\uD7B0-\uD7C6\uD7CB-\uD7FB\uF900-\uFA6D]|[\uFA70-\uFAD9\uFB00-\uFB06\uFB13-\uFB17\uFB1D\uFB1F-\uFB28\uFB2A-\uFB36]|[\uFB38-\uFB3C\uFB3E\uFB40\uFB41\uFB43\uFB44\uFB46-\uFBB1\uFBD3-\uFD3D]|[\uFD50-\uFD8F\uFD92-\uFDC7\uFDF0-\uFDFB\uFE70-\uFE74\uFE76-\uFEFC]|[\uFF21-\uFF3A\uFF41-\uFF5A\uFF66-\uFFBE\uFFC2-\uFFC7\uFFCA-\uFFCF]|[\uFFD2-\uFFD7\uFFDA-\uFFDC])/,/^(?:\s)/,/^(?:$)/],conditions:{acc_descr_multiline:{rules:[16,17],inclusive:!1},acc_descr:{rules:[14],inclusive:!1},acc_title:{rules:[12],inclusive:!1},arg_directive:{rules:[7,8],inclusive:!1},type_directive:{rules:[6,7],inclusive:!1},open_directive:{rules:[5],inclusive:!1},callback_args:{rules:[54,55],inclusive:!1},callback_name:{rules:[51,52,53],inclusive:!1},href:{rules:[48,49],inclusive:!1},struct:{rules:[23,24,25,26,27,28],inclusive:!1},generic:{rules:[39,40],inclusive:!1},bqstring:{rules:[45,46],inclusive:!1},string:{rules:[42,43],inclusive:!1},INITIAL:{rules:[0,1,2,3,4,9,10,11,13,15,18,19,20,21,22,23,29,30,31,32,33,34,35,36,37,38,41,44,47,50,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84],inclusive:!0}}};return Nt}();kt.lexer=Dt;function vt(){this.yy={}}return vt.prototype=kt,kt.Parser=vt,new vt}();oge.parser=oge;const XRe=oge,cge="classId-";let uge=[],hf={},OK=[],QRe=0,IP=[];const M5=i=>Wa.sanitizeText(i,Tt()),HHt=function(i,a,f){rd.parseDirective(this,i,a,f)},hL=function(i){let a="",f=i;if(i.indexOf("~")>0){const p=i.split("~");f=M5(p[0]),a=M5(p[1])}return{className:f,type:a}},zHt=function(i,a){a&&(a=M5(a));const{className:f}=hL(i);hf[f].label=a},lge=function(i){const a=hL(i);hf[a.className]===void 0&&(hf[a.className]={id:a.className,type:a.type,label:a.className,cssClasses:[],methods:[],members:[],annotations:[],domId:cge+a.className+"-"+QRe},QRe++)},ZRe=function(i){if(i in hf)return hf[i].domId;throw new Error("Class not found: "+i)},GHt=function(){uge=[],hf={},OK=[],IP=[],IP.push(eFe),rp()},qHt=function(i){return hf[i]},VHt=function(){return hf},UHt=function(){return uge},WHt=function(){return OK},KHt=function(i){Fe.debug("Adding relation: 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46:this.$={stmt:"state",id:Ot[kt-2].trim(),classes:[Ot[kt].trim()],type:"default",description:""};break;case 47:this.$={stmt:"state",id:Ot[kt-2].trim(),classes:[Ot[kt].trim()],type:"default",description:""};break;case 50:cn.parseDirective("%%{","open_directive");break;case 51:cn.parseDirective(Ot[kt],"type_directive");break;case 52:Ot[kt]=Ot[kt].trim().replace(/'/g,'"'),cn.parseDirective(Ot[kt],"arg_directive");break;case 53:cn.parseDirective("}%%","close_directive","state");break}},table:[{3:1,4:a,5:f,6:4,7:p,45:6,60:w},{1:[3]},{3:8,4:a,5:f,6:4,7:p,45:6,60:w},{3:9,4:a,5:f,6:4,7:p,45:6,60:w},{3:10,4:a,5:f,6:4,7:p,45:6,60:w},i([1,4,5,16,17,19,22,24,25,26,27,28,29,33,35,37,38,42,50,51,52,53,56,60],y,{8:11}),{46:12,61:[1,13]},{61:[2,50]},{1:[2,1]},{1:[2,2]},{1:[2,3]},{1:[2,4],4:b,5:E,6:30,9:14,10:16,11:18,12:19,13:20,16:S,17:N,19:B,22:R,24:j,25:$,26:V,27:Q,28:oe,29:ce,32:31,33:se,35:ge,37:ye,38:ke,42:Ae,45:6,50:de,51:ve,52:te,53:xe,56:De,60:w},{47:43,48:[1,44],63:he},i([48,63],[2,51]),i(Ie,[2,6]),{6:30,10:46,11:18,12:19,13:20,16:S,17:N,19:B,22:R,24:j,25:$,26:V,27:Q,28:oe,29:ce,32:31,33:se,35:ge,37:ye,38:ke,42:Ae,45:6,50:de,51:ve,52:te,53:xe,56:De,60:w},i(Ie,[2,8]),i(Ie,[2,9]),i(Ie,[2,10]),i(Ie,[2,11]),i(Ie,[2,12],{14:[1,47],15:[1,48]}),i(Ie,[2,16]),{18:[1,49]},i(Ie,[2,18],{20:[1,50]}),{23:[1,51]},i(Ie,[2,22]),i(Ie,[2,23]),i(Ie,[2,24]),i(Ie,[2,25]),{30:52,31:[1,53],58:[1,54],59:[1,55]},i(Ie,[2,28]),i(Ie,[2,29]),{34:[1,56]},{36:[1,57]},i(Ie,[2,32]),{39:[1,58],41:[1,59]},{43:[1,60]},i(ee,[2,44],{57:[1,61]}),i(ee,[2,45],{57:[1,62]}),i(Ie,[2,38]),i(Ie,[2,39]),i(Ie,[2,40]),i(Ie,[2,41]),i(rt,[2,36]),{49:63,62:[1,64]},i(rt,[2,53]),i(Ie,[2,7]),i(Ie,[2,13]),{13:65,24:j,56:De},i(Ie,[2,17]),i(me,y,{8:66}),{24:[1,67]},{24:[1,68]},{23:[1,69]},{24:[2,48]},{24:[2,49]},i(Ie,[2,30]),i(Ie,[2,31]),{40:[1,70]},{40:[1,71]},{44:[1,72]},{24:[1,73]},{24:[1,74]},{47:75,63:he},{63:[2,52]},i(Ie,[2,14],{14:[1,76]}),{4:b,5:E,6:30,9:14,10:16,11:18,12:19,13:20,16:S,17:N,19:B,21:[1,77],22:R,24:j,25:$,26:V,27:Q,28:oe,29:ce,32:31,33:se,35:ge,37:ye,38:ke,42:Ae,45:6,50:de,51:ve,52:te,53:xe,56:De,60:w},i(Ie,[2,20],{20:[1,78]}),{31:[1,79]},{24:[1,80]},i(Ie,[2,33]),i(Ie,[2,34]),i(Ie,[2,35]),i(ee,[2,46]),i(ee,[2,47]),i(rt,[2,37]),i(Ie,[2,15]),i(Ie,[2,19]),i(me,y,{8:81}),i(Ie,[2,26]),i(Ie,[2,27]),{4:b,5:E,6:30,9:14,10:16,11:18,12:19,13:20,16:S,17:N,19:B,21:[1,82],22:R,24:j,25:$,26:V,27:Q,28:oe,29:ce,32:31,33:se,35:ge,37:ye,38:ke,42:Ae,45:6,50:de,51:ve,52:te,53:xe,56:De,60:w},i(Ie,[2,21])],defaultActions:{7:[2,50],8:[2,1],9:[2,2],10:[2,3],54:[2,48],55:[2,49],64:[2,52]},parseError:function(jt,At){if(At.recoverable)this.trace(jt);else{var Bt=new Error(jt);throw Bt.hash=At,Bt}},parse:function(jt){var At=this,Bt=[0],cn=[],Nn=[null],Ot=[],oi=this.table,kt="",Dt=0,vt=0,Nt=2,ze=1,Xe=Ot.slice.call(arguments,1),Lt=Object.create(this.lexer),Ge={yy:{}};for(var Bn in this.yy)Object.prototype.hasOwnProperty.call(this.yy,Bn)&&(Ge.yy[Bn]=this.yy[Bn]);Lt.setInput(jt,Ge.yy),Ge.yy.lexer=Lt,Ge.yy.parser=this,typeof Lt.yylloc>"u"&&(Lt.yylloc={});var Oe=Lt.yylloc;Ot.push(Oe);var Ri=Lt.options&&Lt.options.ranges;typeof Ge.yy.parseError=="function"?this.parseError=Ge.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function tn(){var Hi;return Hi=cn.pop()||Lt.lex()||ze,typeof Hi!="number"&&(Hi instanceof Array&&(cn=Hi,Hi=cn.pop()),Hi=At.symbols_[Hi]||Hi),Hi}for(var hi,Sr,Zn,Xn,ir={},Hn,tr,ha,Zs;;){if(Sr=Bt[Bt.length-1],this.defaultActions[Sr]?Zn=this.defaultActions[Sr]:((hi===null||typeof hi>"u")&&(hi=tn()),Zn=oi[Sr]&&oi[Sr][hi]),typeof Zn>"u"||!Zn.length||!Zn[0]){var ns="";Zs=[];for(Hn in oi[Sr])this.terminals_[Hn]&&Hn>Nt&&Zs.push("'"+this.terminals_[Hn]+"'");Lt.showPosition?ns="Parse error on line "+(Dt+1)+`: +`+Lt.showPosition()+` +Expecting `+Zs.join(", ")+", got '"+(this.terminals_[hi]||hi)+"'":ns="Parse error on line "+(Dt+1)+": Unexpected "+(hi==ze?"end of input":"'"+(this.terminals_[hi]||hi)+"'"),this.parseError(ns,{text:Lt.match,token:this.terminals_[hi]||hi,line:Lt.yylineno,loc:Oe,expected:Zs})}if(Zn[0]instanceof Array&&Zn.length>1)throw new Error("Parse Error: multiple actions possible at state: "+Sr+", token: "+hi);switch(Zn[0]){case 1:Bt.push(hi),Nn.push(Lt.yytext),Ot.push(Lt.yylloc),Bt.push(Zn[1]),hi=null,vt=Lt.yyleng,kt=Lt.yytext,Dt=Lt.yylineno,Oe=Lt.yylloc;break;case 2:if(tr=this.productions_[Zn[1]][1],ir.$=Nn[Nn.length-tr],ir._$={first_line:Ot[Ot.length-(tr||1)].first_line,last_line:Ot[Ot.length-1].last_line,first_column:Ot[Ot.length-(tr||1)].first_column,last_column:Ot[Ot.length-1].last_column},Ri&&(ir._$.range=[Ot[Ot.length-(tr||1)].range[0],Ot[Ot.length-1].range[1]]),Xn=this.performAction.apply(ir,[kt,vt,Dt,Ge.yy,Zn[1],Nn,Ot].concat(Xe)),typeof Xn<"u")return Xn;tr&&(Bt=Bt.slice(0,-1*tr*2),Nn=Nn.slice(0,-1*tr),Ot=Ot.slice(0,-1*tr)),Bt.push(this.productions_[Zn[1]][0]),Nn.push(ir.$),Ot.push(ir._$),ha=oi[Bt[Bt.length-2]][Bt[Bt.length-1]],Bt.push(ha);break;case 3:return!0}}return!0}},pe=function(){var wt={EOF:1,parseError:function(At,Bt){if(this.yy.parser)this.yy.parser.parseError(At,Bt);else throw new Error(At)},setInput:function(jt,At){return this.yy=At||this.yy||{},this._input=jt,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},input:function(){var jt=this._input[0];this.yytext+=jt,this.yyleng++,this.offset++,this.match+=jt,this.matched+=jt;var At=jt.match(/(?:\r\n?|\n).*/g);return At?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),jt},unput:function(jt){var At=jt.length,Bt=jt.split(/(?:\r\n?|\n)/g);this._input=jt+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-At),this.offset-=At;var cn=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),Bt.length-1&&(this.yylineno-=Bt.length-1);var Nn=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:Bt?(Bt.length===cn.length?this.yylloc.first_column:0)+cn[cn.length-Bt.length].length-Bt[0].length:this.yylloc.first_column-At},this.options.ranges&&(this.yylloc.range=[Nn[0],Nn[0]+this.yyleng-At]),this.yyleng=this.yytext.length,this},more:function(){return this._more=!0,this},reject:function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true). +`+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},less:function(jt){this.unput(this.match.slice(jt))},pastInput:function(){var jt=this.matched.substr(0,this.matched.length-this.match.length);return(jt.length>20?"...":"")+jt.substr(-20).replace(/\n/g,"")},upcomingInput:function(){var jt=this.match;return jt.length<20&&(jt+=this._input.substr(0,20-jt.length)),(jt.substr(0,20)+(jt.length>20?"...":"")).replace(/\n/g,"")},showPosition:function(){var jt=this.pastInput(),At=new Array(jt.length+1).join("-");return jt+this.upcomingInput()+` +`+At+"^"},test_match:function(jt,At){var Bt,cn,Nn;if(this.options.backtrack_lexer&&(Nn={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(Nn.yylloc.range=this.yylloc.range.slice(0))),cn=jt[0].match(/(?:\r\n?|\n).*/g),cn&&(this.yylineno+=cn.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:cn?cn[cn.length-1].length-cn[cn.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+jt[0].length},this.yytext+=jt[0],this.match+=jt[0],this.matches=jt,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(jt[0].length),this.matched+=jt[0],Bt=this.performAction.call(this,this.yy,this,At,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),Bt)return Bt;if(this._backtrack){for(var Ot in Nn)this[Ot]=Nn[Ot];return!1}return!1},next:function(){if(this.done)return this.EOF;this._input||(this.done=!0);var jt,At,Bt,cn;this._more||(this.yytext="",this.match="");for(var Nn=this._currentRules(),Ot=0;OtAt[0].length)){if(At=Bt,cn=Ot,this.options.backtrack_lexer){if(jt=this.test_match(Bt,Nn[Ot]),jt!==!1)return jt;if(this._backtrack){At=!1;continue}else return!1}else if(!this.options.flex)break}return At?(jt=this.test_match(At,Nn[cn]),jt!==!1?jt:!1):this._input===""?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+`. Unrecognized text. +`+this.showPosition(),{text:"",token:null,line:this.yylineno})},lex:function(){var At=this.next();return At||this.lex()},begin:function(At){this.conditionStack.push(At)},popState:function(){var At=this.conditionStack.length-1;return At>0?this.conditionStack.pop():this.conditionStack[0]},_currentRules:function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},topState:function(At){return At=this.conditionStack.length-1-Math.abs(At||0),At>=0?this.conditionStack[At]:"INITIAL"},pushState:function(At){this.begin(At)},stateStackSize:function(){return this.conditionStack.length},options:{"case-insensitive":!0},performAction:function(At,Bt,cn,Nn){switch(cn){case 0:return 41;case 1:return 50;case 2:return 51;case 3:return 52;case 4:return 53;case 5:return this.begin("open_directive"),60;case 6:return this.begin("type_directive"),61;case 7:return this.popState(),this.begin("arg_directive"),48;case 8:return this.popState(),this.popState(),63;case 9:return 62;case 10:break;case 11:break;case 12:return 5;case 13:break;case 14:break;case 15:break;case 16:break;case 17:return this.pushState("SCALE"),17;case 18:return 18;case 19:this.popState();break;case 20:return this.begin("acc_title"),33;case 21:return this.popState(),"acc_title_value";case 22:return this.begin("acc_descr"),35;case 23:return this.popState(),"acc_descr_value";case 24:this.begin("acc_descr_multiline");break;case 25:this.popState();break;case 26:return"acc_descr_multiline_value";case 27:return this.pushState("CLASSDEF"),38;case 28:return this.popState(),this.pushState("CLASSDEFID"),"DEFAULT_CLASSDEF_ID";case 29:return this.popState(),this.pushState("CLASSDEFID"),39;case 30:return this.popState(),40;case 31:return this.pushState("CLASS"),42;case 32:return this.popState(),this.pushState("CLASS_STYLE"),43;case 33:return this.popState(),44;case 34:return this.pushState("SCALE"),17;case 35:return 18;case 36:this.popState();break;case 37:this.pushState("STATE");break;case 38:return this.popState(),Bt.yytext=Bt.yytext.slice(0,-8).trim(),25;case 39:return this.popState(),Bt.yytext=Bt.yytext.slice(0,-8).trim(),26;case 40:return this.popState(),Bt.yytext=Bt.yytext.slice(0,-10).trim(),27;case 41:return this.popState(),Bt.yytext=Bt.yytext.slice(0,-8).trim(),25;case 42:return this.popState(),Bt.yytext=Bt.yytext.slice(0,-8).trim(),26;case 43:return this.popState(),Bt.yytext=Bt.yytext.slice(0,-10).trim(),27;case 44:return 50;case 45:return 51;case 46:return 52;case 47:return 53;case 48:this.pushState("STATE_STRING");break;case 49:return this.pushState("STATE_ID"),"AS";case 50:return this.popState(),"ID";case 51:this.popState();break;case 52:return"STATE_DESCR";case 53:return 19;case 54:this.popState();break;case 55:return this.popState(),this.pushState("struct"),20;case 56:break;case 57:return this.popState(),21;case 58:break;case 59:return this.begin("NOTE"),29;case 60:return this.popState(),this.pushState("NOTE_ID"),58;case 61:return this.popState(),this.pushState("NOTE_ID"),59;case 62:this.popState(),this.pushState("FLOATING_NOTE");break;case 63:return this.popState(),this.pushState("FLOATING_NOTE_ID"),"AS";case 64:break;case 65:return"NOTE_TEXT";case 66:return this.popState(),"ID";case 67:return this.popState(),this.pushState("NOTE_TEXT"),24;case 68:return this.popState(),Bt.yytext=Bt.yytext.substr(2).trim(),31;case 69:return this.popState(),Bt.yytext=Bt.yytext.slice(0,-8).trim(),31;case 70:return 7;case 71:return 7;case 72:return 16;case 73:return 56;case 74:return 24;case 75:return Bt.yytext=Bt.yytext.trim(),14;case 76:return 15;case 77:return 28;case 78:return 57;case 79:return 5;case 80:return"INVALID"}},rules:[/^(?:default\b)/i,/^(?:.*direction\s+TB[^\n]*)/i,/^(?:.*direction\s+BT[^\n]*)/i,/^(?:.*direction\s+RL[^\n]*)/i,/^(?:.*direction\s+LR[^\n]*)/i,/^(?:%%\{)/i,/^(?:((?:(?!\}%%)[^:.])*))/i,/^(?::)/i,/^(?:\}%%)/i,/^(?:((?:(?!\}%%).|\n)*))/i,/^(?:%%(?!\{)[^\n]*)/i,/^(?:[^\}]%%[^\n]*)/i,/^(?:[\n]+)/i,/^(?:[\s]+)/i,/^(?:((?!\n)\s)+)/i,/^(?:#[^\n]*)/i,/^(?:%[^\n]*)/i,/^(?:scale\s+)/i,/^(?:\d+)/i,/^(?:\s+width\b)/i,/^(?:accTitle\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*\{\s*)/i,/^(?:[\}])/i,/^(?:[^\}]*)/i,/^(?:classDef\s+)/i,/^(?:DEFAULT\s+)/i,/^(?:\w+\s+)/i,/^(?:[^\n]*)/i,/^(?:class\s+)/i,/^(?:(\w+)+((,\s*\w+)*))/i,/^(?:[^\n]*)/i,/^(?:scale\s+)/i,/^(?:\d+)/i,/^(?:\s+width\b)/i,/^(?:state\s+)/i,/^(?:.*<>)/i,/^(?:.*<>)/i,/^(?:.*<>)/i,/^(?:.*\[\[fork\]\])/i,/^(?:.*\[\[join\]\])/i,/^(?:.*\[\[choice\]\])/i,/^(?:.*direction\s+TB[^\n]*)/i,/^(?:.*direction\s+BT[^\n]*)/i,/^(?:.*direction\s+RL[^\n]*)/i,/^(?:.*direction\s+LR[^\n]*)/i,/^(?:["])/i,/^(?:\s*as\s+)/i,/^(?:[^\n\{]*)/i,/^(?:["])/i,/^(?:[^"]*)/i,/^(?:[^\n\s\{]+)/i,/^(?:\n)/i,/^(?:\{)/i,/^(?:%%(?!\{)[^\n]*)/i,/^(?:\})/i,/^(?:[\n])/i,/^(?:note\s+)/i,/^(?:left of\b)/i,/^(?:right of\b)/i,/^(?:")/i,/^(?:\s*as\s*)/i,/^(?:["])/i,/^(?:[^"]*)/i,/^(?:[^\n]*)/i,/^(?:\s*[^:\n\s\-]+)/i,/^(?:\s*:[^:\n;]+)/i,/^(?:[\s\S]*?end note\b)/i,/^(?:stateDiagram\s+)/i,/^(?:stateDiagram-v2\s+)/i,/^(?:hide empty description\b)/i,/^(?:\[\*\])/i,/^(?:[^:\n\s\-\{]+)/i,/^(?:\s*:[^:\n;]+)/i,/^(?:-->)/i,/^(?:--)/i,/^(?::::)/i,/^(?:$)/i,/^(?:.)/i],conditions:{LINE:{rules:[14,15],inclusive:!1},close_directive:{rules:[14,15],inclusive:!1},arg_directive:{rules:[8,9,14,15],inclusive:!1},type_directive:{rules:[7,8,14,15],inclusive:!1},open_directive:{rules:[6,14,15],inclusive:!1},struct:{rules:[14,15,27,31,37,44,45,46,47,56,57,58,59,73,74,75,76,77],inclusive:!1},FLOATING_NOTE_ID:{rules:[66],inclusive:!1},FLOATING_NOTE:{rules:[63,64,65],inclusive:!1},NOTE_TEXT:{rules:[68,69],inclusive:!1},NOTE_ID:{rules:[67],inclusive:!1},NOTE:{rules:[60,61,62],inclusive:!1},CLASS_STYLE:{rules:[33],inclusive:!1},CLASS:{rules:[32],inclusive:!1},CLASSDEFID:{rules:[30],inclusive:!1},CLASSDEF:{rules:[28,29],inclusive:!1},acc_descr_multiline:{rules:[25,26],inclusive:!1},acc_descr:{rules:[23],inclusive:!1},acc_title:{rules:[21],inclusive:!1},SCALE:{rules:[18,19,35,36],inclusive:!1},ALIAS:{rules:[],inclusive:!1},STATE_ID:{rules:[50],inclusive:!1},STATE_STRING:{rules:[51,52],inclusive:!1},FORK_STATE:{rules:[],inclusive:!1},STATE:{rules:[14,15,38,39,40,41,42,43,48,49,53,54,55],inclusive:!1},ID:{rules:[14,15],inclusive:!1},INITIAL:{rules:[0,1,2,3,4,5,10,11,12,13,15,16,17,20,22,24,27,31,34,37,55,59,70,71,72,73,74,75,76,78,79,80],inclusive:!0}}};return wt}();gt.lexer=pe;function Et(){this.yy={}}return Et.prototype=gt,gt.Parser=Et,new Et}();dge.parser=dge;const sFe=dge,pzt="LR",bzt="TB",RK="state",gge="relation",vzt="classDef",wzt="applyClass",NP="default",aFe="divider",pge="[*]",oFe="start",cFe=pge,uFe="end",lFe="color",hFe="fill",mzt="bgFill",yzt=",";function fFe(){return{}}let dFe=pzt,FK=[],PP=fFe();const gFe=()=>({relations:[],states:{},documents:{}});let jK={root:gFe()},x0=jK.root,BP=0,pFe=0;const kzt={LINE:0,DOTTED_LINE:1},xzt={AGGREGATION:0,EXTENSION:1,COMPOSITION:2,DEPENDENCY:3},$K=i=>JSON.parse(JSON.stringify(i)),Ezt=function(i,a,f){rd.parseDirective(this,i,a,f)},Tzt=i=>{Fe.info("Setting root doc",i),FK=i},_zt=()=>FK,HK=(i,a,f)=>{if(a.stmt===gge)HK(i,a.state1,!0),HK(i,a.state2,!1);else if(a.stmt===RK&&(a.id==="[*]"?(a.id=f?i.id+"_start":i.id+"_end",a.start=f):a.id=a.id.trim()),a.doc){const p=[];let w=[],y;for(y=0;y0&&w.length>0){const b={stmt:RK,id:IIe(),type:"divider",doc:$K(w)};p.push($K(b)),a.doc=p}a.doc.forEach(b=>HK(a,b,!0))}},Czt=()=>(HK({id:"root"},{id:"root",doc:FK},!0),{id:"root",doc:FK}),Szt=i=>{let a;i.doc?a=i.doc:a=i,Fe.info(a),bFe(!0),Fe.info("Extract",a),a.forEach(f=>{switch(f.stmt){case RK:p9(f.id.trim(),f.type,f.doc,f.description,f.note,f.classes,f.styles,f.textStyles);break;case gge:vFe(f.state1,f.state2,f.description);break;case vzt:wFe(f.id.trim(),f.classes);break;case wzt:mge(f.id.trim(),f.styleClass);break}})},p9=function(i,a=NP,f=null,p=null,w=null,y=null,b=null,E=null){const S=i==null?void 0:i.trim();x0.states[S]===void 0?(Fe.info("Adding state ",S,p),x0.states[S]={id:S,descriptions:[],type:a,doc:f,note:w,classes:[],styles:[],textStyles:[]}):(x0.states[S].doc||(x0.states[S].doc=f),x0.states[S].type||(x0.states[S].type=a)),p&&(Fe.info("Setting state description",S,p),typeof p=="string"&&wge(S,p.trim()),typeof p=="object"&&p.forEach(N=>wge(S,N.trim()))),w&&(x0.states[S].note=w,x0.states[S].note.text=Wa.sanitizeText(x0.states[S].note.text,Tt())),y&&(Fe.info("Setting state classes",S,y),(typeof y=="string"?[y]:y).forEach(B=>mge(S,B.trim()))),b&&(Fe.info("Setting state styles",S,b),(typeof b=="string"?[b]:b).forEach(B=>Rzt(S,B.trim()))),E&&(Fe.info("Setting state styles",S,b),(typeof E=="string"?[E]:E).forEach(B=>Fzt(S,B.trim())))},bFe=function(i){jK={root:gFe()},x0=jK.root,BP=0,PP=fFe(),i||rp()},RP=function(i){return x0.states[i]},Azt=function(){return x0.states},Lzt=function(){Fe.info("Documents = ",jK)},Mzt=function(){return x0.relations};function bge(i=""){let a=i;return i===pge&&(BP++,a=`${oFe}${BP}`),a}function vge(i="",a=NP){return i===pge?oFe:a}function Dzt(i=""){let a=i;return i===cFe&&(BP++,a=`${uFe}${BP}`),a}function Izt(i="",a=NP){return i===cFe?uFe:a}function Ozt(i,a,f){let p=bge(i.id.trim()),w=vge(i.id.trim(),i.type),y=bge(a.id.trim()),b=vge(a.id.trim(),a.type);p9(p,w,i.doc,i.description,i.note,i.classes,i.styles,i.textStyles),p9(y,b,a.doc,a.description,a.note,a.classes,a.styles,a.textStyles),x0.relations.push({id1:p,id2:y,relationTitle:Wa.sanitizeText(f,Tt())})}const vFe=function(i,a,f){if(typeof i=="object")Ozt(i,a,f);else{const p=bge(i.trim()),w=vge(i),y=Dzt(a.trim()),b=Izt(a);p9(p,w),p9(y,b),x0.relations.push({id1:p,id2:y,title:Wa.sanitizeText(f,Tt())})}},wge=function(i,a){const f=x0.states[i],p=a.startsWith(":")?a.replace(":","").trim():a;f.descriptions.push(Wa.sanitizeText(p,Tt()))},Nzt=function(i){return i.substring(0,1)===":"?i.substr(2).trim():i.trim()},Pzt=()=>(pFe++,"divider-id-"+pFe),wFe=function(i,a=""){PP[i]===void 0&&(PP[i]={id:i,styles:[],textStyles:[]});const f=PP[i];a!=null&&a.split(yzt).forEach(p=>{const w=p.replace(/([^;]*);/,"$1").trim();if(p.match(lFe)){const b=w.replace(hFe,mzt).replace(lFe,hFe);f.textStyles.push(b)}f.styles.push(w)})},Bzt=function(){return PP},mge=function(i,a){i.split(",").forEach(function(f){let p=RP(f);if(p===void 0){const w=f.trim();p9(w),p=RP(w)}p.classes.push(a)})},Rzt=function(i,a){const f=RP(i);f!==void 0&&f.textStyles.push(a)},Fzt=function(i,a){const f=RP(i);f!==void 0&&f.textStyles.push(a)},D5={parseDirective:Ezt,getConfig:()=>Tt().state,addState:p9,clear:bFe,getState:RP,getStates:Azt,getRelations:Mzt,getClasses:Bzt,getDirection:()=>dFe,addRelation:vFe,getDividerId:Pzt,setDirection:i=>{dFe=i},cleanupLabel:Nzt,lineType:kzt,relationType:xzt,logDocuments:Lzt,getRootDoc:_zt,setRootDoc:Tzt,getRootDocV2:Czt,extract:Szt,trimColon:i=>i&&i[0]===":"?i.substr(1).trim():i.trim(),getAccTitle:L2,setAccTitle:ip,getAccDescription:D2,setAccDescription:M2,addStyleClass:wFe,setCssClass:mge,addDescription:wge,setDiagramTitle:Uw,getDiagramTitle:Ww},mFe=i=>` +defs #statediagram-barbEnd { + fill: ${i.transitionColor}; + stroke: ${i.transitionColor}; + } +g.stateGroup text { + fill: ${i.nodeBorder}; + stroke: none; + font-size: 10px; +} +g.stateGroup text { + fill: ${i.textColor}; + stroke: none; + font-size: 10px; + +} +g.stateGroup .state-title { + font-weight: bolder; + fill: ${i.stateLabelColor}; +} + +g.stateGroup rect { + fill: ${i.mainBkg}; + stroke: ${i.nodeBorder}; +} + +g.stateGroup line { + stroke: ${i.lineColor}; + stroke-width: 1; +} + +.transition { + stroke: ${i.transitionColor}; + stroke-width: 1; + fill: none; +} + +.stateGroup .composit { + fill: ${i.background}; + border-bottom: 1px +} + +.stateGroup .alt-composit { + fill: #e0e0e0; + border-bottom: 1px +} + +.state-note { + stroke: ${i.noteBorderColor}; + fill: ${i.noteBkgColor}; + + text { + fill: ${i.noteTextColor}; + stroke: none; + font-size: 10px; + } +} + +.stateLabel .box { + stroke: none; + stroke-width: 0; + fill: ${i.mainBkg}; + opacity: 0.5; +} + +.edgeLabel .label rect { + fill: ${i.labelBackgroundColor}; + opacity: 0.5; +} +.edgeLabel .label text { + fill: ${i.transitionLabelColor||i.tertiaryTextColor}; +} +.label div .edgeLabel { + color: ${i.transitionLabelColor||i.tertiaryTextColor}; +} + +.stateLabel text { + fill: ${i.stateLabelColor}; + font-size: 10px; + font-weight: bold; +} + +.node circle.state-start { + fill: ${i.specialStateColor}; + stroke: ${i.specialStateColor}; +} + +.node .fork-join { + fill: ${i.specialStateColor}; + stroke: ${i.specialStateColor}; +} + +.node circle.state-end { + fill: ${i.innerEndBackground}; + stroke: ${i.background}; + stroke-width: 1.5 +} +.end-state-inner { + fill: ${i.compositeBackground||i.background}; + // stroke: ${i.background}; + stroke-width: 1.5 +} + +.node rect { + fill: ${i.stateBkg||i.mainBkg}; + stroke: ${i.stateBorder||i.nodeBorder}; + stroke-width: 1px; +} +.node polygon { + fill: ${i.mainBkg}; + stroke: ${i.stateBorder||i.nodeBorder};; + stroke-width: 1px; +} +#statediagram-barbEnd { + fill: ${i.lineColor}; +} + +.statediagram-cluster rect { + fill: ${i.compositeTitleBackground}; + stroke: ${i.stateBorder||i.nodeBorder}; + stroke-width: 1px; +} + +.cluster-label, .nodeLabel { + color: ${i.stateLabelColor}; +} + +.statediagram-cluster rect.outer { + rx: 5px; + ry: 5px; +} +.statediagram-state .divider { + stroke: ${i.stateBorder||i.nodeBorder}; +} + +.statediagram-state .title-state { + rx: 5px; + ry: 5px; +} +.statediagram-cluster.statediagram-cluster .inner { + fill: ${i.compositeBackground||i.background}; +} +.statediagram-cluster.statediagram-cluster-alt .inner { + fill: ${i.altBackground?i.altBackground:"#efefef"}; +} + +.statediagram-cluster .inner { + rx:0; + ry:0; +} + +.statediagram-state rect.basic { + rx: 5px; + ry: 5px; +} +.statediagram-state rect.divider { + stroke-dasharray: 10,10; + fill: ${i.altBackground?i.altBackground:"#efefef"}; +} + +.note-edge { + stroke-dasharray: 5; +} + +.statediagram-note rect { + fill: ${i.noteBkgColor}; + stroke: ${i.noteBorderColor}; + stroke-width: 1px; + rx: 0; + ry: 0; +} +.statediagram-note rect { + fill: ${i.noteBkgColor}; + stroke: ${i.noteBorderColor}; + stroke-width: 1px; + rx: 0; + ry: 0; +} + +.statediagram-note text { + fill: ${i.noteTextColor}; +} + +.statediagram-note .nodeLabel { + color: ${i.noteTextColor}; +} +.statediagram .edgeLabel { + color: red; // ${i.noteTextColor}; +} + +#dependencyStart, #dependencyEnd { + fill: ${i.lineColor}; + stroke: ${i.lineColor}; + stroke-width: 1; +} + +.statediagramTitleText { + text-anchor: middle; + font-size: 18px; + fill: ${i.textColor}; +} +`,yge={},jzt=(i,a)=>{yge[i]=a},$zt=i=>yge[i],yFe=()=>Object.keys(yge),Hzt={get:$zt,set:jzt,keys:yFe,size:()=>yFe().length},zzt=i=>i.append("circle").attr("class","start-state").attr("r",Tt().state.sizeUnit).attr("cx",Tt().state.padding+Tt().state.sizeUnit).attr("cy",Tt().state.padding+Tt().state.sizeUnit),Gzt=i=>i.append("line").style("stroke","grey").style("stroke-dasharray","3").attr("x1",Tt().state.textHeight).attr("class","divider").attr("x2",Tt().state.textHeight*2).attr("y1",0).attr("y2",0),qzt=(i,a)=>{const f=i.append("text").attr("x",2*Tt().state.padding).attr("y",Tt().state.textHeight+2*Tt().state.padding).attr("font-size",Tt().state.fontSize).attr("class","state-title").text(a.id),p=f.node().getBBox();return i.insert("rect",":first-child").attr("x",Tt().state.padding).attr("y",Tt().state.padding).attr("width",p.width+2*Tt().state.padding).attr("height",p.height+2*Tt().state.padding).attr("rx",Tt().state.radius),f},Vzt=(i,a)=>{const f=function(j,$,V){const 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N.attr("x2",R+3*Tt().state.padding),i.insert("rect",":first-child").attr("x",Tt().state.padding).attr("y",Tt().state.padding).attr("width",R+2*Tt().state.padding).attr("height",B.height+y+2*Tt().state.padding).attr("rx",Tt().state.radius),i},Uzt=(i,a,f)=>{const p=Tt().state.padding,w=2*Tt().state.padding,y=i.node().getBBox(),b=y.width,E=y.x,S=i.append("text").attr("x",0).attr("y",Tt().state.titleShift).attr("font-size",Tt().state.fontSize).attr("class","state-title").text(a.id),B=S.node().getBBox().width+w;let R=Math.max(B,b);R===b&&(R=R+w);let j;const $=i.node().getBBox();a.doc,j=E-p,B>b&&(j=(b-R)/2+p),Math.abs(E-$.x)b&&(j=E-(B-b)/2);const V=1-Tt().state.textHeight;return i.insert("rect",":first-child").attr("x",j).attr("y",V).attr("class",f?"alt-composit":"composit").attr("width",R).attr("height",$.height+Tt().state.textHeight+Tt().state.titleShift+1).attr("rx","0"),S.attr("x",j+p),B<=b&&S.attr("x",E+(R-w)/2-B/2+p),i.insert("rect",":first-child").attr("x",j).attr("y",Tt().state.titleShift-Tt().state.textHeight-Tt().state.padding).attr("width",R).attr("height",Tt().state.textHeight*3).attr("rx",Tt().state.radius),i.insert("rect",":first-child").attr("x",j).attr("y",Tt().state.titleShift-Tt().state.textHeight-Tt().state.padding).attr("width",R).attr("height",$.height+3+2*Tt().state.textHeight).attr("rx",Tt().state.radius),i},Wzt=i=>(i.append("circle").attr("class","end-state-outer").attr("r",Tt().state.sizeUnit+Tt().state.miniPadding).attr("cx",Tt().state.padding+Tt().state.sizeUnit+Tt().state.miniPadding).attr("cy",Tt().state.padding+Tt().state.sizeUnit+Tt().state.miniPadding),i.append("circle").attr("class","end-state-inner").attr("r",Tt().state.sizeUnit).attr("cx",Tt().state.padding+Tt().state.sizeUnit+2).attr("cy",Tt().state.padding+Tt().state.sizeUnit+2)),Kzt=(i,a)=>{let f=Tt().state.forkWidth,p=Tt().state.forkHeight;if(a.parentId){let w=f;f=p,p=w}return i.append("rect").style("stroke","black").style("fill","black").attr("width",f).attr("height",p).attr("x",Tt().state.padding).attr("y",Tt().state.padding)},Yzt=(i,a,f,p)=>{let w=0;const y=p.append("text");y.style("text-anchor","start"),y.attr("class","noteText");let b=i.replace(/\r\n/g,"
");b=b.replace(/\n/g,"
");const E=b.split(Wa.lineBreakRegex);let S=1.25*Tt().state.noteMargin;for(const N of E){const B=N.trim();if(B.length>0){const R=y.append("tspan");if(R.text(B),S===0){const j=R.node().getBBox();S+=j.height}w+=S,R.attr("x",a+Tt().state.noteMargin),R.attr("y",f+w+1.25*Tt().state.noteMargin)}}return{textWidth:y.node().getBBox().width,textHeight:w}},Xzt=(i,a)=>{a.attr("class","state-note");const f=a.append("rect").attr("x",0).attr("y",Tt().state.padding),p=a.append("g"),{textWidth:w,textHeight:y}=Yzt(i,0,0,p);return f.attr("height",y+2*Tt().state.noteMargin),f.attr("width",w+Tt().state.noteMargin*2),f},kFe=function(i,a){const f=a.id,p={id:f,label:a.id,width:0,height:0},w=i.append("g").attr("id",f).attr("class","stateGroup");a.type==="start"&&zzt(w),a.type==="end"&&Wzt(w),(a.type==="fork"||a.type==="join")&&Kzt(w,a),a.type==="note"&&Xzt(a.note.text,w),a.type==="divider"&&Gzt(w),a.type==="default"&&a.descriptions.length===0&&qzt(w,a),a.type==="default"&&a.descriptions.length>0&&Vzt(w,a);const y=w.node().getBBox();return p.width=y.width+2*Tt().state.padding,p.height=y.height+2*Tt().state.padding,Hzt.set(f,p),p};let xFe=0;const Qzt=function(i,a,f){const p=function(S){switch(S){case D5.relationType.AGGREGATION:return"aggregation";case D5.relationType.EXTENSION:return"extension";case D5.relationType.COMPOSITION:return"composition";case D5.relationType.DEPENDENCY:return"dependency"}};a.points=a.points.filter(S=>!Number.isNaN(S.y));const w=a.points,y=WE().x(function(S){return S.x}).y(function(S){return S.y}).curve(SA),b=i.append("path").attr("d",y(w)).attr("id","edge"+xFe).attr("class","transition");let E="";if(Tt().state.arrowMarkerAbsolute&&(E=window.location.protocol+"//"+window.location.host+window.location.pathname+window.location.search,E=E.replace(/\(/g,"\\("),E=E.replace(/\)/g,"\\)")),b.attr("marker-end","url("+E+"#"+p(D5.relationType.DEPENDENCY)+"End)"),f.title!==void 0){const S=i.append("g").attr("class","stateLabel"),{x:N,y:B}=co.calcLabelPosition(a.points),R=Wa.getRows(f.title);let j=0;const $=[];let V=0,Q=0;for(let se=0;se<=R.length;se++){const ge=S.append("text").attr("text-anchor","middle").text(R[se]).attr("x",N).attr("y",B+j),ye=ge.node().getBBox();V=Math.max(V,ye.width),Q=Math.min(Q,ye.x),Fe.info(ye.x,N,B+j),j===0&&(j=ge.node().getBBox().height,Fe.info("Title height",j,B)),$.push(ge)}let oe=j*R.length;if(R.length>1){const se=(R.length-1)*j*.5;$.forEach((ge,ye)=>ge.attr("y",B+ye*j-se)),oe=j*R.length}const 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t,n,r;for(r=e.f,e.n=Me(pa,Ao,25,r,15,1),e.d=Me(pa,Ao,25,r,15,1),t=0;t0?e.c:0),++s;e.b=r,e.d=o}function Pun(e,t){var n,r,s,o,h;for(r=0,s=0,n=0,h=new C(t);h.a0?e.g:0),++n;e.c=s,e.d=r}function Dit(e,t){var n;return n=ie(re(pa,1),Ao,25,15,[y3e(e,(n1(),pc),t),y3e(e,lu,t),y3e(e,bc,t)]),e.f&&(n[0]=b.Math.max(n[0],n[2]),n[2]=n[0]),n}function Bun(e,t,n){var r;try{hz(e,t+e.j,n+e.k,!1,!0)}catch(s){throw s=ts(s),we(s,73)?(r=s,J(new Do(r.g+Pz+t+io+n+")."))):J(s)}}function Run(e,t,n){var r;try{hz(e,t+e.j,n+e.k,!0,!1)}catch(s){throw s=ts(s),we(s,73)?(r=s,J(new Do(r.g+Pz+t+io+n+")."))):J(s)}}function Iit(e){var t;ta(e,(pt(),Tw))&&(t=u(K(e,Tw),21),t.Hc((sy(),If))?(t.Mc(If),t.Fc(Of)):t.Hc(Of)&&(t.Mc(Of),t.Fc(If)))}function Oit(e){var t;ta(e,(pt(),Tw))&&(t=u(K(e,Tw),21),t.Hc((sy(),Pf))?(t.Mc(Pf),t.Fc(Zh)):t.Hc(Zh)&&(t.Mc(Zh),t.Fc(Pf)))}function Fun(e,t,n){kr(n,"Self-Loop ordering",1),ms(Cu(Vi(Vi(ic(new vn(null,new mn(t.b,16)),new rB),new VY),new UY),new WY),new mm(e)),ur(n)}function XD(e,t,n,r){var s,o;for(s=t;s0&&(s.b+=t),s}function HH(e,t){var n,r,s;for(s=new Fa,r=e.Kc();r.Ob();)n=u(r.Pb(),37),cC(n,0,s.b),s.b+=n.f.b+t,s.a=b.Math.max(s.a,n.f.a);return s.a>0&&(s.a+=t),s}function Pit(e){var t,n,r;for(r=Ei,n=new C(e.a);n.a>16==6?e.Cb.ih(e,5,h1,t):(r=go(u(gn((n=u(_n(e,16),26),n||e.zh()),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function Gun(e){k8();var t=e.e;if(t&&t.stack){var n=t.stack,r=t+` +`;return n.substring(0,r.length)==r&&(n=n.substring(r.length)),n.split(` +`)}return[]}function qun(e){var t;return t=(Zet(),I0t),t[e>>>28]|t[e>>24&15]<<4|t[e>>20&15]<<8|t[e>>16&15]<<12|t[e>>12&15]<<16|t[e>>8&15]<<20|t[e>>4&15]<<24|t[e&15]<<28}function Fit(e){var t,n,r;e.b==e.c&&(r=e.a.length,n=cye(b.Math.max(8,r))<<1,e.b!=0?(t=wf(e.a,n),att(e,t,r),e.a=t,e.b=0):rHe(e.a,n),e.c=r)}function Vun(e,t){var n;return n=e.b,n.Xe((bi(),kl))?n.Hf()==(ht(),Dn)?-n.rf().a-Ue(ft(n.We(kl))):t+Ue(ft(n.We(kl))):n.Hf()==(ht(),Dn)?-n.rf().a:t}function QD(e){var t;return e.b.c.length!=0&&u(St(e.b,0),70).a?u(St(e.b,0),70).a:(t=ere(e),t??""+(e.c?Yo(e.c.a,e,0):-1))}function zH(e){var t;return e.f.c.length!=0&&u(St(e.f,0),70).a?u(St(e.f,0),70).a:(t=ere(e),t??""+(e.i?Yo(e.i.j,e,0):-1))}function Uun(e,t){var n,r;if(t<0||t>=e.gc())return null;for(n=t;n0?e.c:0),s=b.Math.max(s,t.d),++r;e.e=o,e.b=s}function Kun(e){var t,n;if(!e.b)for(e.b=p$(u(e.f,118).Ag().i),n=new rr(u(e.f,118).Ag());n.e!=n.i.gc();)t=u(pr(n),137),it(e.b,new tte(t));return e.b}function Yun(e,t){var n,r,s;if(t.dc())return u8(),u8(),uN;for(n=new jUe(e,t.gc()),s=new rr(e);s.e!=s.i.gc();)r=pr(s),t.Hc(r)&&Br(n,r);return n}function L3e(e,t,n,r){return t==0?r?(!e.o&&(e.o=new Nl((cu(),k2),Dw,e,0)),e.o):(!e.o&&(e.o=new Nl((cu(),k2),Dw,e,0)),hD(e.o)):NH(e,t,n,r)}function bse(e){var t,n;if(e.rb)for(t=0,n=e.rb.i;t>22),s+=r>>22,s<0)?!1:(e.l=n&ml,e.m=r&ml,e.h=s&V0,!0)}function Jun(e,t,n,r,s,o,h){var d,v;return!(t.Ae()&&(v=e.a.ue(n,r),v<0||!s&&v==0)||t.Be()&&(d=e.a.ue(n,o),d>0||!h&&d==0))}function eln(e,t){X8();var n;if(n=e.j.g-t.j.g,n!=0)return 0;switch(e.j.g){case 2:return jie(t,r9e)-jie(e,r9e);case 4:return jie(e,n9e)-jie(t,n9e)}return 0}function tln(e){switch(e.g){case 0:return mle;case 1:return yle;case 2:return kle;case 3:return xle;case 4:return Mq;case 5:return Ele;default:return null}}function Ro(e,t,n){var r,s;return r=(s=new Wee,cb(s,t),au(s,n),Br((!e.c&&(e.c=new at(Iw,e,12,10)),e.c),s),s),Cg(r,0),Wm(r,1),Mg(r,!0),Lg(r,!0),r}function J6(e,t){var n,r;if(t>=e.i)throw J(new zte(t,e.i));return++e.j,n=e.g[t],r=e.i-t-1,r>0&&Hc(e.g,t+1,e.g,t,r),cs(e.g,--e.i,null),e.fi(t,n),e.ci(),n}function jit(e,t){var n,r;return e.Db>>16==17?e.Cb.ih(e,21,tf,t):(r=go(u(gn((n=u(_n(e,16),26),n||e.zh()),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function nln(e){var t,n,r,s;for(hn(),aa(e.c,e.a),s=new C(e.c);s.an.a.c.length))throw J(new Ln("index must be >= 0 and <= layer node count"));e.c&&Au(e.c.a,e),e.c=n,n&&Om(n.a,t,e)}function qit(e,t){var n,r,s;for(r=new cr(fr(j0(e).a.Kc(),new V));Vr(r);)return n=u(Pr(r),17),s=u(t.Kb(n),10),new Bx(Nr(s.n.b+s.o.b/2));return kT(),kT(),hue}function Vit(e,t){this.c=new Mr,this.a=e,this.b=t,this.d=u(K(e,(et(),G4)),304),je(K(e,(pt(),zTe)))===je((pD(),Dq))?this.e=new yHe:this.e=new mHe}function cln(e,t){var n,r,s,o;for(o=0,r=new C(e);r.a>16==6?e.Cb.ih(e,6,ra,t):(r=go(u(gn((n=u(_n(e,16),26),n||(cu(),qV)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function P3e(e,t){var n,r;return e.Db>>16==7?e.Cb.ih(e,1,iN,t):(r=go(u(gn((n=u(_n(e,16),26),n||(cu(),xAe)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function B3e(e,t){var n,r;return e.Db>>16==9?e.Cb.ih(e,9,hs,t):(r=go(u(gn((n=u(_n(e,16),26),n||(cu(),TAe)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function Wit(e,t){var n,r;return e.Db>>16==5?e.Cb.ih(e,9,JV,t):(r=go(u(gn((n=u(_n(e,16),26),n||(on(),Yg)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function R3e(e,t){var n,r;return e.Db>>16==3?e.Cb.ih(e,0,aN,t):(r=go(u(gn((n=u(_n(e,16),26),n||(on(),Kg)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function Kit(e,t){var n,r;return e.Db>>16==7?e.Cb.ih(e,6,h1,t):(r=go(u(gn((n=u(_n(e,16),26),n||(on(),Qg)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function Yit(){this.a=new VB,this.g=new FH,this.j=new FH,this.b=new Mr,this.d=new FH,this.i=new FH,this.k=new Mr,this.c=new Mr,this.e=new Mr,this.f=new Mr}function fln(e,t,n){var r,s,o;for(n<0&&(n=0),o=e.i,s=n;sioe)return o7(e,r);if(r==e)return!0}}return!1}function gln(e){switch(uj(),e.q.g){case 5:Oat(e,(ht(),An)),Oat(e,xr);break;case 4:Aot(e,(ht(),An)),Aot(e,xr);break;default:Alt(e,(ht(),An)),Alt(e,xr)}}function pln(e){switch(uj(),e.q.g){case 5:Kat(e,(ht(),$n)),Kat(e,Dn);break;case 4:sit(e,(ht(),$n)),sit(e,Dn);break;default:Llt(e,(ht(),$n)),Llt(e,Dn)}}function bln(e){var t,n;t=u(K(e,(a1(),dpt)),19),t?(n=t.a,n==0?Ye(e,(zp(),tq),new Fie):Ye(e,(zp(),tq),new m$(n))):Ye(e,(zp(),tq),new m$(1))}function vln(e,t){var n;switch(n=e.i,t.g){case 1:return-(e.n.b+e.o.b);case 2:return e.n.a-n.o.a;case 3:return e.n.b-n.o.b;case 4:return-(e.n.a+e.o.a)}return 0}function wln(e,t){switch(e.g){case 0:return t==(mh(),l2)?kq:xq;case 1:return t==(mh(),l2)?kq:bO;case 2:return t==(mh(),l2)?bO:xq;default:return bO}}function JD(e,t){var n,r,s;for(Au(e.a,t),e.e-=t.r+(e.a.c.length==0?0:e.c),s=Exe,r=new C(e.a);r.a>16==3?e.Cb.ih(e,12,hs,t):(r=go(u(gn((n=u(_n(e,16),26),n||(cu(),kAe)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function j3e(e,t){var n,r;return e.Db>>16==11?e.Cb.ih(e,10,hs,t):(r=go(u(gn((n=u(_n(e,16),26),n||(cu(),EAe)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function Xit(e,t){var n,r;return e.Db>>16==10?e.Cb.ih(e,11,tf,t):(r=go(u(gn((n=u(_n(e,16),26),n||(on(),Xg)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function Qit(e,t){var n,r;return e.Db>>16==10?e.Cb.ih(e,12,nf,t):(r=go(u(gn((n=u(_n(e,16),26),n||(on(),Ky)),e.Db>>16),18)),e.Cb.ih(e,r.n,r.f,t))}function $h(e){var t;return!(e.Bb&1)&&e.r&&e.r.kh()&&(t=u(e.r,49),e.r=u(Up(e,t),138),e.r!=t&&e.Db&4&&!(e.Db&1)&&_i(e,new oa(e,9,8,t,e.r))),e.r}function wse(e,t,n){var r;return r=ie(re(pa,1),Ao,25,15,[l4e(e,(n1(),pc),t,n),l4e(e,lu,t,n),l4e(e,bc,t,n)]),e.f&&(r[0]=b.Math.max(r[0],r[2]),r[2]=r[0]),r}function mln(e,t){var n,r,s;if(s=dun(e,t),s.c.length!=0)for(aa(s,new PY),n=s.c.length,r=0;r>19,x=t.h>>19,v!=x?x-v:(s=e.h,d=t.h,s!=d?s-d:(r=e.m,h=t.m,r!=h?r-h:(n=e.l,o=t.l,n-o)))}function GH(){GH=pe,S7e=(uz(),Mue),C7e=new dn(A6e,S7e),_7e=(P$(),Lue),T7e=new dn(L6e,_7e),E7e=(LH(),Aue),x7e=new dn(M6e,E7e),k7e=new dn(D6e,(Mn(),!0))}function Z_(e,t,n){var r,s;r=t*n,we(e.g,145)?(s=j6(e),s.f.d?s.f.a||(e.d.a+=r+z1):(e.d.d-=r+z1,e.d.a+=r+z1)):we(e.g,10)&&(e.d.d-=r,e.d.a+=2*r)}function Zit(e,t,n){var r,s,o,h,d;for(s=e[n.g],d=new C(t.d);d.a0?e.g:0),++n;t.b=r,t.e=s}function Jit(e){var t,n,r;if(r=e.b,mGe(e.i,r.length)){for(n=r.length*2,e.b=Me(pue,AI,317,n,0,1),e.c=Me(pue,AI,317,n,0,1),e.f=n-1,e.i=0,t=e.a;t;t=t.c)aI(e,t,t);++e.g}}function Sln(e,t,n,r){var s,o,h,d;for(s=0;sh&&(d=h/r),s>o&&(v=o/s),bd(e,b.Math.min(d,v)),e}function Lln(){pz();var e,t;try{if(t=u(X3e((Ap(),rf),H7),2014),t)return t}catch(n){if(n=ts(n),we(n,102))e=n,Rve((jr(),e));else throw J(n)}return new Y5}function Mln(){zJe();var e,t;try{if(t=u(X3e((Ap(),rf),_b),2024),t)return t}catch(n){if(n=ts(n),we(n,102))e=n,Rve((jr(),e));else throw J(n)}return new bm}function Dln(){pz();var e,t;try{if(t=u(X3e((Ap(),rf),Uh),1941),t)return t}catch(n){if(n=ts(n),we(n,102))e=n,Rve((jr(),e));else throw J(n)}return new KZ}function Iln(e,t,n){var r,s;return s=e.e,e.e=t,e.Db&4&&!(e.Db&1)&&(r=new oa(e,1,4,s,t),n?n.Ei(r):n=r),s!=t&&(t?n=E7(e,nz(e,t),n):n=E7(e,e.a,n)),n}function est(){kF.call(this),this.e=-1,this.a=!1,this.p=$a,this.k=-1,this.c=-1,this.b=-1,this.g=!1,this.f=-1,this.j=-1,this.n=-1,this.i=-1,this.d=-1,this.o=$a}function Oln(e,t){var n,r,s;if(r=e.b.d.d,e.a||(r+=e.b.d.a),s=t.b.d.d,t.a||(s+=t.b.d.a),n=Fs(r,s),n==0){if(!e.a&&t.a)return-1;if(!t.a&&e.a)return 1}return n}function Nln(e,t){var 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null;if(r=Xc(e,!0),s=tO.length,an(r.substr(r.length-s,s),tO)){if(n=r.length,n==4){if(t=(zr(0,r.length),r.charCodeAt(0)),t==43)return nLe;if(t==45)return F4t}else if(n==3)return nLe}return new hpe(r)}function agn(e){var t,n,r;return n=e.l,n&n-1||(r=e.m,r&r-1)||(t=e.h,t&t-1)||t==0&&r==0&&n==0?-1:t==0&&r==0&&n!=0?Dme(n):t==0&&r!=0&&n==0?Dme(r)+22:t!=0&&r==0&&n==0?Dme(t)+44:-1}function ogn(e,t){var n,r,s,o,h;for(kr(t,"Edge joining",1),n=It(Mt(K(e,(pt(),Jle)))),s=new C(e.b);s.a1)for(s=new C(e.a);s.a0),o.a.Xb(o.c=--o.b),Dm(o,s),Qn(o.b3&&e0(e,0,t-3))}function hgn(e){var t,n,r,s;return je(K(e,(pt(),Iy)))===je((F0(),Wg))?!e.e&&je(K(e,_O))!==je((q8(),wO)):(r=u(K(e,Hle),292),s=It(Mt(K(e,zle)))||je(K(e,dS))===je((V6(),vO)),t=u(K(e,kTe),19).a,n=e.a.c.length,!s&&r!=(q8(),wO)&&(t==0||t>n))}function fgn(e){var t,n;for(n=0;n0);n++);if(n>0&&n0);t++);return t>0&&n>16!=6&&t){if(o7(e,t))throw J(new Ln(FC+Zat(e)));r=null,e.Cb&&(r=(n=e.Db>>16,n>=0?N3e(e,r):e.Cb.ih(e,-1-n,null,r))),t&&(r=Q6(t,e,6,r)),r=Ibe(e,t,r),r&&r.Fi()}else e.Db&4&&!(e.Db&1)&&_i(e,new oa(e,1,6,t,t))}function c5e(e,t){var n,r;if(t!=e.Cb||e.Db>>16!=9&&t){if(o7(e,t))throw J(new Ln(FC+Nct(e)));r=null,e.Cb&&(r=(n=e.Db>>16,n>=0?B3e(e,r):e.Cb.ih(e,-1-n,null,r))),t&&(r=Q6(t,e,9,r)),r=Obe(e,t,r),r&&r.Fi()}else e.Db&4&&!(e.Db&1)&&_i(e,new oa(e,1,9,t,t))}function Wse(e,t){var n,r;if(t!=e.Cb||e.Db>>16!=3&&t){if(o7(e,t))throw J(new Ln(FC+Out(e)));r=null,e.Cb&&(r=(n=e.Db>>16,n>=0?F3e(e,r):e.Cb.ih(e,-1-n,null,r))),t&&(r=Q6(t,e,12,r)),r=Dbe(e,t,r),r&&r.Fi()}else e.Db&4&&!(e.Db&1)&&_i(e,new oa(e,1,3,t,t))}function b7(e){var t,n,r,s,o;if(r=$h(e),o=e.j,o==null&&r)return e.$j()?null:r.zj();if(we(r,148)){if(n=r.Aj(),n&&(s=n.Nh(),s!=e.i)){if(t=u(r,148),t.Ej())try{e.g=s.Kh(t,o)}catch(h){if(h=ts(h),we(h,78))e.g=null;else throw J(h)}e.i=s}return e.g}return null}function Pot(e){var t;return t=new st,it(t,new y6(new Pt(e.c,e.d),new Pt(e.c+e.b,e.d))),it(t,new y6(new Pt(e.c,e.d),new Pt(e.c,e.d+e.a))),it(t,new y6(new Pt(e.c+e.b,e.d+e.a),new Pt(e.c+e.b,e.d))),it(t,new y6(new Pt(e.c+e.b,e.d+e.a),new Pt(e.c,e.d+e.a))),t}function Bot(e,t,n,r){var s,o,h;if(h=U3e(t,n),r.c[r.c.length]=t,e.j[h.p]==-1||e.j[h.p]==2||e.a[t.p])return r;for(e.j[h.p]=-1,o=new cr(fr(j0(h).a.Kc(),new V));Vr(o);)if(s=u(Pr(o),17),!(!(!to(s)&&!(!to(s)&&s.c.i.c==s.d.i.c))||s==t))return Bot(e,s,h,r);return r}function dgn(e,t,n){var r,s,o;for(o=t.a.ec().Kc();o.Ob();)s=u(o.Pb(),79),r=u(er(e.b,s),266),!r&&(us(n0(s))==us(Kp(s))?Apn(e,s,n):n0(s)==us(Kp(s))?er(e.c,s)==null&&er(e.b,Kp(s))!=null&&plt(e,s,n,!1):er(e.d,s)==null&&er(e.b,n0(s))!=null&&plt(e,s,n,!0))}function ggn(e,t){var n,r,s,o,h,d,v;for(s=e.Kc();s.Ob();)for(r=u(s.Pb(),10),d=new $c,rc(d,r),Vs(d,(ht(),$n)),Ye(d,(et(),$q),(Mn(),!0)),h=t.Kc();h.Ob();)o=u(h.Pb(),10),v=new $c,rc(v,o),Vs(v,Dn),Ye(v,$q,!0),n=new Iv,Ye(n,$q,!0),Va(n,d),ba(n,v)}function pgn(e,t,n,r){var s,o,h,d;s=Drt(e,t,n),o=Drt(e,n,t),h=u(er(e.c,t),112),d=u(er(e.c,n),112),sr.b.g&&(o.c[o.c.length]=r);return o}function v7(){v7=pe,X4=new _M("CANDIDATE_POSITION_LAST_PLACED_RIGHT",0),Nk=new _M("CANDIDATE_POSITION_LAST_PLACED_BELOW",1),IS=new _M("CANDIDATE_POSITION_WHOLE_DRAWING_RIGHT",2),DS=new _M("CANDIDATE_POSITION_WHOLE_DRAWING_BELOW",3),OS=new _M("WHOLE_DRAWING",4)}function bgn(e,t){if(we(t,239))return Uan(e,u(t,33));if(we(t,186))return son(e,u(t,118));if(we(t,354))return wJt(e,u(t,137));if(we(t,352))return zbn(e,u(t,79));if(t)return null;throw J(new Ln(a8e+Yp(new Al(ie(re(Yn,1),yt,1,5,[t])))))}function vgn(e){var t,n,r,s,o,h,d;for(o=new as,s=new C(e.d.a);s.a1)for(t=Ev((n=new z2,++e.b,n),e.d),d=ii(o,0);d.b!=d.d.c;)h=u(ri(d),121),Cf(bf(pf(vf(gf(new Nh,1),0),t),h))}function u5e(e,t){var n,r;if(t!=e.Cb||e.Db>>16!=11&&t){if(o7(e,t))throw J(new Ln(FC+S5e(e)));r=null,e.Cb&&(r=(n=e.Db>>16,n>=0?j3e(e,r):e.Cb.ih(e,-1-n,null,r))),t&&(r=Q6(t,e,10,r)),r=Hbe(e,t,r),r&&r.Fi()}else e.Db&4&&!(e.Db&1)&&_i(e,new oa(e,1,11,t,t))}function wgn(e){var t,n,r,s;for(r=new ob(new dg(e.b).a);r.b;)n=$v(r),s=u(n.cd(),11),t=u(n.dd(),10),Ye(t,(et(),Mi),s),Ye(s,cl,t),Ye(s,kO,(Mn(),!0)),Vs(s,u(K(t,vc),61)),K(t,vc),Ye(s.i,(pt(),bs),(wa(),CE)),u(K(Ya(s.i),eu),21).Fc((mo(),uE))}function mgn(e,t,n){var r,s,o,h,d,v;if(o=0,h=0,e.c)for(v=new C(e.d.i.j);v.ao.a?-1:s.av){for(_=e.d,e.d=Me(SAe,p8e,63,2*v+4,0,1),o=0;o=9223372036854776e3?(D8(),B8e):(s=!1,e<0&&(s=!0,e=-e),r=0,e>=vb&&(r=_s(e/vb),e-=r*vb),n=0,e>=ck&&(n=_s(e/ck),e-=n*ck),t=_s(e),o=fu(t,n,r),s&&gie(o),o)}function Lgn(e,t){var n,r,s,o;for(n=!t||!e.u.Hc((ol(),Z0)),o=0,s=new C(e.e.Cf());s.a=-t&&r==t?new xa(ct(n-1),ct(r)):new xa(ct(n),ct(r-1))}function Hot(){return po(),ie(re(m3n,1),tt,77,0,[MEe,SEe,tS,ele,YEe,uq,mq,eE,WEe,FEe,VEe,J7,KEe,PEe,XEe,kEe,dq,tle,oq,bq,ZEe,pq,xEe,UEe,JEe,vq,QEe,cq,IEe,GEe,zEe,yq,_Ee,aq,hq,TEe,Z7,$Ee,BEe,qEe,nS,AEe,CEe,HEe,REe,fq,wq,EEe,gq,jEe,lq,OEe,DEe,pO,sq,NEe,LEe])}function Ogn(e,t,n){e.d=0,e.b=0,t.k==(zn(),Jc)&&n.k==Jc&&u(K(t,(et(),Mi)),10)==u(K(n,Mi),10)&&(Hre(t).j==(ht(),An)?Cot(e,t,n):Cot(e,n,t)),t.k==Jc&&n.k==ca?Hre(t).j==(ht(),An)?e.d=1:e.b=1:n.k==Jc&&t.k==ca&&(Hre(n).j==(ht(),An)?e.b=1:e.d=1),yun(e,t,n)}function Ngn(e){var t,n,r,s,o,h,d,v,x,_,L;return L=c4e(e),t=e.a,v=t!=null,v&&f8(L,"category",e.a),s=hM(new vm(e.d)),h=!s,h&&(x=new hg,t1(L,"knownOptions",x),n=new S$e(x),Da(new vm(e.d),n)),o=hM(e.g),d=!o,d&&(_=new hg,t1(L,"supportedFeatures",_),r=new A$e(_),Da(e.g,r)),L}function Pgn(e){var t,n,r,s,o,h,d,v,x;for(r=!1,t=336,n=0,o=new HUe(e.length),d=e,v=0,x=d.length;v>16!=7&&t){if(o7(e,t))throw J(new Ln(FC+Kst(e)));r=null,e.Cb&&(r=(n=e.Db>>16,n>=0?P3e(e,r):e.Cb.ih(e,-1-n,null,r))),t&&(r=u(t,49).gh(e,1,iN,r)),r=Ove(e,t,r),r&&r.Fi()}else e.Db&4&&!(e.Db&1)&&_i(e,new oa(e,1,7,t,t))}function zot(e,t){var n,r;if(t!=e.Cb||e.Db>>16!=3&&t){if(o7(e,t))throw J(new Ln(FC+rrt(e)));r=null,e.Cb&&(r=(n=e.Db>>16,n>=0?R3e(e,r):e.Cb.ih(e,-1-n,null,r))),t&&(r=u(t,49).gh(e,0,aN,r)),r=Nve(e,t,r),r&&r.Fi()}else e.Db&4&&!(e.Db&1)&&_i(e,new oa(e,1,3,t,t))}function Yse(e,t){d7();var n,r,s,o,h,d,v,x,_;return t.d>e.d&&(d=e,e=t,t=d),t.d<63?_pn(e,t):(h=(e.d&-2)<<4,x=Wwe(e,h),_=Wwe(t,h),r=hae(e,$6(x,h)),s=hae(t,$6(_,h)),v=Yse(x,_),n=Yse(r,s),o=Yse(hae(x,r),hae(s,_)),o=mae(mae(o,v),n),o=$6(o,h),v=$6(v,h<<1),mae(mae(v,o),n))}function Rgn(e,t,n){var r,s,o,h,d;for(h=H_(e,n),d=Me(h0,Bg,10,t.length,0,1),r=0,o=h.Kc();o.Ob();)s=u(o.Pb(),11),It(Mt(K(s,(et(),kO))))&&(d[r++]=u(K(s,cl),10));if(r=0;o+=n?1:-1)h=h|t.c.Sf(v,o,n,r&&!It(Mt(K(t.j,(et(),kw))))&&!It(Mt(K(t.j,(et(),z4))))),h=h|t.q._f(v,o,n),h=h|Sct(e,v[o],n,r);return Gs(e.c,t),h}function sz(e,t,n){var r,s,o,h,d,v,x,_,L,P;for(_=TQe(e.j),L=0,P=_.length;L1&&(e.a=!0),JQt(u(n.b,65),Ni(fc(u(t.b,65).c),bd(da(fc(u(n.b,65).a),u(t.b,65).a),s))),FXe(e,t),Got(e,n)}function qot(e){var t,n,r,s,o,h,d;for(o=new C(e.a.a);o.a0&&o>0?h.p=t++:r>0?h.p=n++:o>0?h.p=s++:h.p=n++}hn(),aa(e.j,new _L)}function zgn(e){var t,n;n=null,t=u(St(e.g,0),17);do{if(n=t.d.i,ta(n,(et(),Yh)))return u(K(n,Yh),11).i;if(n.k!=(zn(),Hs)&&Vr(new cr(fr(js(n).a.Kc(),new V))))t=u(Pr(new cr(fr(js(n).a.Kc(),new V))),17);else if(n.k!=Hs)return null}while(n&&n.k!=(zn(),Hs));return n}function Ggn(e,t){var n,r,s,o,h,d,v,x,_;for(d=t.j,h=t.g,v=u(St(d,d.c.length-1),113),_=(xn(0,d.c.length),u(d.c[0],113)),x=gse(e,h,v,_),o=1;ox&&(v=n,_=s,x=r);t.a=_,t.c=v}function qgn(e,t){var n,r;if(r=KM(e.b,t.b),!r)throw J(new Wo("Invalid hitboxes for scanline constraint calculation."));(Qtt(t.b,u(qKt(e.b,t.b),57))||Qtt(t.b,u(GKt(e.b,t.b),57)))&&(Ud(),t.b+""),e.a[t.b.f]=u(hne(e.b,t.b),57),n=u(lne(e.b,t.b),57),n&&(e.a[n.f]=t.b)}function Cf(e){if(!e.a.d||!e.a.e)throw J(new Wo((S0(sgt),sgt.k+" must have a source and target "+(S0(R7e),R7e.k)+" specified.")));if(e.a.d==e.a.e)throw J(new Wo("Network simplex does not support self-loops: "+e.a+" "+e.a.d+" "+e.a.e));return lj(e.a.d.g,e.a),lj(e.a.e.b,e.a),e.a}function Vgn(e,t,n){var r,s,o,h,d,v,x;for(x=new Sp(new Cje(e)),h=ie(re(Upt,1),ift,11,0,[t,n]),d=0,v=h.length;dv-e.b&&dv-e.a&&d0&&++z;++P}return z}function tpn(e,t){var n,r,s,o,h;for(h=u(K(t,(nw(),q_e)),425),o=ii(t.b,0);o.b!=o.d.c;)if(s=u(ri(o),86),e.b[s.g]==0){switch(h.g){case 0:wit(e,s);break;case 1:r0n(e,s)}e.b[s.g]=2}for(r=ii(e.a,0);r.b!=r.d.c;)n=u(ri(r),188),Xm(n.b.d,n,!0),Xm(n.c.b,n,!0);Ye(t,(Tc(),R_e),e.a)}function pu(e,t){ho();var n,r,s,o;return t?t==(Fi(),B4t)||(t==T4t||t==zb||t==E4t)&&e!=eLe?new s6e(e,t):(r=u(t,677),n=r.pk(),n||(m8(Po((Yu(),Oa),t)),n=r.pk()),o=(!n.i&&(n.i=new Mr),n.i),s=u(hc($o(o.f,e)),1942),!s&&Si(o,e,s=new s6e(e,t)),s):y4t}function npn(e,t){var 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r,s,o,h,d,v,x;if(r=n.gc(),r==0)return!1;if(e.ej())if(v=e.fj(),Qye(e,t,n),h=r==1?e.Zi(3,null,n.Kc().Pb(),t,v):e.Zi(5,null,n,t,v),e.bj()){for(d=r<100?null:new _p(r),o=t+r,s=t;s0){for(h=0;h>16==-15&&e.Cb.nh()&&Gre(new jre(e.Cb,9,13,n,e.c,Dg(gl(u(e.Cb,59)),e))):we(e.Cb,88)&&e.Db>>16==-23&&e.Cb.nh()&&(t=e.c,we(t,88)||(t=(on(),sf)),we(n,88)||(n=(on(),sf)),Gre(new jre(e.Cb,9,10,n,t,Dg(jc(u(e.Cb,26)),e)))))),e.c}function _bn(e,t){var n,r,s,o,h,d,v,x,_,L;for(kr(t,"Hypernodes processing",1),s=new C(e.b);s.an);return s}function gut(e,t){var n,r,s;r=vl(e.d,1)!=0,!It(Mt(K(t.j,(et(),kw))))&&!It(Mt(K(t.j,z4)))||je(K(t.j,(pt(),h2)))===je((R0(),f2))?t.c.Tf(t.e,r):r=It(Mt(K(t.j,kw))),gI(e,t,r,!0),It(Mt(K(t.j,z4)))&&Ye(t.j,z4,(Mn(),!1)),It(Mt(K(t.j,kw)))&&(Ye(t.j,kw,(Mn(),!1)),Ye(t.j,z4,!0)),n=Pse(e,t);do{if(zme(e),n==0)return 0;r=!r,s=n,gI(e,t,r,!1),n=Pse(e,t)}while(s>n);return s}function put(e,t,n){var r,s,o,h,d,v,x,_,L,P,z,q;if(t==n)return!0;if(t=U4e(e,t),n=U4e(e,n),r=ose(t),r){if(_=ose(n),_!=r)return 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o,h;if(o=Ua(qs(t[0],yo),qs(r[0],yo)),e[0]=Or(o),o=Np(o,32),n>=s){for(h=1;h0&&(s.b[h++]=0,s.b[h++]=o.b[0]-1),t=1;t0&&(tM(v,v.d-s.d),s.c==(Jf(),d2)&&Wge(v,v.a-s.d),v.d<=0&&v.i>0&&ks(t,v,t.c.b,t.c)));for(o=new C(e.f);o.a0&&(hT(d,d.i-s.d),s.c==(Jf(),d2)&&sv(d,d.b-s.d),d.i<=0&&d.d>0&&ks(n,d,n.c.b,n.c)))}function Pbn(e,t,n){var r,s,o,h,d,v,x,_;for(kr(n,"Processor compute fanout",1),sl(e.b),sl(e.a),d=null,o=ii(t.b,0);!d&&o.b!=o.d.c;)x=u(ri(o),86),It(Mt(K(x,(Tc(),$y))))&&(d=x);for(v=new as,ks(v,d,v.c.b,v.c),Mlt(e,v),_=ii(t.b,0);_.b!=_.d.c;)x=u(ri(_),86),h=Hr(K(x,(Tc(),AS))),s=Uc(e.b,h)!=null?u(Uc(e.b,h),19).a:0,Ye(x,gV,ct(s)),r=1+(Uc(e.a,h)!=null?u(Uc(e.a,h),19).a:0),Ye(x,cmt,ct(r));ur(n)}function Bbn(e,t,n,r,s){var o,h,d,v,x,_,L,P,z,q;for(P=mhn(e,n),v=0;v0),r.a.Xb(r.c=--r.b),L>P+v&&Ol(r);for(h=new C(z);h.a0),r.a.Xb(r.c=--r.b)}}function Rbn(){yi();var e,t,n,r,s,o;if(Mfe)return Mfe;for(e=new Hl(4),ly(e,Zp(cue,!0)),bC(e,Zp("M",!0)),bC(e,Zp("C",!0)),o=new Hl(4),r=0;r<11;r++)Yc(o,r,r);return t=new Hl(4),ly(t,Zp("M",!0)),Yc(t,4448,4607),Yc(t,65438,65439),s=new e_(2),pb(s,e),pb(s,nA),n=new e_(2),n.$l(Ij(o,Zp("L",!0))),n.$l(t),n=new $m(3,n),n=new Xve(s,n),Mfe=n,Mfe}function Fbn(e){var t,n;if(t=Hr(Ft(e,(bi(),PS))),!Ptt(t,e)&&!J2(e,xE)&&((!e.a&&(e.a=new at(hs,e,10,11)),e.a).i!=0||It(Mt(Ft(e,UO)))))if(t==null||ny(t).length==0){if(!Ptt(qn,e))throw n=Yr(Yr(new Fl("Unable to load default layout algorithm "),qn)," for unconfigured node "),yz(e,n),J(new M3(n.a))}else throw n=Yr(Yr(new Fl("Layout algorithm '"),t),"' not found for "),yz(e,n),J(new M3(n.a))}function uae(e){var t,n,r,s,o,h,d,v,x,_,L,P,z;if(n=e.i,t=e.n,e.b==0)for(z=n.c+t.b,P=n.b-t.b-t.c,h=e.a,v=0,_=h.length;v<_;++v)s=h[v],Nj(s,z,P);else r=vit(e,!1),Nj(e.a[0],n.c+t.b,r[0]),Nj(e.a[2],n.c+n.b-t.c-r[2],r[2]),L=n.b-t.b-t.c,r[0]>0&&(L-=r[0]+e.c,r[0]+=e.c),r[2]>0&&(L-=r[2]+e.c),r[1]=b.Math.max(r[1],L),Nj(e.a[1],n.c+t.b+r[0]-(r[1]-L)/2,r[1]);for(o=e.a,d=0,x=o.length;d0?(e.n.c.length-1)*e.i:0,r=new C(e.n);r.a1)for(r=ii(s,0);r.b!=r.d.c;)for(n=u(ri(r),231),o=0,v=new C(n.e);v.a0&&(t[0]+=e.c,L-=t[0]),t[2]>0&&(L-=t[2]+e.c),t[1]=b.Math.max(t[1],L),Pj(e.a[1],r.d+n.d+t[0]-(t[1]-L)/2,t[1]);else for(q=r.d+n.d,z=r.a-n.d-n.a,h=e.a,v=0,_=h.length;v<_;++v)s=h[v],Pj(s,q,z);for(o=e.a,d=0,x=o.length;d=0&&o!=n))throw J(new Ln(YI));for(s=0,v=0;v0||Kv(s.b.d,e.b.d+e.b.a)==0&&r.b<0||Kv(s.b.d+s.b.a,e.b.d)==0&&r.b>0){d=0;break}}else d=b.Math.min(d,Eat(e,s,r));d=b.Math.min(d,Eut(e,o,d,r))}return d}function mI(e,t){var n,r,s,o,h,d,v;if(e.b<2)throw J(new Ln("The vector chain must contain at least a source and a target point."));for(s=(Qn(e.b!=0),u(e.a.a.c,8)),nj(t,s.a,s.b),v=new _6((!t.a&&(t.a=new Bs(ef,t,5)),t.a)),h=ii(e,1);h.aUe(A1(h.g,h.d[0]).a)?(Qn(v.b>0),v.a.Xb(v.c=--v.b),Dm(v,h),s=!0):d.e&&d.e.gc()>0&&(o=(!d.e&&(d.e=new st),d.e).Mc(t),x=(!d.e&&(d.e=new st),d.e).Mc(n),(o||x)&&((!d.e&&(d.e=new st),d.e).Fc(h),++h.c));s||(r.c[r.c.length]=h)}function Cut(e){var t,n,r;if(R3(u(K(e,(pt(),bs)),98)))for(n=new C(e.j);n.a>>0,"0"+t.toString(16)),r="\\x"+jl(n,n.length-2,n.length)):e>=so?(n=(t=e>>>0,"0"+t.toString(16)),r="\\v"+jl(n,n.length-6,n.length)):r=""+String.fromCharCode(e&Ss)}return r}function hae(e,t){var n,r,s,o,h,d,v,x,_,L;if(h=e.e,v=t.e,v==0)return e;if(h==0)return t.e==0?t:new z3(-t.e,t.d,t.a);if(o=e.d,d=t.d,o+d==2)return n=qs(e.a[0],yo),r=qs(t.a[0],yo),h<0&&(n=M8(n)),v<0&&(r=M8(r)),WD(Wp(n,r));if(s=o!=d?o>d?1:-1:mye(e.a,t.a,o),s==-1)L=-v,_=h==v?Ore(t.a,d,e.a,o):Pre(t.a,d,e.a,o);else if(L=h,h==v){if(s==0)return Qp(),K7;_=Ore(e.a,o,t.a,d)}else _=Pre(e.a,o,t.a,d);return x=new z3(L,_.length,_),E_(x),x}function G5e(e){var t,n,r,s,o,h;for(this.e=new st,this.a=new st,n=e.b-1;n<3;n++)c8(e,0,u(s1(e,0),8));if(e.b<4)throw J(new Ln("At (least dimension + 1) control points are necessary!"));for(this.b=3,this.d=!0,this.c=!1,M0n(this,e.b+this.b-1),h=new st,o=new 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n,r,s,o,h,d,v,x,_,L,P,z;if(n=u(_o(e.b,t),124),v=u(u(Ii(e.r,t),21),84),v.dc()){n.n.d=0,n.n.a=0;return}for(x=e.u.Hc((ol(),Z0)),h=0,e.A.Hc((Bl(),Hb))&&Mct(e,t),d=v.Kc(),_=null,P=0,L=0;d.Ob();)r=u(d.Pb(),111),o=Ue(ft(r.b.We((uj(),WG)))),s=r.b.rf().b,_?(z=L+_.d.a+e.w+r.d.d,h=b.Math.max(h,(S1(),Ef(z1),b.Math.abs(P-o)<=z1||P==o||isNaN(P)&&isNaN(o)?0:z/(o-P)))):e.C&&e.C.d>0&&(h=b.Math.max(h,Ett(e.C.d+r.d.d,o))),_=r,P=o,L=s;e.C&&e.C.a>0&&(z=L+e.C.a,x&&(z+=_.d.a),h=b.Math.max(h,(S1(),Ef(z1),b.Math.abs(P-1)<=z1||P==1||isNaN(P)&&isNaN(1)?0:z/(1-P)))),n.n.d=0,n.a.b=h}function Zut(e,t,n){var r,s,o,h,d,v;for(this.g=e,d=t.d.length,v=n.d.length,this.d=Me(h0,Bg,10,d+v,0,1),h=0;h0?Xre(this,this.f/this.a):A1(t.g,t.d[0]).a!=null&&A1(n.g,n.d[0]).a!=null?Xre(this,(Ue(A1(t.g,t.d[0]).a)+Ue(A1(n.g,n.d[0]).a))/2):A1(t.g,t.d[0]).a!=null?Xre(this,A1(t.g,t.d[0]).a):A1(n.g,n.d[0]).a!=null&&Xre(this,A1(n.g,n.d[0]).a)}function Cwn(e,t){var n,r,s,o,h,d,v,x,_,L;for(e.a=new iYe(tsn(RS)),r=new C(t.a);r.a=1&&(X-h>0&&L>=0?(v.n.a+=W,v.n.b+=o*h):X-h<0&&_>=0&&(v.n.a+=W*X,v.n.b+=o));e.o.a=t.a,e.o.b=t.b,Ye(e,(pt(),Ib),(Bl(),r=u(Qf(qS),9),new hh(r,u(wf(r,r.length),9),0)))}function Mwn(e,t,n,r,s,o){var h;if(!(t==null||!$ie(t,OAe,NAe)))throw J(new Ln("invalid scheme: "+t));if(!e&&!(n!=null&&pd(n,Nu(35))==-1&&n.length>0&&(zr(0,n.length),n.charCodeAt(0)!=47)))throw J(new Ln("invalid opaquePart: "+n));if(e&&!(t!=null&&gM(ZV,t.toLowerCase()))&&!(n==null||!$ie(n,KS,YS)))throw J(new Ln(ydt+n));if(e&&t!=null&&gM(ZV,t.toLowerCase())&&!Ehn(n))throw J(new Ln(ydt+n));if(!Son(r))throw J(new Ln("invalid device: "+r));if(!yan(s))throw h=s==null?"invalid segments: null":"invalid segment: "+ban(s),J(new Ln(h));if(!(o==null||pd(o,Nu(35))==-1))throw J(new Ln("invalid query: "+o))}function Dwn(e,t){var n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le;for(kr(t,"Calculate Graph Size",1),t.n&&e&&yf(t,kf(e),(Pl(),nh)),d=O7,v=O7,o=Exe,h=Exe,L=new rr((!e.a&&(e.a=new 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C(Ce.e);h.a=x&&Ve>=X&&(P+=q.n.b+W.n.b+W.a.b-Ne,++d))}d>0&&(nt+=P/d,++z)}z>0?(t.a=s*nt/z,t.g=z):(t.a=0,t.g=0)}function Amn(e,t){var n,r,s,o,h,d,v,x,_,L,P;for(s=new C(e.a.b);s.aDs||t.o==Pb&&_0&&Du(le,Ne*nt),Ve>0&&Iu(le,Ve*bt);for(B_(e.b,new sm),t=new st,d=new ob(new dg(e.c).a);d.b;)h=$v(d),r=u(h.cd(),79),n=u(h.dd(),395).a,s=d4(r,!1,!1),L=mst(n0(r),iI(s),n),mI(L,s),Ee=Dst(r),Ee&&Yo(t,Ee,0)==-1&&(t.c[t.c.length]=Ee,PYe(Ee,(Qn(L.b!=0),u(L.a.a.c,8)),n));for(X=new ob(new dg(e.d).a);X.b;)W=$v(X),r=u(W.cd(),79),n=u(W.dd(),395).a,s=d4(r,!1,!1),L=mst(Kp(r),BD(iI(s)),n),L=BD(L),mI(L,s),Ee=Ist(r),Ee&&Yo(t,Ee,0)==-1&&(t.c[t.c.length]=Ee,PYe(Ee,(Qn(L.b!=0),u(L.c.b.c,8)),n))}function klt(e,t,n,r){var s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt;if(n.c.length!=0){for(z=new st,P=new C(n);P.a1)for(z=new Y5e(q,Ee,r),Da(Ee,new fqe(e,z)),h.c[h.c.length]=z,L=Ee.a.ec().Kc();L.Ob();)_=u(L.Pb(),46),Au(o,_.b);if(d.a.gc()>1)for(z=new Y5e(q,d,r),Da(d,new 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cr(fr(z0(Ne).a.Kc(),new V));Vr(_);)x=u(Pr(_),79),iC(x)||Fyn(x,t,bt,nt);bt+=s.b+s.c,nt+=s.d+s.a,sw(e,bt,nt,!1,!0)}function xz(e){var t,n,r,s,o,h,d,v,x,_,L;if(e==null)throw J(new gd(Pu));if(x=e,o=e.length,v=!1,o>0&&(t=(zr(0,e.length),e.charCodeAt(0)),(t==45||t==43)&&(e=e.substr(1),--o,v=t==45)),o==0)throw J(new gd(cw+x+'"'));for(;e.length>0&&(zr(0,e.length),e.charCodeAt(0)==48);)e=e.substr(1),--o;if(o>(hut(),O0t)[10])throw J(new gd(cw+x+'"'));for(s=0;s0&&(L=-parseInt(e.substr(0,r),10),e=e.substr(r),o-=r,n=!1);o>=h;){if(r=parseInt(e.substr(0,h),10),e=e.substr(h),o-=h,n)n=!1;else{if(Mc(L,d)<0)throw J(new gd(cw+x+'"'));L=ja(L,_)}L=Wp(L,r)}if(Mc(L,0)>0)throw J(new gd(cw+x+'"'));if(!v&&(L=M8(L),Mc(L,0)<0))throw J(new gd(cw+x+'"'));return L}function s6e(e,t){ZWe();var n,r,s,o,h,d,v;if(this.a=new Y2e(this),this.b=e,this.c=t,this.f=Bne(Po((Yu(),Oa),t)),this.f.dc())if((d=q3e(Oa,e))==t)for(this.e=!0,this.d=new st,this.f=new xx,this.f.Fc(_b),u(wz(wD(Oa,Gl(e)),""),26)==e&&this.f.Fc(f_(Oa,Gl(e))),s=iae(Oa,e).Kc();s.Ob();)switch(r=u(s.Pb(),170),Dv(Po(Oa,r))){case 4:{this.d.Fc(r);break}case 5:{this.f.Gc(Bne(Po(Oa,r)));break}}else if(ho(),u(t,66).Oj())for(this.e=!0,this.f=null,this.d=new st,h=0,v=(e.i==null&&xd(e),e.i).length;h=0&&h0&&(u(_o(e.b,t),124).a.b=n)}function Fmn(e,t){var n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le;for(kr(t,"Comment pre-processing",1),n=0,v=new C(e.a);v.a0&&(v=(zr(0,t.length),t.charCodeAt(0)),v!=64)){if(v==37&&(L=t.lastIndexOf("%"),x=!1,L!=0&&(L==P-1||(x=(zr(L+1,t.length),t.charCodeAt(L+1)==46))))){if(h=t.substr(1,L-1),Ee=an("%",h)?null:o6e(h),r=0,x)try{r=Wl(t.substr(L+2),$a,Ei)}catch(Ne){throw Ne=ts(Ne),we(Ne,127)?(d=Ne,J(new D$(d))):J(Ne)}for(X=Hme(e.Wg());X.Ob();)if(q=aH(X),we(q,510)&&(s=u(q,590),Ce=s.d,(Ee==null?Ce==null:an(Ee,Ce))&&r--==0))return s;return null}if(_=t.lastIndexOf("."),z=_==-1?t:t.substr(0,_),n=0,_!=-1)try{n=Wl(t.substr(_+1),$a,Ei)}catch(Ne){if(Ne=ts(Ne),we(Ne,127))z=t;else throw J(Ne)}for(z=an("%",z)?null:o6e(z),W=Hme(e.Wg());W.Ob();)if(q=aH(W),we(q,191)&&(o=u(q,191),le=o.ne(),(z==null?le==null:an(z,le))&&n--==0))return o;return null}return Kut(e,t)}function Hmn(e){var t,n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn;for(nt=new st,q=new C(e.b);q.a=t.length)return{done:!0};var s=t[r++];return{value:[s,n.get(s)],done:!1}}}},Upn()||(e.prototype.createObject=function(){return{}},e.prototype.get=function(t){return this.obj[":"+t]},e.prototype.set=function(t,n){this.obj[":"+t]=n},e.prototype[coe]=function(t){delete this.obj[":"+t]},e.prototype.keys=function(){var t=[];for(var n in this.obj)n.charCodeAt(0)==58&&t.push(n.substring(1));return t}),e}function Gmn(e){j5e();var t,n,r,s,o,h,d,v,x,_,L,P,z,q,W,X;if(e==null)return null;if(L=e.length*8,L==0)return"";for(d=L%24,z=L/24|0,P=d!=0?z+1:z,o=null,o=Me(Sh,Td,25,P*4,15,1),x=0,_=0,t=0,n=0,r=0,h=0,s=0,v=0;v>24,x=(t&3)<<24>>24,q=t&-128?(t>>2^192)<<24>>24:t>>2<<24>>24,W=n&-128?(n>>4^240)<<24>>24:n>>4<<24>>24,X=r&-128?(r>>6^252)<<24>>24:r>>6<<24>>24,o[h++]=Zg[q],o[h++]=Zg[W|x<<4],o[h++]=Zg[_<<2|X],o[h++]=Zg[r&63];return d==8?(t=e[s],x=(t&3)<<24>>24,q=t&-128?(t>>2^192)<<24>>24:t>>2<<24>>24,o[h++]=Zg[q],o[h++]=Zg[x<<4],o[h++]=61,o[h++]=61):d==16&&(t=e[s],n=e[s+1],_=(n&15)<<24>>24,x=(t&3)<<24>>24,q=t&-128?(t>>2^192)<<24>>24:t>>2<<24>>24,W=n&-128?(n>>4^240)<<24>>24:n>>4<<24>>24,o[h++]=Zg[q],o[h++]=Zg[W|x<<4],o[h++]=Zg[_<<2],o[h++]=61),jh(o,0,o.length)}function qmn(e,t){var n,r,s,o,h,d,v;if(e.e==0&&e.p>0&&(e.p=-(e.p-1)),e.p>$a&&$we(t,e.p-e2),h=t.q.getDate(),tD(t,1),e.k>=0&&Cen(t,e.k),e.c>=0?tD(t,e.c):e.k>=0?(v=new oye(t.q.getFullYear()-e2,t.q.getMonth(),35),r=35-v.q.getDate(),tD(t,b.Math.min(r,h))):tD(t,h),e.f<0&&(e.f=t.q.getHours()),e.b>0&&e.f<12&&(e.f+=12),RWt(t,e.f==24&&e.g?0:e.f),e.j>=0&&Rnn(t,e.j),e.n>=0&&trn(t,e.n),e.i>=0&&Qqe(t,Ua(ja(eI(Ou(t.q.getTime()),Pg),Pg),e.i)),e.a&&(s=new kF,$we(s,s.q.getFullYear()-e2-80),fte(Ou(t.q.getTime()),Ou(s.q.getTime()))&&$we(t,s.q.getFullYear()-e2+100)),e.d>=0){if(e.c==-1)n=(7+e.d-t.q.getDay())%7,n>3&&(n-=7),d=t.q.getMonth(),tD(t,t.q.getDate()+n),t.q.getMonth()!=d&&tD(t,t.q.getDate()+(n>0?-7:7));else if(t.q.getDay()!=e.d)return!1}return e.o>$a&&(o=t.q.getTimezoneOffset(),Qqe(t,Ua(Ou(t.q.getTime()),(e.o-o)*60*Pg))),!0}function Clt(e,t){var n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne;if(s=K(t,(et(),Mi)),!!we(s,239)){for(q=u(s,33),W=t.e,P=new Io(t.c),o=t.d,P.a+=o.b,P.b+=o.d,Ne=u(Ft(q,(pt(),Jq)),174),Vu(Ne,(wl(),$V))&&(z=u(Ft(q,qTe),116),jge(z,o.a),wee(z,o.d),$ge(z,o.b),Vge(z,o.c)),n=new st,_=new C(t.a);_.a<_.c.c.length;)for(v=u(Y(_),10),we(K(v,Mi),239)?Xmn(v,P):we(K(v,Mi),186)&&!W&&(r=u(K(v,Mi),118),Ce=vut(t,v,r.g,r.f),C1(r,Ce.a,Ce.b)),le=new C(v.j);le.a0&&it(e.p,_),it(e.o,_);t-=r,z=v+t,x+=t*e.e,gh(e.a,d,ct(z)),gh(e.b,d,x),e.j=b.Math.max(e.j,z),e.k=b.Math.max(e.k,x),e.d+=t,t+=W}}function ht(){ht=pe;var e;uc=new MM(EC,0),An=new MM(Oz,1),$n=new MM(woe,2),xr=new MM(moe,3),Dn=new MM(yoe,4),Q1=(hn(),new Kx((e=u(Qf(ao),9),new 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$r(Ur((jr(),hdt))));if(n=r,t==44){if(s>=e.j)throw J(new $r(Ur((jr(),ddt))));if((t=Ma(e.i,s++))>=48&&t<=57){for(n=t-48;s=48&&t<=57;)if(n=n*10+t-48,n<0)throw J(new $r(Ur((jr(),d8e))));if(r>n)throw J(new $r(Ur((jr(),gdt))))}else n=-1}if(t!=125)throw J(new $r(Ur((jr(),fdt))));e.sl(s)?(o=(yi(),yi(),new $m(9,o)),e.d=s+1):(o=(yi(),yi(),new $m(3,o)),e.d=s),o.dm(r),o.cm(n),mi(e)}}return o}function Glt(e,t,n,r,s){var o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn;for(W=new su(t.b),Ne=new su(t.b),P=new su(t.b),zt=new su(t.b),X=new su(t.b),bt=ii(t,0);bt.b!=bt.d.c;)for(Ve=u(ri(bt),11),d=new C(Ve.g);d.a0,le=Ve.g.c.length>0,x&&le?P.c[P.c.length]=Ve:x?W.c[W.c.length]=Ve:le&&(Ne.c[Ne.c.length]=Ve);for(q=new C(W);q.a1)for(q=new _6((!e.a&&(e.a=new at(os,e,6,6)),e.a));q.e!=q.i.gc();)J_(q);for(h=u(Te((!e.a&&(e.a=new at(os,e,6,6)),e.a),0),202),X=ki,ki>Ve+Ne?X=Ve+Ne:kint+W?le=nt+W:WsVe-Ne&&Xnt-W&&leki+dr?zt=ki+dr:VeWs+bt?Ut=Ws+bt:ntki-dr&&ztWs-bt&&Utn&&(P=n-1),z=pN+vl(t,24)*NI*L-L/2,z<0?z=1:z>r&&(z=r-1),s=(pv(),v=new pp,v),z$(s,P),G$(s,z),Br((!h.a&&(h.a=new Bs(ef,h,5)),h.a),s)}function pt(){pt=pe,Xle=(bi(),c3t),QTe=u3t,SO=zSe,Mf=l3t,Ok=GSe,Sw=h3t,Ry=qSe,bE=VSe,vE=USe,Qle=RV,Aw=jb,Zle=f3t,bS=YSe,eV=Fk,CO=(f6e(),svt),V4=avt,Nb=ovt,U4=cvt,Vvt=new fo(BV,ct(0)),pE=nvt,XTe=rvt,Ik=ivt,s_e=Mvt,ZTe=hvt,JTe=gvt,ehe=kvt,e_e=vvt,t_e=mvt,tV=Nvt,the=Dvt,r_e=Cvt,n_e=Tvt,i_e=Avt,_w=Xbt,pS=Qbt,Vle=gbt,ATe=bbt,VTe=new kv(12),qTe=new fo(Fb,VTe),_Te=($0(),_E),K0=new fo(wSe,_Te),Ny=new fo(kl,0),Uvt=new fo(ufe,ct(1)),Hq=new fo(Bk,N7),Ob=PV,bs=BS,gE=t5,Fvt=VO,Bd=Jyt,Iy=Q4,Wvt=new fo(lfe,(Mn(),!0)),Oy=UO,Db=nfe,Ib=Rb,Jq=p2,Yle=NV,TTe=(wo(),f0),Zl=new fo(Mw,TTe),Tw=J4,Qq=SSe,Py=Hy,qvt=cfe,KTe=$Se,WTe=(n4(),ZO),new fo(PSe,WTe),Hvt=ife,zvt=sfe,Gvt=afe,$vt=rfe,Jle=lvt,jTe=Fbt,Wle=Rbt,vS=uvt,vu=Mbt,Dy=abt,dS=sbt,My=U2t,kTe=W2t,Hle=Q2t,_O=K2t,zle=rbt,$Te=jbt,HTe=$bt,NTe=Tbt,Zq=evt,Kle=Gbt,Ule=mbt,GTe=Kbt,STe=fbt,qle=dbt,$le=IV,zTe=Hbt,Gq=j2t,wTe=F2t,zq=R2t,DTe=xbt,MTe=kbt,ITe=Ebt,fE=e5,Fo=Z4,Hg=ySe,Rd=tfe,Gle=efe,xTe=J2t,zg=ofe,fS=n3t,Kq=r3t,Cw=RSe,UTe=i3t,dE=s3t,BTe=Ibt,RTe=Nbt,By=Rk,Fle=B2t,FTe=Bbt,Wq=ubt,Uq=cbt,Xq=WO,PTe=Sbt,gS=Vbt,AO=WSe,ETe=obt,YTe=tvt,CTe=lbt,jvt=Lbt,Rvt=tbt,OTe=TSe,Yq=Dbt,Vq=nbt,h2=V2t,yTe=G2t,qq=H2t,mTe=z2t,jle=q2t,Dk=$2t,LTe=ybt}function Lae(e,t){pae();var n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn,dr,ki;if(zt=e.e,q=e.d,s=e.a,zt==0)switch(t){case 0:return"0";case 1:return L7;case 2:return"0.00";case 3:return"0.000";case 4:return"0.0000";case 5:return"0.00000";case 6:return"0.000000";default:return nt=new Tp,t<0?nt.a+="0E+":nt.a+="0E",nt.a+=-t,nt.a}if(Ee=q*10+1+7,Ne=Me(Sh,Td,25,Ee+1,15,1),n=Ee,q==1)if(d=s[0],d<0){ki=qs(d,yo);do W=ki,ki=eI(ki,10),Ne[--n]=48+Or(Wp(W,ja(ki,10)))&Ss;while(Mc(ki,0)!=0)}else{ki=d;do W=ki,ki=ki/10|0,Ne[--n]=48+(W-ki*10)&Ss;while(ki!=0)}else{In=Me(Lr,Jr,25,q,15,1),dr=q,Hc(s,0,In,0,dr);e:for(;;){for(bt=0,x=dr-1;x>=0;x--)Rn=Ua(A0(bt,32),qs(In[x],yo)),le=Ghn(Rn),In[x]=Or(le),bt=Or(Np(le,32));Ce=Or(bt),X=n;do Ne[--n]=48+Ce%10&Ss;while((Ce=Ce/10|0)!=0&&n!=0);for(r=9-X+n,v=0;v0;v++)Ne[--n]=48;for(L=dr-1;In[L]==0;L--)if(L==0)break e;dr=L+1}for(;Ne[n]==48;)++n}if(z=zt<0,h=Ee-n-t-1,t==0)return z&&(Ne[--n]=45),jh(Ne,n,Ee-n);if(t>0&&h>=-6){if(h>=0){for(_=n+h,P=Ee-1;P>=_;P--)Ne[P+1]=Ne[P];return Ne[++_]=46,z&&(Ne[--n]=45),jh(Ne,n,Ee-n+1)}for(L=2;L<-h+1;L++)Ne[--n]=48;return Ne[--n]=46,Ne[--n]=48,z&&(Ne[--n]=45),jh(Ne,n,Ee-n)}return Ut=n+1,o=Ee,Ve=new xm,z&&(Ve.a+="-"),o-Ut>=1?(Bp(Ve,Ne[n]),Ve.a+=".",Ve.a+=jh(Ne,n+1,Ee-n-1)):Ve.a+=jh(Ne,n,Ee-n),Ve.a+="E",h>0&&(Ve.a+="+"),Ve.a+=""+h,Ve.a}function Ult(e,t){var n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt;switch(e.c=t,e.g=new Mr,n=(Tm(),new ym(e.c)),r=new nr(n),Uye(r),Ee=Hr(Ft(e.c,(nI(),HCe))),v=u(Ft(e.c,Vhe),316),Ve=u(Ft(e.c,Uhe),429),h=u(Ft(e.c,FCe),482),Ne=u(Ft(e.c,qhe),430),e.j=Ue(ft(Ft(e.c,Eyt))),d=e.a,v.g){case 0:d=e.a;break;case 1:d=e.b;break;case 2:d=e.i;break;case 3:d=e.e;break;case 4:d=e.f;break;default:throw J(new Ln(lG+(v.f!=null?v.f:""+v.g)))}if(e.d=new gXe(d,Ve,h),Ye(e.d,(H8(),JC),Mt(Ft(e.c,kyt))),e.d.c=It(Mt(Ft(e.c,jCe))),Jj(e.c).i==0)return e.d;for(L=new rr(Jj(e.c));L.e!=L.i.gc();){for(_=u(pr(L),33),z=_.g/2,P=_.f/2,nt=new Pt(_.i+z,_.j+P);Il(e.g,nt);)Lm(nt,(b.Math.random()-.5)*Sd,(b.Math.random()-.5)*Sd);W=u(Ft(_,(bi(),WO)),142),X=new DXe(nt,new fh(nt.a-z-e.j/2-W.b,nt.b-P-e.j/2-W.d,_.g+e.j+(W.b+W.c),_.f+e.j+(W.d+W.a))),it(e.d.i,X),Si(e.g,nt,new xa(X,_))}switch(Ne.g){case 0:if(Ee==null)e.d.d=u(St(e.d.i,0),65);else for(Ce=new C(e.d.i);Ce.a1&&ks(_,le,_.c.b,_.c),F$(s)));le=Ce}return _}function jyn(e,t,n){var r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn,dr,ki,Ws,rh,af,ed;for(kr(n,"Greedy cycle 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t,n,r,s,o,h,d,v,x,_,L,P,z;if(h=!0,L=null,r=null,s=null,t=!1,z=e4t,x=null,o=null,d=0,v=Yie(e,d,OAe,NAe),v=0&&an(e.substr(d,2),"//")?(d+=2,v=Yie(e,d,KS,YS),r=e.substr(d,v-d),d=v):L!=null&&(d==e.length||(zr(d,e.length),e.charCodeAt(d)!=47))&&(h=!1,v=lbe(e,Nu(35),d),v==-1&&(v=e.length),r=e.substr(d,v-d),d=v);if(!n&&d0&&Ma(_,_.length-1)==58&&(s=_,d=v)),d=e.j){e.a=-1,e.c=1;return}if(t=Ma(e.i,e.d++),e.a=t,e.b==1){switch(t){case 92:if(r=10,e.d>=e.j)throw J(new $r(Ur((jr(),vG))));e.a=Ma(e.i,e.d++);break;case 45:(e.e&512)==512&&e.d=e.j||Ma(e.i,e.d)!=63)break;if(++e.d>=e.j)throw J(new $r(Ur((jr(),Wce))));switch(t=Ma(e.i,e.d++),t){case 58:r=13;break;case 61:r=14;break;case 33:r=15;break;case 91:r=19;break;case 62:r=18;break;case 60:if(e.d>=e.j)throw J(new $r(Ur((jr(),Wce))));if(t=Ma(e.i,e.d++),t==61)r=16;else if(t==33)r=17;else throw J(new $r(Ur((jr(),W1t))));break;case 35:for(;e.d=e.j)throw J(new $r(Ur((jr(),vG))));e.a=Ma(e.i,e.d++);break;default:r=0}e.c=r}function zyn(e){var t,n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn,dr;if(bt=u(K(e,(pt(),bs)),98),bt!=(wa(),X1)&&bt!=w2){for(q=e.b,z=q.c.length,_=new su((ql(z+2,Nae),R$(Ua(Ua(5,z+2),(z+2)/10|0)))),W=new su((ql(z+2,Nae),R$(Ua(Ua(5,z+2),(z+2)/10|0)))),it(_,new Mr),it(_,new Mr),it(W,new st),it(W,new st),nt=new st,t=0;t=Ve||!ucn(le,r))&&(r=HXe(t,_)),No(le,r),o=new cr(fr(Xo(le).a.Kc(),new V));Vr(o);)s=u(Pr(o),17),!e.a[s.p]&&(W=s.c.i,--e.e[W.p],e.e[W.p]==0&&S8(l7(z,W)));for(x=_.c.length-1;x>=0;--x)it(t.b,(xn(x,_.c.length),u(_.c[x],29)));t.a.c=Me(Yn,yt,1,0,5,1),ur(n)}function Ylt(e){var t,n,r,s,o,h,d,v,x;for(e.b=1,mi(e),t=null,e.c==0&&e.a==94?(mi(e),t=(yi(),yi(),new Hl(4)),Yc(t,0,q7),d=new Hl(4)):d=(yi(),yi(),new Hl(4)),s=!0;(x=e.c)!=1;){if(x==0&&e.a==93&&!s){t&&(bC(t,d),d=t);break}if(n=e.a,r=!1,x==10)switch(n){case 100:case 68:case 119:case 87:case 115:case 83:ly(d,m7(n)),r=!0;break;case 105:case 73:case 99:case 67:n=(ly(d,m7(n)),-1),n<0&&(r=!0);break;case 112:case 80:if(v=$4e(e,n),!v)throw J(new $r(Ur((jr(),Kce))));ly(d,v),r=!0;break;default:n=y5e(e)}else if(x==24&&!s){if(t&&(bC(t,d),d=t),o=Ylt(e),bC(d,o),e.c!=0||e.a!=93)throw J(new $r(Ur((jr(),rdt))));break}if(mi(e),!r){if(x==0){if(n==91)throw J(new $r(Ur((jr(),h8e))));if(n==93)throw J(new $r(Ur((jr(),f8e))));if(n==45&&!s&&e.a!=93)throw J(new $r(Ur((jr(),Yce))))}if(e.c!=0||e.a!=45||n==45&&s)Yc(d,n,n);else{if(mi(e),(x=e.c)==1)throw J(new $r(Ur((jr(),wG))));if(x==0&&e.a==93)Yc(d,n,n),Yc(d,45,45);else{if(x==0&&e.a==93||x==24)throw J(new $r(Ur((jr(),Yce))));if(h=e.a,x==0){if(h==91)throw J(new $r(Ur((jr(),h8e))));if(h==93)throw J(new $r(Ur((jr(),f8e))));if(h==45)throw J(new $r(Ur((jr(),Yce))))}else x==10&&(h=y5e(e));if(mi(e),n>h)throw J(new $r(Ur((jr(),adt))));Yc(d,n,h)}}}s=!1}if(e.c==1)throw J(new $r(Ur((jr(),wG))));return l4(d),gC(d),e.b=0,mi(e),d}function qyn(e){Rr(e.c,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#decimal"])),Rr(e.d,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#integer"])),Rr(e.e,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#boolean"])),Rr(e.f,Zr,ie(re(mt,1),Qe,2,6,[Ha,"EBoolean",gi,"EBoolean:Object"])),Rr(e.i,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#byte"])),Rr(e.g,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#hexBinary"])),Rr(e.j,Zr,ie(re(mt,1),Qe,2,6,[Ha,"EByte",gi,"EByte:Object"])),Rr(e.n,Zr,ie(re(mt,1),Qe,2,6,[Ha,"EChar",gi,"EChar:Object"])),Rr(e.t,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#double"])),Rr(e.u,Zr,ie(re(mt,1),Qe,2,6,[Ha,"EDouble",gi,"EDouble:Object"])),Rr(e.F,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#float"])),Rr(e.G,Zr,ie(re(mt,1),Qe,2,6,[Ha,"EFloat",gi,"EFloat:Object"])),Rr(e.I,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#int"])),Rr(e.J,Zr,ie(re(mt,1),Qe,2,6,[Ha,"EInt",gi,"EInt:Object"])),Rr(e.N,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#long"])),Rr(e.O,Zr,ie(re(mt,1),Qe,2,6,[Ha,"ELong",gi,"ELong:Object"])),Rr(e.Z,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#short"])),Rr(e.$,Zr,ie(re(mt,1),Qe,2,6,[Ha,"EShort",gi,"EShort:Object"])),Rr(e._,Zr,ie(re(mt,1),Qe,2,6,[Ha,"http://www.w3.org/2001/XMLSchema#string"]))}function Vyn(e){var t,n,r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn,dr;if(e.c.length==1)return xn(0,e.c.length),u(e.c[0],135);if(e.c.length<=0)return new E$;for(v=new C(e);v.aL&&(Rn=0,dr+=_+bt,_=0),tgn(Ve,h,Rn,dr),t=b.Math.max(t,Rn+nt.a),_=b.Math.max(_,nt.b),Rn+=nt.a+bt;for(Ne=new Mr,n=new Mr,Ut=new C(e);Ut.aqse(o))&&(L=o);for(!L&&(L=(xn(0,X.c.length),u(X.c[0],180))),W=new C(t.b);W.a=-1900?1:0,n>=4?Yr(e,ie(re(mt,1),Qe,2,6,[fht,dht])[d]):Yr(e,ie(re(mt,1),Qe,2,6,["BC","AD"])[d]);break;case 121:jcn(e,n,r);break;case 77:G2n(e,n,r);break;case 107:v=s.q.getHours(),v==0?e0(e,24,n):e0(e,v,n);break;case 83:lgn(e,n,s);break;case 69:_=r.q.getDay(),n==5?Yr(e,ie(re(mt,1),Qe,2,6,["S","M","T","W","T","F","S"])[_]):n==4?Yr(e,ie(re(mt,1),Qe,2,6,[Kae,Yae,Xae,Qae,Zae,Jae,eoe])[_]):Yr(e,ie(re(mt,1),Qe,2,6,["Sun","Mon","Tue","Wed","Thu","Fri","Sat"])[_]);break;case 97:s.q.getHours()>=12&&s.q.getHours()<24?Yr(e,ie(re(mt,1),Qe,2,6,["AM","PM"])[1]):Yr(e,ie(re(mt,1),Qe,2,6,["AM","PM"])[0]);break;case 104:L=s.q.getHours()%12,L==0?e0(e,12,n):e0(e,L,n);break;case 75:P=s.q.getHours()%12,e0(e,P,n);break;case 72:z=s.q.getHours(),e0(e,z,n);break;case 99:q=r.q.getDay(),n==5?Yr(e,ie(re(mt,1),Qe,2,6,["S","M","T","W","T","F","S"])[q]):n==4?Yr(e,ie(re(mt,1),Qe,2,6,[Kae,Yae,Xae,Qae,Zae,Jae,eoe])[q]):n==3?Yr(e,ie(re(mt,1),Qe,2,6,["Sun","Mon","Tue","Wed","Thu","Fri","Sat"])[q]):e0(e,q,1);break;case 76:W=r.q.getMonth(),n==5?Yr(e,ie(re(mt,1),Qe,2,6,["J","F","M","A","M","J","J","A","S","O","N","D"])[W]):n==4?Yr(e,ie(re(mt,1),Qe,2,6,[Rae,Fae,jae,$ae,ak,Hae,zae,Gae,qae,Vae,Uae,Wae])[W]):n==3?Yr(e,ie(re(mt,1),Qe,2,6,["Jan","Feb","Mar","Apr",ak,"Jun","Jul","Aug","Sep","Oct","Nov","Dec"])[W]):e0(e,W+1,n);break;case 81:X=r.q.getMonth()/3|0,n<4?Yr(e,ie(re(mt,1),Qe,2,6,["Q1","Q2","Q3","Q4"])[X]):Yr(e,ie(re(mt,1),Qe,2,6,["1st quarter","2nd quarter","3rd quarter","4th quarter"])[X]);break;case 100:le=r.q.getDate(),e0(e,le,n);break;case 109:x=s.q.getMinutes(),e0(e,x,n);break;case 115:h=s.q.getSeconds(),e0(e,h,n);break;case 122:n<4?Yr(e,o.c[0]):Yr(e,o.c[1]);break;case 118:Yr(e,o.b);break;case 90:n<3?Yr(e,J1n(o)):n==3?Yr(e,ndn(o)):Yr(e,rdn(o.a));break;default:return!1}return!0}function h6e(e,t,n,r){var s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn,dr,ki;if(Bct(t),v=u(Te((!t.b&&(t.b=new wn(mr,t,4,7)),t.b),0),82),_=u(Te((!t.c&&(t.c=new wn(mr,t,5,8)),t.c),0),82),d=zo(v),x=zo(_),h=(!t.a&&(t.a=new at(os,t,6,6)),t.a).i==0?null:u(Te((!t.a&&(t.a=new at(os,t,6,6)),t.a),0),202),bt=u(er(e.a,d),10),Rn=u(er(e.a,x),10),zt=null,dr=null,we(v,186)&&(nt=u(er(e.a,v),299),we(nt,11)?zt=u(nt,11):we(nt,10)&&(bt=u(nt,10),zt=u(St(bt.j,0),11))),we(_,186)&&(In=u(er(e.a,_),299),we(In,11)?dr=u(In,11):we(In,10)&&(Rn=u(In,10),dr=u(St(Rn.j,0),11))),!bt||!Rn)throw J(new CT("The source or the target of edge "+t+" could not be found. This usually happens when an edge connects a node laid out by ELK Layered to a node in another level of hierarchy laid out by either another instance of ELK Layered or another layout algorithm alltogether. The former can be solved by setting the hierarchyHandling option to INCLUDE_CHILDREN."));for(W=new Iv,Ho(W,t),Ye(W,(et(),Mi),t),Ye(W,(pt(),Fo),null),z=u(K(r,eu),21),bt==Rn&&z.Fc((mo(),cS)),zt||(Ve=(vo(),hu),Ut=null,h&&R3(u(K(bt,bs),98))&&(Ut=new Pt(h.j,h.k),qQe(Ut,nD(t)),yZe(Ut,n),Vm(x,d)&&(Ve=ul,Ni(Ut,bt.n))),zt=Nut(bt,Ut,Ve,r)),dr||(Ve=(vo(),ul),ki=null,h&&R3(u(K(Rn,bs),98))&&(ki=new Pt(h.b,h.c),qQe(ki,nD(t)),yZe(ki,n)),dr=Nut(Rn,ki,Ve,Ya(Rn))),Va(W,zt),ba(W,dr),(zt.e.c.length>1||zt.g.c.length>1||dr.e.c.length>1||dr.g.c.length>1)&&z.Fc((mo(),oS)),P=new rr((!t.n&&(t.n=new at(Jo,t,1,7)),t.n));P.e!=P.i.gc();)if(L=u(pr(P),137),!It(Mt(Ft(L,Ob)))&&L.a)switch(X=Mie(L),it(W.b,X),u(K(X,Rd),272).g){case 1:case 2:z.Fc((mo(),cE));break;case 0:z.Fc((mo(),oE)),Ye(X,Rd,(P1(),EE))}if(o=u(K(r,dS),314),le=u(K(r,Zq),315),s=o==(V6(),vO)||le==(X_(),ohe),h&&(!h.a&&(h.a=new Bs(ef,h,5)),h.a).i!=0&&s){for(Ce=iI(h),q=new Gu,Ne=ii(Ce,0);Ne.b!=Ne.d.c;)Ee=u(ri(Ne),8),ci(q,new Io(Ee));Ye(W,R9e,q)}return W}function Yyn(e){e.gb||(e.gb=!0,e.b=gc(e,0),ls(e.b,18),zi(e.b,19),e.a=gc(e,1),ls(e.a,1),zi(e.a,2),zi(e.a,3),zi(e.a,4),zi(e.a,5),e.o=gc(e,2),ls(e.o,8),ls(e.o,9),zi(e.o,10),zi(e.o,11),zi(e.o,12),zi(e.o,13),zi(e.o,14),zi(e.o,15),zi(e.o,16),zi(e.o,17),zi(e.o,18),zi(e.o,19),zi(e.o,20),zi(e.o,21),zi(e.o,22),zi(e.o,23),Bo(e.o),Bo(e.o),Bo(e.o),Bo(e.o),Bo(e.o),Bo(e.o),Bo(e.o),Bo(e.o),Bo(e.o),Bo(e.o),e.p=gc(e,3),ls(e.p,2),ls(e.p,3),ls(e.p,4),ls(e.p,5),zi(e.p,6),zi(e.p,7),Bo(e.p),Bo(e.p),e.q=gc(e,4),ls(e.q,8),e.v=gc(e,5),zi(e.v,9),Bo(e.v),Bo(e.v),Bo(e.v),e.w=gc(e,6),ls(e.w,2),ls(e.w,3),ls(e.w,4),zi(e.w,5),e.B=gc(e,7),zi(e.B,1),Bo(e.B),Bo(e.B),Bo(e.B),e.Q=gc(e,8),zi(e.Q,0),Bo(e.Q),e.R=gc(e,9),ls(e.R,1),e.S=gc(e,10),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),Bo(e.S),e.T=gc(e,11),zi(e.T,10),zi(e.T,11),zi(e.T,12),zi(e.T,13),zi(e.T,14),Bo(e.T),Bo(e.T),e.U=gc(e,12),ls(e.U,2),ls(e.U,3),zi(e.U,4),zi(e.U,5),zi(e.U,6),zi(e.U,7),Bo(e.U),e.V=gc(e,13),zi(e.V,10),e.W=gc(e,14),ls(e.W,18),ls(e.W,19),ls(e.W,20),zi(e.W,21),zi(e.W,22),zi(e.W,23),e.bb=gc(e,15),ls(e.bb,10),ls(e.bb,11),ls(e.bb,12),ls(e.bb,13),ls(e.bb,14),ls(e.bb,15),ls(e.bb,16),zi(e.bb,17),Bo(e.bb),Bo(e.bb),e.eb=gc(e,16),ls(e.eb,2),ls(e.eb,3),ls(e.eb,4),ls(e.eb,5),ls(e.eb,6),ls(e.eb,7),zi(e.eb,8),zi(e.eb,9),e.ab=gc(e,17),ls(e.ab,0),ls(e.ab,1),e.H=gc(e,18),zi(e.H,0),zi(e.H,1),zi(e.H,2),zi(e.H,3),zi(e.H,4),zi(e.H,5),Bo(e.H),e.db=gc(e,19),zi(e.db,2),e.c=di(e,20),e.d=di(e,21),e.e=di(e,22),e.f=di(e,23),e.i=di(e,24),e.g=di(e,25),e.j=di(e,26),e.k=di(e,27),e.n=di(e,28),e.r=di(e,29),e.s=di(e,30),e.t=di(e,31),e.u=di(e,32),e.fb=di(e,33),e.A=di(e,34),e.C=di(e,35),e.D=di(e,36),e.F=di(e,37),e.G=di(e,38),e.I=di(e,39),e.J=di(e,40),e.L=di(e,41),e.M=di(e,42),e.N=di(e,43),e.O=di(e,44),e.P=di(e,45),e.X=di(e,46),e.Y=di(e,47),e.Z=di(e,48),e.$=di(e,49),e._=di(e,50),e.cb=di(e,51),e.K=di(e,52))}function bi(){bi=pe;var e,t;PS=new Zi(n1t),xE=new Zi(r1t),dSe=(t0(),Yhe),Jyt=new dn(Zke,dSe),Bk=new dn(fk,null),e3t=new Zi(Uxe),pSe=(ty(),Ui(Zhe,ie(re(Jhe,1),tt,291,0,[Qhe]))),IV=new dn(rG,pSe),VO=new dn(WI,(Mn(),!1)),bSe=(wo(),f0),Mw=new dn(txe,bSe),mSe=($0(),hfe),wSe=new dn(VI,mSe),xSe=new dn(uG,!1),ESe=(F0(),FV),Q4=new dn(nG,ESe),OSe=new kv(12),Fb=new dn(uw,OSe),OV=new dn(jI,!1),TSe=new dn(fce,!1),KO=new dn(CC,!1),FSe=(wa(),w2),BS=new dn(Doe,FSe),Rk=new Zi(iG),BV=new Zi(FI),ufe=new Zi(Fz),lfe=new Zi(_C),_Se=new Gu,Z4=new dn(lxe,_Se),n3t=new dn(dxe,!1),r3t=new dn(gxe,!1),CSe=new yT,WO=new dn(bxe,CSe),PV=new dn(Xke,!1),o3t=new dn(i1t,1),new dn(s1t,!0),ct(0),new dn(a1t,ct(100)),new dn(o1t,!1),ct(0),new dn(c1t,ct(4e3)),ct(0),new dn(u1t,ct(400)),new dn(l1t,!1),new dn(h1t,!1),new dn(f1t,!0),new dn(d1t,!1),gSe=(EH(),pfe),t3t=new dn(Vxe,gSe),c3t=new dn(Fke,10),u3t=new dn(jke,10),zSe=new dn(_oe,20),l3t=new dn($ke,10),GSe=new dn(Moe,2),h3t=new dn(Hke,10),qSe=new dn(zke,0),RV=new dn(Vke,5),VSe=new dn(Gke,1),USe=new dn(qke,1),jb=new dn(py,20),f3t=new dn(Uke,10),YSe=new dn(Wke,10),Fk=new Zi(Kke),KSe=new bVe,WSe=new dn(vxe,KSe),s3t=new Zi(hce),NSe=!1,i3t=new dn(lce,NSe),ASe=new kv(5),SSe=new dn(nxe,ASe),LSe=(sy(),t=u(Qf(xo),9),new hh(t,u(wf(t,t.length),9),0)),J4=new dn(P7,LSe),BSe=(n4(),v2),PSe=new dn(sxe,BSe),ife=new Zi(axe),sfe=new Zi(oxe),afe=new Zi(cxe),rfe=new Zi(uxe),MSe=(e=u(Qf(qS),9),new hh(e,u(wf(e,e.length),9),0)),Rb=new dn(E4,MSe),ISe=rn((wl(),SE)),p2=new dn(dk,ISe),DSe=new Pt(0,0),e5=new dn(gk,DSe),NV=new dn(uce,!1),vSe=(P1(),EE),tfe=new dn(hxe,vSe),efe=new dn(jz,!1),ct(1),new dn(g1t,null),RSe=new Zi(pxe),ofe=new Zi(fxe),HSe=(ht(),uc),t5=new dn(Qke,HSe),kl=new Zi(Yke),jSe=(ol(),rn(m2)),Hy=new dn(B7,jSe),cfe=new dn(rxe,!1),$Se=new dn(ixe,!0),UO=new dn(Jke,!1),nfe=new dn(exe,!1),ySe=new dn(Coe,1),kSe=(YH(),dfe),new dn(p1t,kSe),a3t=!0}function et(){et=pe;var e,t;Mi=new Zi(K6e),O9e=new Zi("coordinateOrigin"),Ple=new Zi("processors"),I9e=new zs("compoundNode",(Mn(),!1)),kO=new zs("insideConnections",!1),R9e=new Zi("originalBendpoints"),F9e=new Zi("originalDummyNodePosition"),j9e=new Zi("originalLabelEdge"),EO=new Zi("representedLabels"),uS=new Zi("endLabels"),Ck=new Zi("endLabel.origin"),Ak=new zs("labelSide",(Ul(),QO)),H4=new zs("maxEdgeThickness",0),W1=new zs("reversed",!1),Lk=new Zi(Qht),l1=new zs("longEdgeSource",null),Yh=new zs("longEdgeTarget",null),Ay=new zs("longEdgeHasLabelDummies",!1),xO=new zs("longEdgeBeforeLabelDummy",!1),Fq=new zs("edgeConstraint",(sb(),wle)),xw=new Zi("inLayerLayoutUnit"),Lb=new zs("inLayerConstraint",(P0(),mO)),Sk=new zs("inLayerSuccessorConstraint",new st),B9e=new zs("inLayerSuccessorConstraintBetweenNonDummies",!1),cl=new Zi("portDummy"),Rq=new zs("crossingHint",ct(0)),eu=new zs("graphProperties",(t=u(Qf(_le),9),new hh(t,u(wf(t,t.length),9),0))),vc=new zs("externalPortSide",(ht(),uc)),P9e=new zs("externalPortSize",new Fa),Mle=new Zi("externalPortReplacedDummies"),jq=new Zi("externalPortReplacedDummy"),Sy=new zs("externalPortConnections",(e=u(Qf(ao),9),new hh(e,u(wf(e,e.length),9),0))),Ew=new zs(Ght,0),D9e=new Zi("barycenterAssociates"),Mk=new Zi("TopSideComments"),_k=new Zi("BottomSideComments"),Bq=new Zi("CommentConnectionPort"),Ile=new zs("inputCollect",!1),Nle=new zs("outputCollect",!1),yO=new zs("cyclic",!1),N9e=new Zi("crossHierarchyMap"),Rle=new Zi("targetOffset"),new zs("splineLabelSize",new Fa),G4=new Zi("spacings"),$q=new zs("partitionConstraint",!1),yw=new Zi("breakingPoint.info"),z9e=new Zi("splines.survivingEdge"),Mb=new Zi("splines.route.start"),q4=new Zi("splines.edgeChain"),H9e=new Zi("originalPortConstraints"),lE=new Zi("selfLoopHolder"),hE=new Zi("splines.nsPortY"),Nc=new Zi("modelOrder"),Ole=new Zi("longEdgeTargetNode"),kw=new zs(Tft,!1),z4=new zs(Tft,!1),Dle=new Zi("layerConstraints.hiddenNodes"),$9e=new Zi("layerConstraints.opposidePort"),Ble=new Zi("targetNode.modelOrder")}function f6e(){f6e=pe,J9e=(ED(),Lq),obt=new dn(nke,J9e),mbt=new dn(rke,(Mn(),!1)),sTe=(b$(),Lle),Tbt=new dn(Gz,sTe),jbt=new dn(ike,!1),$bt=new dn(ske,!0),B2t=new dn(ake,!1),dTe=(mD(),lhe),tvt=new dn(oke,dTe),ct(1),uvt=new dn(cke,ct(7)),lvt=new dn(uke,!1),ybt=new dn(lke,!1),Z9e=(db(),ble),abt=new dn(Roe,Z9e),cTe=(WH(),rhe),Fbt=new dn(GI,cTe),aTe=(mh(),TO),Mbt=new dn(hke,aTe),ct(-1),Lbt=new dn(fke,ct(-1)),ct(-1),Dbt=new dn(dke,ct(-1)),ct(-1),Ibt=new dn(Foe,ct(4)),ct(-1),Nbt=new dn(joe,ct(2)),oTe=(f4(),aV),Rbt=new dn($oe,oTe),ct(0),Bbt=new dn(Hoe,ct(0)),Sbt=new dn(zoe,ct(Ei)),Q9e=(V6(),Ek),sbt=new dn(MC,Q9e),U2t=new dn(gke,!1),J2t=new dn(Goe,.1),rbt=new dn(qoe,!1),ct(-1),tbt=new dn(pke,ct(-1)),ct(-1),nbt=new dn(bke,ct(-1)),ct(0),W2t=new dn(vke,ct(40)),X9e=(q8(),Sle),Q2t=new dn(Voe,X9e),Y9e=wO,K2t=new dn(qz,Y9e),fTe=(X_(),wS),evt=new dn(T4,fTe),Vbt=new Zi(Vz),uTe=(pD(),Dq),Hbt=new dn(Uoe,uTe),lTe=(tI(),Iq),Gbt=new dn(Woe,lTe),Kbt=new dn(Koe,.3),Xbt=new Zi(Yoe),hTe=(Zm(),sV),Qbt=new dn(Xoe,hTe),nTe=(iH(),fhe),fbt=new dn(wke,nTe),rTe=(uD(),dhe),dbt=new dn(mke,rTe),iTe=(Q8(),kS),gbt=new dn(Uz,iTe),bbt=new dn(Wz,.2),lbt=new dn(Qoe,2),svt=new dn(yke,null),ovt=new dn(kke,10),avt=new dn(xke,10),cvt=new dn(Eke,20),ct(0),nvt=new dn(Tke,ct(0)),ct(0),rvt=new dn(_ke,ct(0)),ct(0),ivt=new dn(Cke,ct(0)),R2t=new dn(Zoe,!1),V9e=(h7(),aS),j2t=new dn(Ske,V9e),q9e=(S$(),gle),F2t=new dn(Ake,q9e),xbt=new dn(Kz,!1),ct(0),kbt=new dn(Joe,ct(16)),ct(0),Ebt=new dn(ece,ct(5)),bTe=(uH(),bhe),Mvt=new dn(W0,bTe),hvt=new dn(Yz,10),gvt=new dn(Xz,1),pTe=(V$(),Aq),kvt=new dn(DC,pTe),vvt=new Zi(tce),gTe=ct(1),ct(0),mvt=new dn(nce,gTe),vTe=(nH(),phe),Nvt=new dn(Qz,vTe),Dvt=new Zi(Zz),Cvt=new dn(Jz,!0),Tvt=new dn(eG,2),Avt=new dn(rce,!0),tTe=(QH(),Mq),ubt=new dn(Lke,tTe),eTe=(ek(),iE),cbt=new dn(Mke,eTe),K9e=(R0(),f2),V2t=new dn(tG,K9e),q2t=new dn(Dke,!1),U9e=(Uv(),N4),$2t=new dn(ice,U9e),W9e=(j_(),ihe),G2t=new dn(Ike,W9e),H2t=new dn(sce,0),z2t=new dn(ace,0),Cbt=vle,_bt=vO,Obt=rV,Pbt=rV,Abt=nhe,ebt=(F0(),Wg),ibt=Ek,Z2t=Ek,Y2t=Ek,X2t=Wg,Ubt=mS,Wbt=wS,zbt=wS,qbt=wS,Ybt=che,Jbt=mS,Zbt=mS,pbt=($0(),jk),vbt=jk,wbt=kS,hbt=YO,fvt=wE,dvt=Fy,pvt=wE,bvt=Fy,xvt=wE,Evt=Fy,wvt=ple,yvt=Aq,Pvt=wE,Bvt=Fy,Ivt=wE,Ovt=Fy,Svt=Fy,_vt=Fy,Lvt=Fy}function po(){po=pe,MEe=new Cs("DIRECTION_PREPROCESSOR",0),SEe=new Cs("COMMENT_PREPROCESSOR",1),tS=new Cs("EDGE_AND_LAYER_CONSTRAINT_EDGE_REVERSER",2),ele=new Cs("INTERACTIVE_EXTERNAL_PORT_POSITIONER",3),YEe=new Cs("PARTITION_PREPROCESSOR",4),uq=new Cs("LABEL_DUMMY_INSERTER",5),mq=new Cs("SELF_LOOP_PREPROCESSOR",6),eE=new Cs("LAYER_CONSTRAINT_PREPROCESSOR",7),WEe=new Cs("PARTITION_MIDPROCESSOR",8),FEe=new Cs("HIGH_DEGREE_NODE_LAYER_PROCESSOR",9),VEe=new Cs("NODE_PROMOTION",10),J7=new Cs("LAYER_CONSTRAINT_POSTPROCESSOR",11),KEe=new Cs("PARTITION_POSTPROCESSOR",12),PEe=new Cs("HIERARCHICAL_PORT_CONSTRAINT_PROCESSOR",13),XEe=new Cs("SEMI_INTERACTIVE_CROSSMIN_PROCESSOR",14),kEe=new Cs("BREAKING_POINT_INSERTER",15),dq=new Cs("LONG_EDGE_SPLITTER",16),tle=new Cs("PORT_SIDE_PROCESSOR",17),oq=new Cs("INVERTED_PORT_PROCESSOR",18),bq=new Cs("PORT_LIST_SORTER",19),ZEe=new Cs("SORT_BY_INPUT_ORDER_OF_MODEL",20),pq=new Cs("NORTH_SOUTH_PORT_PREPROCESSOR",21),xEe=new Cs("BREAKING_POINT_PROCESSOR",22),UEe=new Cs(bft,23),JEe=new Cs(vft,24),vq=new Cs("SELF_LOOP_PORT_RESTORER",25),QEe=new Cs("SINGLE_EDGE_GRAPH_WRAPPER",26),cq=new Cs("IN_LAYER_CONSTRAINT_PROCESSOR",27),IEe=new Cs("END_NODE_PORT_LABEL_MANAGEMENT_PROCESSOR",28),GEe=new Cs("LABEL_AND_NODE_SIZE_PROCESSOR",29),zEe=new Cs("INNERMOST_NODE_MARGIN_CALCULATOR",30),yq=new Cs("SELF_LOOP_ROUTER",31),_Ee=new Cs("COMMENT_NODE_MARGIN_CALCULATOR",32),aq=new Cs("END_LABEL_PREPROCESSOR",33),hq=new Cs("LABEL_DUMMY_SWITCHER",34),TEe=new Cs("CENTER_LABEL_MANAGEMENT_PROCESSOR",35),Z7=new Cs("LABEL_SIDE_SELECTOR",36),$Ee=new Cs("HYPEREDGE_DUMMY_MERGER",37),BEe=new Cs("HIERARCHICAL_PORT_DUMMY_SIZE_PROCESSOR",38),qEe=new Cs("LAYER_SIZE_AND_GRAPH_HEIGHT_CALCULATOR",39),nS=new Cs("HIERARCHICAL_PORT_POSITION_PROCESSOR",40),AEe=new Cs("CONSTRAINTS_POSTPROCESSOR",41),CEe=new Cs("COMMENT_POSTPROCESSOR",42),HEe=new Cs("HYPERNODE_PROCESSOR",43),REe=new Cs("HIERARCHICAL_PORT_ORTHOGONAL_EDGE_ROUTER",44),fq=new Cs("LONG_EDGE_JOINER",45),wq=new Cs("SELF_LOOP_POSTPROCESSOR",46),EEe=new Cs("BREAKING_POINT_REMOVER",47),gq=new Cs("NORTH_SOUTH_PORT_POSTPROCESSOR",48),jEe=new Cs("HORIZONTAL_COMPACTOR",49),lq=new Cs("LABEL_DUMMY_REMOVER",50),OEe=new Cs("FINAL_SPLINE_BENDPOINTS_CALCULATOR",51),DEe=new Cs("END_LABEL_SORTER",52),pO=new Cs("REVERSED_EDGE_RESTORER",53),sq=new Cs("END_LABEL_POSTPROCESSOR",54),NEe=new Cs("HIERARCHICAL_NODE_RESIZER",55),LEe=new Cs("DIRECTION_POSTPROCESSOR",56)}function Xyn(e,t,n){var r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce,Ee,Ne,Ve,nt,bt,zt,Ut,In,Rn,dr,ki,Ws,rh,af,ed,aU,pN,rA,bN,IE,Dfe,Q4t,Ife,Jg,Bw,OE,vN,wN,Vk,Ofe,iA,Z4t,gLe,Rw,sA,Nfe,Uk,aA,Qy,oA,Pfe,J4t;for(gLe=0,ki=t,af=0,pN=ki.length;af0&&(e.a[Jg.p]=gLe++)}for(aA=0,Ws=n,ed=0,rA=Ws.length;ed0;){for(Jg=(Qn(wN.b>0),u(wN.a.Xb(wN.c=--wN.b),11)),vN=0,d=new C(Jg.e);d.a0&&(Jg.j==(ht(),An)?(e.a[Jg.p]=aA,++aA):(e.a[Jg.p]=aA+bN+Dfe,++Dfe))}aA+=Dfe}for(OE=new Mr,q=new C0,dr=t,rh=0,aU=dr.length;rhx.b&&(x.b=Vk)):Jg.i.c==Z4t&&(Vkx.c&&(x.c=Vk));for(L8(W,0,W.length,null),Uk=Me(Lr,Jr,25,W.length,15,1),r=Me(Lr,Jr,25,aA+1,15,1),le=0;le0;)bt%2>0&&(s+=Pfe[bt+1]),bt=(bt-1)/2|0,++Pfe[bt];for(Ut=Me(_wt,yt,362,W.length*2,0,1),Ne=0;Ne'?":an(W1t,e)?"'(?<' or '(? toIndex: ",_6e=", toIndex: ",C6e="Index: ",S6e=", Size: ",M7="org.eclipse.elk.alg.common",ji={62:1},_ht="org.eclipse.elk.alg.common.compaction",Cht="Scanline/EventHandler",o0="org.eclipse.elk.alg.common.compaction.oned",Sht="CNode belongs to another CGroup.",Aht="ISpacingsHandler/1",doe="The ",goe=" instance has been finished already.",Lht="The direction ",Mht=" is not supported by the CGraph instance.",Dht="OneDimensionalCompactor",Iht="OneDimensionalCompactor/lambda$0$Type",Oht="Quadruplet",Nht="ScanlineConstraintCalculator",Pht="ScanlineConstraintCalculator/ConstraintsScanlineHandler",Bht="ScanlineConstraintCalculator/ConstraintsScanlineHandler/lambda$0$Type",Rht="ScanlineConstraintCalculator/Timestamp",Fht="ScanlineConstraintCalculator/lambda$0$Type",_d={169:1,45:1},poe="org.eclipse.elk.alg.common.compaction.options",cc="org.eclipse.elk.core.data",A6e="org.eclipse.elk.polyomino.traversalStrategy",L6e="org.eclipse.elk.polyomino.lowLevelSort",M6e="org.eclipse.elk.polyomino.highLevelSort",D6e="org.eclipse.elk.polyomino.fill",zh={130:1},boe="polyomino",xC="org.eclipse.elk.alg.common.networksimplex",c0={177:1,3:1,4:1},jht="org.eclipse.elk.alg.common.nodespacing",wb="org.eclipse.elk.alg.common.nodespacing.cellsystem",D7="CENTER",$ht={212:1,326:1},I6e={3:1,4:1,5:1,595:1},uk="LEFT",lk="RIGHT",O6e="Vertical alignment cannot be 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Requested point (",Eoe=") is out of bounds.",Pz=" Given center based coordinates were (",BI="org.eclipse.elk.graph.properties",qht="IPropertyHolder",B6e={3:1,94:1,134:1},hk="org.eclipse.elk.alg.common.spore",Vht="org.eclipse.elk.alg.common.utils",mb={209:1},k4="org.eclipse.elk.core",Uht="Connected Components Compaction",Wht="org.eclipse.elk.alg.disco",Bz="org.eclipse.elk.alg.disco.graph",Toe="org.eclipse.elk.alg.disco.options",R6e="CompactionStrategy",F6e="org.eclipse.elk.disco.componentCompaction.strategy",j6e="org.eclipse.elk.disco.componentCompaction.componentLayoutAlgorithm",$6e="org.eclipse.elk.disco.debug.discoGraph",H6e="org.eclipse.elk.disco.debug.discoPolys",Kht="componentCompaction",yb="org.eclipse.elk.disco",_oe="org.eclipse.elk.spacing.componentComponent",Coe="org.eclipse.elk.edge.thickness",fk="org.eclipse.elk.aspectRatio",uw="org.eclipse.elk.padding",x4="org.eclipse.elk.alg.disco.transform",Soe=1.5707963267948966,O7=17976931348623157e292,gy={3:1,4:1,5:1,192:1},z6e={3:1,6:1,4:1,5:1,106:1,120:1},G6e="org.eclipse.elk.alg.force",q6e="ComponentsProcessor",Yht="ComponentsProcessor/1",RI="org.eclipse.elk.alg.force.graph",Xht="Component Layout",V6e="org.eclipse.elk.alg.force.model",Rz="org.eclipse.elk.force.model",U6e="org.eclipse.elk.force.iterations",W6e="org.eclipse.elk.force.repulsivePower",Aoe="org.eclipse.elk.force.temperature",Sd=.001,Loe="org.eclipse.elk.force.repulsion",TC="org.eclipse.elk.alg.force.options",N7=1.600000023841858,Yl="org.eclipse.elk.force",FI="org.eclipse.elk.priority",py="org.eclipse.elk.spacing.nodeNode",Moe="org.eclipse.elk.spacing.edgeLabel",Fz="org.eclipse.elk.randomSeed",_C="org.eclipse.elk.separateConnectedComponents",jI="org.eclipse.elk.interactive",Doe="org.eclipse.elk.portConstraints",jz="org.eclipse.elk.edgeLabels.inline",CC="org.eclipse.elk.omitNodeMicroLayout",dk="org.eclipse.elk.nodeSize.options",E4="org.eclipse.elk.nodeSize.constraints",P7="org.eclipse.elk.nodeLabels.placement",B7="org.eclipse.elk.portLabels.placement",K6e="origin",Qht="random",Zht="boundingBox.upLeft",Jht="boundingBox.lowRight",Y6e="org.eclipse.elk.stress.fixed",X6e="org.eclipse.elk.stress.desiredEdgeLength",Q6e="org.eclipse.elk.stress.dimension",Z6e="org.eclipse.elk.stress.epsilon",J6e="org.eclipse.elk.stress.iterationLimit",t2="org.eclipse.elk.stress",eft="ELK Stress",gk="org.eclipse.elk.nodeSize.minimum",$z="org.eclipse.elk.alg.force.stress",tft="Layered layout",pk="org.eclipse.elk.alg.layered",$I="org.eclipse.elk.alg.layered.compaction.components",SC="org.eclipse.elk.alg.layered.compaction.oned",Hz="org.eclipse.elk.alg.layered.compaction.oned.algs",kb="org.eclipse.elk.alg.layered.compaction.recthull",Ad="org.eclipse.elk.alg.layered.components",U0="NONE",Dc={3:1,6:1,4:1,9:1,5:1,122:1},nft={3:1,6:1,4:1,5:1,141:1,106:1,120:1},zz="org.eclipse.elk.alg.layered.compound",ps={51:1},uu="org.eclipse.elk.alg.layered.graph",Ioe=" -> ",rft="Not supported by LGraph",eke="Port side is undefined",Ooe={3:1,6:1,4:1,5:1,474:1,141:1,106:1,120:1},Bg={3:1,6:1,4:1,5:1,141:1,193:1,203:1,106:1,120:1},ift={3:1,6:1,4:1,5:1,141:1,1943:1,203:1,106:1,120:1},sft=`([{"' \r +`,aft=`)]}"' \r +`,oft="The given string contains parts that cannot be parsed as numbers.",HI="org.eclipse.elk.core.math",cft={3:1,4:1,142:1,207:1,414:1},uft={3:1,4:1,116:1,207:1,414:1},qn="org.eclipse.elk.layered",Rg="org.eclipse.elk.alg.layered.graph.transform",lft="ElkGraphImporter",hft="ElkGraphImporter/lambda$0$Type",fft="ElkGraphImporter/lambda$1$Type",dft="ElkGraphImporter/lambda$2$Type",gft="ElkGraphImporter/lambda$4$Type",pft="Node margin calculation",Pn="org.eclipse.elk.alg.layered.intermediate",bft="ONE_SIDED_GREEDY_SWITCH",vft="TWO_SIDED_GREEDY_SWITCH",Noe="No implementation is available for the layout processor ",tke="IntermediateProcessorStrategy",Poe="Node '",wft="FIRST_SEPARATE",mft="LAST_SEPARATE",yft="Odd port side processing",Is="org.eclipse.elk.alg.layered.intermediate.compaction",AC="org.eclipse.elk.alg.layered.intermediate.greedyswitch",u0="org.eclipse.elk.alg.layered.p3order.counting",zI={225:1},bk="org.eclipse.elk.alg.layered.intermediate.loops",Xl="org.eclipse.elk.alg.layered.intermediate.loops.ordering",n2="org.eclipse.elk.alg.layered.intermediate.loops.routing",LC="org.eclipse.elk.alg.layered.intermediate.preserveorder",Ld="org.eclipse.elk.alg.layered.intermediate.wrapping",Ic="org.eclipse.elk.alg.layered.options",Boe="INTERACTIVE",kft="DEPTH_FIRST",xft="EDGE_LENGTH",Eft="SELF_LOOPS",Tft="firstTryWithInitialOrder",nke="org.eclipse.elk.layered.directionCongruency",rke="org.eclipse.elk.layered.feedbackEdges",Gz="org.eclipse.elk.layered.interactiveReferencePoint",ike="org.eclipse.elk.layered.mergeEdges",ske="org.eclipse.elk.layered.mergeHierarchyEdges",ake="org.eclipse.elk.layered.allowNonFlowPortsToSwitchSides",oke="org.eclipse.elk.layered.portSortingStrategy",cke="org.eclipse.elk.layered.thoroughness",uke="org.eclipse.elk.layered.unnecessaryBendpoints",lke="org.eclipse.elk.layered.generatePositionAndLayerIds",Roe="org.eclipse.elk.layered.cycleBreaking.strategy",GI="org.eclipse.elk.layered.layering.strategy",hke="org.eclipse.elk.layered.layering.layerConstraint",fke="org.eclipse.elk.layered.layering.layerChoiceConstraint",dke="org.eclipse.elk.layered.layering.layerId",Foe="org.eclipse.elk.layered.layering.minWidth.upperBoundOnWidth",joe="org.eclipse.elk.layered.layering.minWidth.upperLayerEstimationScalingFactor",$oe="org.eclipse.elk.layered.layering.nodePromotion.strategy",Hoe="org.eclipse.elk.layered.layering.nodePromotion.maxIterations",zoe="org.eclipse.elk.layered.layering.coffmanGraham.layerBound",MC="org.eclipse.elk.layered.crossingMinimization.strategy",gke="org.eclipse.elk.layered.crossingMinimization.forceNodeModelOrder",Goe="org.eclipse.elk.layered.crossingMinimization.hierarchicalSweepiness",qoe="org.eclipse.elk.layered.crossingMinimization.semiInteractive",pke="org.eclipse.elk.layered.crossingMinimization.positionChoiceConstraint",bke="org.eclipse.elk.layered.crossingMinimization.positionId",vke="org.eclipse.elk.layered.crossingMinimization.greedySwitch.activationThreshold",Voe="org.eclipse.elk.layered.crossingMinimization.greedySwitch.type",qz="org.eclipse.elk.layered.crossingMinimization.greedySwitchHierarchical.type",T4="org.eclipse.elk.layered.nodePlacement.strategy",Vz="org.eclipse.elk.layered.nodePlacement.favorStraightEdges",Uoe="org.eclipse.elk.layered.nodePlacement.bk.edgeStraightening",Woe="org.eclipse.elk.layered.nodePlacement.bk.fixedAlignment",Koe="org.eclipse.elk.layered.nodePlacement.linearSegments.deflectionDampening",Yoe="org.eclipse.elk.layered.nodePlacement.networkSimplex.nodeFlexibility",Xoe="org.eclipse.elk.layered.nodePlacement.networkSimplex.nodeFlexibility.default",wke="org.eclipse.elk.layered.edgeRouting.selfLoopDistribution",mke="org.eclipse.elk.layered.edgeRouting.selfLoopOrdering",Uz="org.eclipse.elk.layered.edgeRouting.splines.mode",Wz="org.eclipse.elk.layered.edgeRouting.splines.sloppy.layerSpacingFactor",Qoe="org.eclipse.elk.layered.edgeRouting.polyline.slopedEdgeZoneWidth",yke="org.eclipse.elk.layered.spacing.baseValue",kke="org.eclipse.elk.layered.spacing.edgeNodeBetweenLayers",xke="org.eclipse.elk.layered.spacing.edgeEdgeBetweenLayers",Eke="org.eclipse.elk.layered.spacing.nodeNodeBetweenLayers",Tke="org.eclipse.elk.layered.priority.direction",_ke="org.eclipse.elk.layered.priority.shortness",Cke="org.eclipse.elk.layered.priority.straightness",Zoe="org.eclipse.elk.layered.compaction.connectedComponents",Ske="org.eclipse.elk.layered.compaction.postCompaction.strategy",Ake="org.eclipse.elk.layered.compaction.postCompaction.constraints",Kz="org.eclipse.elk.layered.highDegreeNodes.treatment",Joe="org.eclipse.elk.layered.highDegreeNodes.threshold",ece="org.eclipse.elk.layered.highDegreeNodes.treeHeight",W0="org.eclipse.elk.layered.wrapping.strategy",Yz="org.eclipse.elk.layered.wrapping.additionalEdgeSpacing",Xz="org.eclipse.elk.layered.wrapping.correctionFactor",DC="org.eclipse.elk.layered.wrapping.cutting.strategy",tce="org.eclipse.elk.layered.wrapping.cutting.cuts",nce="org.eclipse.elk.layered.wrapping.cutting.msd.freedom",Qz="org.eclipse.elk.layered.wrapping.validify.strategy",Zz="org.eclipse.elk.layered.wrapping.validify.forbiddenIndices",Jz="org.eclipse.elk.layered.wrapping.multiEdge.improveCuts",eG="org.eclipse.elk.layered.wrapping.multiEdge.distancePenalty",rce="org.eclipse.elk.layered.wrapping.multiEdge.improveWrappedEdges",Lke="org.eclipse.elk.layered.edgeLabels.sideSelection",Mke="org.eclipse.elk.layered.edgeLabels.centerLabelPlacementStrategy",tG="org.eclipse.elk.layered.considerModelOrder.strategy",Dke="org.eclipse.elk.layered.considerModelOrder.noModelOrder",ice="org.eclipse.elk.layered.considerModelOrder.components",Ike="org.eclipse.elk.layered.considerModelOrder.longEdgeStrategy",sce="org.eclipse.elk.layered.considerModelOrder.crossingCounterNodeInfluence",ace="org.eclipse.elk.layered.considerModelOrder.crossingCounterPortInfluence",oce="layering",_ft="layering.minWidth",Cft="layering.nodePromotion",qI="crossingMinimization",nG="org.eclipse.elk.hierarchyHandling",Sft="crossingMinimization.greedySwitch",Aft="nodePlacement",Lft="nodePlacement.bk",Mft="edgeRouting",VI="org.eclipse.elk.edgeRouting",G1="spacing",Oke="priority",Nke="compaction",Dft="compaction.postCompaction",Ift="Specifies whether and how post-process compaction is applied.",Pke="highDegreeNodes",Bke="wrapping",Oft="wrapping.cutting",Nft="wrapping.validify",Rke="wrapping.multiEdge",cce="edgeLabels",UI="considerModelOrder",Fke="org.eclipse.elk.spacing.commentComment",jke="org.eclipse.elk.spacing.commentNode",$ke="org.eclipse.elk.spacing.edgeEdge",Hke="org.eclipse.elk.spacing.edgeNode",zke="org.eclipse.elk.spacing.labelLabel",Gke="org.eclipse.elk.spacing.labelPortHorizontal",qke="org.eclipse.elk.spacing.labelPortVertical",Vke="org.eclipse.elk.spacing.labelNode",Uke="org.eclipse.elk.spacing.nodeSelfLoop",Wke="org.eclipse.elk.spacing.portPort",Kke="org.eclipse.elk.spacing.individual",Yke="org.eclipse.elk.port.borderOffset",Xke="org.eclipse.elk.noLayout",Qke="org.eclipse.elk.port.side",WI="org.eclipse.elk.debugMode",Zke="org.eclipse.elk.alignment",Jke="org.eclipse.elk.insideSelfLoops.activate",exe="org.eclipse.elk.insideSelfLoops.yo",uce="org.eclipse.elk.nodeSize.fixedGraphSize",txe="org.eclipse.elk.direction",nxe="org.eclipse.elk.nodeLabels.padding",rxe="org.eclipse.elk.portLabels.nextToPortIfPossible",ixe="org.eclipse.elk.portLabels.treatAsGroup",sxe="org.eclipse.elk.portAlignment.default",axe="org.eclipse.elk.portAlignment.north",oxe="org.eclipse.elk.portAlignment.south",cxe="org.eclipse.elk.portAlignment.west",uxe="org.eclipse.elk.portAlignment.east",rG="org.eclipse.elk.contentAlignment",lxe="org.eclipse.elk.junctionPoints",hxe="org.eclipse.elk.edgeLabels.placement",fxe="org.eclipse.elk.port.index",dxe="org.eclipse.elk.commentBox",gxe="org.eclipse.elk.hypernode",pxe="org.eclipse.elk.port.anchor",lce="org.eclipse.elk.partitioning.activate",hce="org.eclipse.elk.partitioning.partition",iG="org.eclipse.elk.position",bxe="org.eclipse.elk.margins",vxe="org.eclipse.elk.spacing.portsSurrounding",fce="org.eclipse.elk.interactiveLayout",Oc="org.eclipse.elk.core.util",wxe={3:1,4:1,5:1,593:1},Pft="NETWORK_SIMPLEX",Qc={123:1,51:1},sG="org.eclipse.elk.alg.layered.p1cycles",by="org.eclipse.elk.alg.layered.p2layers",mxe={402:1,225:1},Bft={832:1,3:1,4:1},Qu="org.eclipse.elk.alg.layered.p3order",ko="org.eclipse.elk.alg.layered.p4nodes",Rft={3:1,4:1,5:1,840:1},Md=1e-5,r2="org.eclipse.elk.alg.layered.p4nodes.bk",dce="org.eclipse.elk.alg.layered.p5edges",o1="org.eclipse.elk.alg.layered.p5edges.orthogonal",gce="org.eclipse.elk.alg.layered.p5edges.orthogonal.direction",pce=1e-6,vy="org.eclipse.elk.alg.layered.p5edges.splines",bce=.09999999999999998,aG=1e-8,Fft=4.71238898038469,jft=3.141592653589793,IC="org.eclipse.elk.alg.mrtree",OC="org.eclipse.elk.alg.mrtree.graph",vk="org.eclipse.elk.alg.mrtree.intermediate",$ft="Set neighbors in level",Hft="DESCENDANTS",yxe="org.eclipse.elk.mrtree.weighting",kxe="org.eclipse.elk.mrtree.searchOrder",oG="org.eclipse.elk.alg.mrtree.options",Fg="org.eclipse.elk.mrtree",zft="org.eclipse.elk.tree",xxe="org.eclipse.elk.alg.radial",_4=6.283185307179586,Exe=5e-324,Gft="org.eclipse.elk.alg.radial.intermediate",vce="org.eclipse.elk.alg.radial.intermediate.compaction",qft={3:1,4:1,5:1,106:1},Txe="org.eclipse.elk.alg.radial.intermediate.optimization",wce="No implementation is available for the layout option ",NC="org.eclipse.elk.alg.radial.options",_xe="org.eclipse.elk.radial.orderId",Cxe="org.eclipse.elk.radial.radius",mce="org.eclipse.elk.radial.compactor",yce="org.eclipse.elk.radial.compactionStepSize",Sxe="org.eclipse.elk.radial.sorter",Axe="org.eclipse.elk.radial.wedgeCriteria",Lxe="org.eclipse.elk.radial.optimizationCriteria",Dd="org.eclipse.elk.radial",Vft="org.eclipse.elk.alg.radial.p1position.wedge",Mxe="org.eclipse.elk.alg.radial.sorting",Uft=5.497787143782138,Wft=3.9269908169872414,Kft=2.356194490192345,Yft="org.eclipse.elk.alg.rectpacking",cG="org.eclipse.elk.alg.rectpacking.firstiteration",kce="org.eclipse.elk.alg.rectpacking.options",Dxe="org.eclipse.elk.rectpacking.optimizationGoal",Ixe="org.eclipse.elk.rectpacking.lastPlaceShift",Oxe="org.eclipse.elk.rectpacking.currentPosition",Nxe="org.eclipse.elk.rectpacking.desiredPosition",Pxe="org.eclipse.elk.rectpacking.onlyFirstIteration",Bxe="org.eclipse.elk.rectpacking.rowCompaction",xce="org.eclipse.elk.rectpacking.expandToAspectRatio",Rxe="org.eclipse.elk.rectpacking.targetWidth",uG="org.eclipse.elk.expandNodes",Gh="org.eclipse.elk.rectpacking",KI="org.eclipse.elk.alg.rectpacking.util",lG="No implementation available for ",wy="org.eclipse.elk.alg.spore",my="org.eclipse.elk.alg.spore.options",lw="org.eclipse.elk.sporeCompaction",Ece="org.eclipse.elk.underlyingLayoutAlgorithm",Fxe="org.eclipse.elk.processingOrder.treeConstruction",jxe="org.eclipse.elk.processingOrder.spanningTreeCostFunction",Tce="org.eclipse.elk.processingOrder.preferredRoot",_ce="org.eclipse.elk.processingOrder.rootSelection",Cce="org.eclipse.elk.structure.structureExtractionStrategy",$xe="org.eclipse.elk.compaction.compactionStrategy",Hxe="org.eclipse.elk.compaction.orthogonal",zxe="org.eclipse.elk.overlapRemoval.maxIterations",Gxe="org.eclipse.elk.overlapRemoval.runScanline",Sce="processingOrder",Xft="overlapRemoval",R7="org.eclipse.elk.sporeOverlap",Qft="org.eclipse.elk.alg.spore.p1structure",Ace="org.eclipse.elk.alg.spore.p2processingorder",Lce="org.eclipse.elk.alg.spore.p3execution",Zft="Invalid index: ",F7="org.eclipse.elk.core.alg",C4={331:1},yy={288:1},Jft="Make sure its type is registered with the ",qxe=" utility class.",j7="true",Mce="false",e1t="Couldn't clone property '",hw=.05,qh="org.eclipse.elk.core.options",t1t=1.2999999523162842,fw="org.eclipse.elk.box",Vxe="org.eclipse.elk.box.packingMode",n1t="org.eclipse.elk.algorithm",r1t="org.eclipse.elk.resolvedAlgorithm",Uxe="org.eclipse.elk.bendPoints",t3n="org.eclipse.elk.labelManager",i1t="org.eclipse.elk.scaleFactor",s1t="org.eclipse.elk.animate",a1t="org.eclipse.elk.animTimeFactor",o1t="org.eclipse.elk.layoutAncestors",c1t="org.eclipse.elk.maxAnimTime",u1t="org.eclipse.elk.minAnimTime",l1t="org.eclipse.elk.progressBar",h1t="org.eclipse.elk.validateGraph",f1t="org.eclipse.elk.validateOptions",d1t="org.eclipse.elk.zoomToFit",n3n="org.eclipse.elk.font.name",g1t="org.eclipse.elk.font.size",p1t="org.eclipse.elk.edge.type",b1t="partitioning",v1t="nodeLabels",hG="portAlignment",Dce="nodeSize",Ice="port",Wxe="portLabels",w1t="insideSelfLoops",PC="org.eclipse.elk.fixed",fG="org.eclipse.elk.random",m1t="port must have a parent node to calculate the port side",y1t="The edge needs to have exactly one edge section. 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size=",Vce="sourceIndex=",Od={3:1,4:1,20:1,28:1,52:1,14:1,15:1,54:1,67:1,63:1,58:1},Uce={3:1,4:1,20:1,28:1,52:1,14:1,47:1,15:1,54:1,67:1,63:1,58:1,588:1},bG="logging",q1t="measureExecutionTime",V1t="parser.parse.1",U1t="parser.parse.2",vG="parser.next.1",Wce="parser.next.2",W1t="parser.next.3",K1t="parser.next.4",Tb="parser.factor.1",c8e="parser.factor.2",Y1t="parser.factor.3",X1t="parser.factor.4",Q1t="parser.factor.5",Z1t="parser.factor.6",J1t="parser.atom.1",edt="parser.atom.2",tdt="parser.atom.3",u8e="parser.atom.4",Kce="parser.atom.5",l8e="parser.cc.1",wG="parser.cc.2",ndt="parser.cc.3",rdt="parser.cc.5",h8e="parser.cc.6",f8e="parser.cc.7",Yce="parser.cc.8",idt="parser.ope.1",sdt="parser.ope.2",adt="parser.ope.3",jg="parser.descape.1",odt="parser.descape.2",cdt="parser.descape.3",udt="parser.descape.4",ldt="parser.descape.5",xh="parser.process.1",hdt="parser.quantifier.1",fdt="parser.quantifier.2",ddt="parser.quantifier.3",gdt="parser.quantifier.4",d8e="parser.quantifier.5",pdt="org.eclipse.emf.common.notify",g8e={415:1,672:1},bdt={3:1,4:1,20:1,28:1,52:1,14:1,15:1,67:1,58:1},XI={366:1,143:1},$C="index=",Xce={3:1,4:1,5:1,126:1},vdt={3:1,4:1,20:1,28:1,52:1,14:1,15:1,54:1,67:1,58:1},p8e={3:1,6:1,4:1,5:1,192:1},wdt={3:1,4:1,5:1,165:1,367:1},mdt=";/?:@&=+$,",ydt="invalid authority: ",kdt="EAnnotation",xdt="ETypedElement",Edt="EStructuralFeature",Tdt="EAttribute",_dt="EClassifier",Cdt="EEnumLiteral",Sdt="EGenericType",Adt="EOperation",Ldt="EParameter",Mdt="EReference",Ddt="ETypeParameter",Wi="org.eclipse.emf.ecore.util",Qce={76:1},b8e={3:1,20:1,14:1,15:1,58:1,589:1,76:1,69:1,95:1},Idt="org.eclipse.emf.ecore.util.FeatureMap$Entry",Zu=8192,ky=2048,HC="byte",mG="char",zC="double",GC="float",qC="int",VC="long",UC="short",Odt="java.lang.Object",L4={3:1,4:1,5:1,247:1},v8e={3:1,4:1,5:1,673:1},Ndt={3:1,4:1,20:1,28:1,52:1,14:1,15:1,54:1,67:1,63:1,58:1,69:1},Zo={3:1,4:1,20:1,28:1,52:1,14:1,15:1,54:1,67:1,63:1,58:1,76:1,69:1,95:1},QI="mixed",Zr="http:///org/eclipse/emf/ecore/util/ExtendedMetaData",Vh="kind",Pdt={3:1,4:1,5:1,674:1},w8e={3:1,4:1,20:1,28:1,52:1,14:1,15:1,67:1,58:1,76:1,69:1,95:1},yG={20:1,28:1,52:1,14:1,15:1,58:1,69:1},kG={47:1,125:1,279:1},xG={72:1,332:1},EG="The value of type '",TG="' must be of type '",M4=1316,Uh="http://www.eclipse.org/emf/2002/Ecore",_G=-32768,gw="constraints",Ha="baseType",Bdt="getEStructuralFeature",Rdt="getFeatureID",WC="feature",Fdt="getOperationID",m8e="operation",jdt="defaultValue",$dt="eTypeParameters",Hdt="isInstance",zdt="getEEnumLiteral",Gdt="eContainingClass",li={55:1},qdt={3:1,4:1,5:1,119:1},Vdt="org.eclipse.emf.ecore.resource",Udt={92:1,90:1,591:1,1935:1},Zce="org.eclipse.emf.ecore.resource.impl",y8e="unspecified",ZI="simple",CG="attribute",Wdt="attributeWildcard",SG="element",Jce="elementWildcard",c1="collapse",eue="itemType",AG="namespace",JI="##targetNamespace",Wh="whiteSpace",k8e="wildcards",_b="http://www.eclipse.org/emf/2003/XMLType",tue="##any",G7="uninitialized",eO="The multiplicity constraint is 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other."),J9e),(Ng(),vs)),g9e),rn((i1(),Fn))))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,rke),""),"Feedback Edges"),"Whether feedback edges should be highlighted by routing around the nodes."),(Mn(),!1)),za),Us),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Gz),""),"Interactive Reference Point"),"Determines which point of a node is considered by interactive layout phases."),sTe),vs),M9e),rn(Fn)))),va(t,Gz,Roe,Cbt),va(t,Gz,MC,_bt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,ike),""),"Merge Edges"),"Edges that have no ports are merged so they touch the connected nodes at the same points. When this option is disabled, one port is created for each edge directly connected to a node. When it is enabled, all such incoming edges share an input port, and all outgoing edges share an output port."),!1),za),Us),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,ske),""),"Merge Hierarchy-Crossing Edges"),"If hierarchical layout is active, hierarchy-crossing edges use as few hierarchical ports as possible. They are broken by the algorithm, with hierarchical ports inserted as required. Usually, one such port is created for each edge at each hierarchy crossing point. With this option set to true, we try to create as few hierarchical ports as possible in the process. In particular, all edges that form a hyperedge can share a port."),!0),za),Us),rn(Fn)))),en(t,new Vt(sUt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,ake),""),"Allow Non-Flow Ports To Switch Sides"),"Specifies whether non-flow ports may switch sides if their node's port constraints are either FIXED_SIDE or FIXED_ORDER. A non-flow port is a port on a side that is not part of the currently configured layout flow. For instance, given a left-to-right layout direction, north and south ports would be considered non-flow ports. Further note that the underlying criterium whether to switch sides or not solely relies on the minimization of edge crossings. Hence, edge length and other aesthetics criteria are not addressed."),!1),za),Us),rn(Bb)),ie(re(mt,1),Qe,2,6,["org.eclipse.elk.layered.northOrSouthPort"])))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,oke),""),"Port Sorting Strategy"),"Only relevant for nodes with FIXED_SIDE port constraints. Determines the way a node's ports are distributed on the sides of a node if their order is not prescribed. The option is set on parent nodes."),dTe),vs),k_e),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,cke),""),"Thoroughness"),"How much effort should be spent to produce a nice layout."),ct(7)),Cc),Za),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,uke),""),"Add Unnecessary Bendpoints"),"Adds bend points even if an edge does not change direction. If true, each long edge dummy will contribute a bend point to its edges and hierarchy-crossing edges will always get a bend point where they cross hierarchy boundaries. By default, bend points are only added where an edge changes direction."),!1),za),Us),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,lke),""),"Generate Position and Layer IDs"),"If enabled position id and layer id are generated, which are usually only used internally when setting the interactiveLayout option. This option should be specified on the root node."),!1),za),Us),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Roe),"cycleBreaking"),"Cycle Breaking Strategy"),"Strategy for cycle breaking. Cycle breaking looks for cycles in the graph and determines which edges to reverse to break the cycles. Reversed edges will end up pointing to the opposite direction of regular edges (that is, reversed edges will point left if edges usually point right)."),Z9e),vs),f9e),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,GI),oce),"Node Layering Strategy"),"Strategy for node layering."),cTe),vs),u_e),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,hke),oce),"Layer Constraint"),"Determines a constraint on the placement of the node regarding the layering."),aTe),vs),G9e),rn(ua)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,fke),oce),"Layer Choice Constraint"),"Allows to set a constraint regarding the layer placement of a node. Let i be the value of teh constraint. Assumed the drawing has n layers and i < n. If set to i, it expresses that the node should be placed in i-th layer. Should i>=n be true then the node is placed in the last layer of the drawing. Note that this option is not part of any of ELK Layered's default configurations but is only evaluated as part of the `InteractiveLayeredGraphVisitor`, which must be applied manually or used via the `DiagramLayoutEngine."),ct(-1)),Cc),Za),rn(ua)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,dke),oce),"Layer ID"),"Layer identifier that was calculated by ELK Layered for a node. This is only generated if interactiveLayot or generatePositionAndLayerIds is set."),ct(-1)),Cc),Za),rn(ua)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Foe),_ft),"Upper Bound On Width [MinWidth Layerer]"),"Defines a loose upper bound on the width of the MinWidth layerer. If set to '-1' multiple values are tested and the best result is selected."),ct(4)),Cc),Za),rn(Fn)))),va(t,Foe,GI,Obt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,joe),_ft),"Upper Layer Estimation Scaling Factor [MinWidth Layerer]"),"Multiplied with Upper Bound On Width for defining an upper bound on the width of layers which haven't been determined yet, but whose maximum width had been (roughly) estimated by the MinWidth algorithm. Compensates for too high estimations. If set to '-1' multiple values are tested and the best result is selected."),ct(2)),Cc),Za),rn(Fn)))),va(t,joe,GI,Pbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,$oe),Cft),"Node Promotion Strategy"),"Reduces number of dummy nodes after layering phase (if possible)."),oTe),vs),w_e),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Hoe),Cft),"Max Node Promotion Iterations"),"Limits the number of iterations for node promotion."),ct(0)),Cc),Za),rn(Fn)))),va(t,Hoe,$oe,null),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,zoe),"layering.coffmanGraham"),"Layer Bound"),"The maximum number of nodes allowed per layer."),ct(Ei)),Cc),Za),rn(Fn)))),va(t,zoe,GI,Abt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,MC),qI),"Crossing Minimization Strategy"),"Strategy for crossing minimization."),Q9e),vs),c9e),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,gke),qI),"Force Node Model Order"),"The node order given by the model does not change to produce a better layout. E.g. if node A is before node B in the model this is not changed during crossing minimization. This assumes that the node model order is already respected before crossing minimization. This can be achieved by setting considerModelOrder.strategy to NODES_AND_EDGES."),!1),za),Us),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Goe),qI),"Hierarchical Sweepiness"),"How likely it is to use cross-hierarchy (1) vs bottom-up (-1)."),.1),qo),ma),rn(Fn)))),va(t,Goe,nG,ebt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,qoe),qI),"Semi-Interactive Crossing Minimization"),"Preserves the order of nodes within a layer but still minimizes crossings between edges connecting long edge dummies. Derives the desired order from positions specified by the 'org.eclipse.elk.position' layout option. Requires a crossing minimization strategy that is able to process 'in-layer' constraints."),!1),za),Us),rn(Fn)))),va(t,qoe,MC,ibt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,pke),qI),"Position Choice Constraint"),"Allows to set a constraint regarding the position placement of a node in a layer. Assumed the layer in which the node placed includes n other nodes and i < n. If set to i, it expresses that the node should be placed at the i-th position. Should i>=n be true then the node is placed at the last position in the layer. Note that this option is not part of any of ELK Layered's default configurations but is only evaluated as part of the `InteractiveLayeredGraphVisitor`, which must be applied manually or used via the `DiagramLayoutEngine."),ct(-1)),Cc),Za),rn(ua)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,bke),qI),"Position ID"),"Position within a layer that was determined by ELK Layered for a node. This is only generated if interactiveLayot or generatePositionAndLayerIds is set."),ct(-1)),Cc),Za),rn(ua)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,vke),Sft),"Greedy Switch Activation Threshold"),"By default it is decided automatically if the greedy switch is activated or not. The decision is based on whether the size of the input graph (without dummy nodes) is smaller than the value of this option. A '0' enforces the activation."),ct(40)),Cc),Za),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Voe),Sft),"Greedy Switch Crossing Minimization"),"Greedy Switch strategy for crossing minimization. The greedy switch heuristic is executed after the regular crossing minimization as a post-processor. Note that if 'hierarchyHandling' is set to 'INCLUDE_CHILDREN', the 'greedySwitchHierarchical.type' option must be used."),X9e),vs),Ale),rn(Fn)))),va(t,Voe,MC,Z2t),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,qz),"crossingMinimization.greedySwitchHierarchical"),"Greedy Switch Crossing Minimization (hierarchical)"),"Activates the greedy switch heuristic in case hierarchical layout is used. The differences to the non-hierarchical case (see 'greedySwitch.type') are: 1) greedy switch is inactive by default, 3) only the option value set on the node at which hierarchical layout starts is relevant, and 2) if it's activated by the user, it properly addresses hierarchy-crossing edges."),Y9e),vs),Ale),rn(Fn)))),va(t,qz,MC,Y2t),va(t,qz,nG,X2t),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,T4),Aft),"Node Placement Strategy"),"Strategy for node placement."),fTe),vs),d_e),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(Wt(Xt(Kt(Yt(new Ht,Vz),Aft),"Favor Straight Edges Over Balancing"),"Favor straight edges over a balanced node placement. The default behavior is determined automatically based on the used 'edgeRouting'. For an orthogonal style it is set to true, for all other styles to false."),za),Us),rn(Fn)))),va(t,Vz,T4,Ubt),va(t,Vz,T4,Wbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Uoe),Lft),"BK Edge Straightening"),"Specifies whether the Brandes Koepf node placer tries to increase the number of straight edges at the expense of diagram size. There is a subtle difference to the 'favorStraightEdges' option, which decides whether a balanced placement of the nodes is desired, or not. In bk terms this means combining the four alignments into a single balanced one, or not. This option on the other hand tries to straighten additional edges during the creation of each of the four alignments."),uTe),vs),v9e),rn(Fn)))),va(t,Uoe,T4,zbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Woe),Lft),"BK Fixed Alignment"),"Tells the BK node placer to use a certain alignment (out of its four) instead of the one producing the smallest height, or the combination of all four."),lTe),vs),x9e),rn(Fn)))),va(t,Woe,T4,qbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Koe),"nodePlacement.linearSegments"),"Linear Segments Deflection Dampening"),"Dampens the movement of nodes to keep the diagram from getting too large."),.3),qo),ma),rn(Fn)))),va(t,Koe,T4,Ybt),en(t,new Vt(Zt(Qt(Jt(Wt(Xt(Kt(Yt(new Ht,Yoe),"nodePlacement.networkSimplex"),"Node Flexibility"),"Aims at shorter and straighter edges. Two configurations are possible: (a) allow ports to move freely on the side they are assigned to (the order is always defined beforehand), (b) additionally allow to enlarge a node wherever it helps. If this option is not configured for a node, the 'nodeFlexibility.default' value is used, which is specified for the node's parent."),vs),ahe),rn(ua)))),va(t,Yoe,T4,Jbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Xoe),"nodePlacement.networkSimplex.nodeFlexibility"),"Node Flexibility Default"),"Default value of the 'nodeFlexibility' option for the children of a hierarchical node."),hTe),vs),ahe),rn(Fn)))),va(t,Xoe,T4,Zbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,wke),Mft),"Self-Loop Distribution"),"Alter the distribution of the loops around the node. It only takes effect for PortConstraints.FREE."),nTe),vs),T_e),rn(ua)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,mke),Mft),"Self-Loop Ordering"),"Alter the ordering of the loops they can either be stacked or sequenced. It only takes effect for PortConstraints.FREE."),rTe),vs),__e),rn(ua)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Uz),"edgeRouting.splines"),"Spline Routing Mode"),"Specifies the way control points are assembled for each individual edge. CONSERVATIVE ensures that edges are properly routed around the nodes but feels rather orthogonal at times. SLOPPY uses fewer control points to obtain curvier edge routes but may result in edges overlapping nodes."),iTe),vs),S_e),rn(Fn)))),va(t,Uz,VI,pbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Wz),"edgeRouting.splines.sloppy"),"Sloppy Spline Layer Spacing Factor"),"Spacing factor for routing area between layers when using sloppy spline routing."),.2),qo),ma),rn(Fn)))),va(t,Wz,VI,vbt),va(t,Wz,Uz,wbt),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,Qoe),"edgeRouting.polyline"),"Sloped Edge Zone Width"),"Width of the strip to the left and to the right of each layer where the polyline edge router is allowed to refrain from ensuring that edges are routed horizontally. This prevents awkward bend points for nodes that extent almost to the edge of their layer."),2),qo),ma),rn(Fn)))),va(t,Qoe,VI,hbt),en(t,new Vt(Zt(Qt(Jt(Wt(Xt(Kt(Yt(new Ht,yke),G1),"Spacing Base Value"),"An optional base value for all other layout options of the 'spacing' group. It can be used to conveniently alter the overall 'spaciousness' of the drawing. Whenever an explicit value is set for the other layout options, this base value will have no effect. The base value is not inherited, i.e. it must be set for each hierarchical node."),qo),ma),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,kke),G1),"Edge Node Between Layers Spacing"),"The spacing to be preserved between nodes and edges that are routed next to the node's layer. For the spacing between nodes and edges that cross the node's layer 'spacing.edgeNode' is used."),10),qo),ma),rn(Fn)))),en(t,new Vt(Zt(Qt(Jt(pn(Wt(Xt(Kt(Yt(new Ht,xke),G1),"Edge Edge Between Layer Spacing"),"Spacing to be preserved between pairs of edges that are routed between the same pair of layers. 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xg(16,this):t?this.p=new yg(19,t,this):this.p=new xg(18,this):this.Bb&Zu?t?this.p=new yg(21,t,this):this.p=new xg(20,this):t?this.p=new yg(23,t,this):this.p=new xg(22,this):this.qk()?this.sk()?this.p=new MWe(u(o,26),this,s):this.p=new vwe(u(o,26),this,s):we(o,148)?t==eU?this.p=new xg(40,this):this.Bb&Zu?t?this.p=new AKe(n,v,this,(Gie(),d==Lr?qAe:d==El?jAe:d==S2?VAe:d==Xy?GAe:d==pa?zAe:d==a5?UAe:d==el?$Ae:d==Sh?HAe:_fe)):this.p=new $Ye(u(o,148),n,v,this):t?this.p=new SKe(n,v,this,(Gie(),d==Lr?qAe:d==El?jAe:d==S2?VAe:d==Xy?GAe:d==pa?zAe:d==a5?UAe:d==el?$Ae:d==Sh?HAe:_fe)):this.p=new jYe(u(o,148),n,v,this):this.rk()?s?this.Bb&Zu?this.sk()?this.p=new IWe(u(o,26),this,s):this.p=new cve(u(o,26),this,s):this.sk()?this.p=new DWe(u(o,26),this,s):this.p=new wne(u(o,26),this,s):this.Bb&Zu?this.sk()?this.p=new SUe(u(o,26),this):this.p=new xbe(u(o,26),this):this.sk()?this.p=new CUe(u(o,26),this):this.p=new ine(u(o,26),this):this.sk()?s?this.Bb&Zu?this.p=new OWe(u(o,26),this,s):this.p=new ave(u(o,26),this,s):this.Bb&Zu?this.p=new AUe(u(o,26),this):this.p=new Ebe(u(o,26),this):s?this.Bb&Zu?this.p=new NWe(u(o,26),this,s):this.p=new ove(u(o,26),this,s):this.Bb&Zu?this.p=new LUe(u(o,26),this):this.p=new Mj(u(o,26),this)),this.p},l.Ij=function(){return(this.Bb&Sf)!=0},l.qk=function(){return!1},l.rk=function(){return!1},l.Jj=function(){return(this.Bb&Ed)!=0},l.Oj=function(){return Ure(this)},l.sk=function(){return!1},l.Kj=function(){return(this.Bb&Zu)!=0},l.tk=function(t){this.k=t},l.Lh=function(t){bre(this,t)},l.Ib=function(){return lz(this)},l.e=!1,l.n=0,O(Tn,"EStructuralFeatureImpl",449),M(322,449,{105:1,92:1,90:1,34:1,147:1,191:1,56:1,170:1,66:1,108:1,472:1,49:1,97:1,322:1,150:1,449:1,284:1,114:1,115:1,677:1},Vee),l._g=function(t,n,r){var s,o;switch(t){case 0:return!this.Ab&&(this.Ab=new at(ti,this,0,3)),this.Ab;case 1:return this.zb;case 2:return Mn(),!!(this.Bb&256);case 3:return Mn(),!!(this.Bb&512);case 4:return ct(this.s);case 5:return ct(this.t);case 6:return Mn(),!!j4e(this);case 7:return Mn(),o=this.s,o>=1;case 8:return n?$h(this):this.r;case 9:return this.q;case 10:return Mn(),!!(this.Bb&Sf);case 11:return Mn(),!!(this.Bb&ky);case 12:return Mn(),!!(this.Bb&dy);case 13:return this.j;case 14:return b7(this);case 15:return Mn(),!!(this.Bb&Zu);case 16:return Mn(),!!(this.Bb&Ed);case 17:return Fm(this);case 18:return Mn(),!!(this.Bb&_c);case 19:return n?lie(this):$Ze(this)}return ph(this,t-Jn((on(),Wy)),gn((s=u(_n(this,16),26),s||Wy),t),n,r)},l.lh=function(t){var n,r;switch(t){case 0:return!!this.Ab&&this.Ab.i!=0;case 1:return this.zb!=null;case 2:return(this.Bb&256)==0;case 3:return(this.Bb&512)==0;case 4:return this.s!=0;case 5:return this.t!=1;case 6:return j4e(this);case 7:return r=this.s,r>=1;case 8:return!!this.r&&!this.q.e&&Mv(this.q).i==0;case 9:return!!this.q&&!(this.r&&!this.q.e&&Mv(this.q).i==0);case 10:return(this.Bb&Sf)==0;case 11:return(this.Bb&ky)!=0;case 12:return(this.Bb&dy)!=0;case 13:return this.j!=null;case 14:return b7(this)!=null;case 15:return(this.Bb&Zu)!=0;case 16:return(this.Bb&Ed)!=0;case 17:return!!Fm(this);case 18:return(this.Bb&_c)!=0;case 19:return!!$Ze(this)}return dh(this,t-Jn((on(),Wy)),gn((n=u(_n(this,16),26),n||Wy),t))},l.sh=function(t,n){var r,s;switch(t){case 0:!this.Ab&&(this.Ab=new at(ti,this,0,3)),_r(this.Ab),!this.Ab&&(this.Ab=new at(ti,this,0,3)),fs(this.Ab,u(n,14));return;case 1:bre(this,Hr(n));return;case 2:Lg(this,It(Mt(n)));return;case 3:Mg(this,It(Mt(n)));return;case 4:Cg(this,u(n,19).a);return;case 5:wze(this,u(n,19).a);return;case 8:cb(this,u(n,138));return;case 9:s=$1(this,u(n,87),null),s&&s.Fi();return;case 10:J8(this,It(Mt(n)));return;case 11:n7(this,It(Mt(n)));return;case 12:e7(this,It(Mt(n)));return;case 13:N2e(this,Hr(n));return;case 15:t7(this,It(Mt(n)));return;case 16:r7(this,It(Mt(n)));return;case 18:Pie(this,It(Mt(n)));return}yh(this,t-Jn((on(),Wy)),gn((r=u(_n(this,16),26),r||Wy),t),n)},l.zh=function(){return on(),Wy},l.Bh=function(t){var n,r;switch(t){case 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2:Vte(this,Hr(n));return;case 5:x7(this,Hr(n));return;case 7:!this.A&&(this.A=new qu(mu,this,7)),_r(this.A),!this.A&&(this.A=new qu(mu,this,7)),fs(this.A,u(n,14));return}yh(this,t-Jn(this.zh()),gn((r=u(_n(this,16),26),r||this.zh()),t),n)},l.zh=function(){return on(),s4t},l.Bh=function(t){var n;switch(t){case 0:!this.Ab&&(this.Ab=new at(ti,this,0,3)),_r(this.Ab);return;case 1:we(this.Cb,179)&&(u(this.Cb,179).tb=null),au(this,null);return;case 2:Y8(this,null),R8(this,this.D);return;case 5:x7(this,null);return;case 7:!this.A&&(this.A=new qu(mu,this,7)),_r(this.A);return}wh(this,t-Jn(this.zh()),gn((n=u(_n(this,16),26),n||this.zh()),t))},l.yj=function(){var t;return this.G==-1&&(this.G=(t=Gl(this),t?Dg(t.Mh(),this):-1)),this.G},l.zj=function(){return null},l.Aj=function(){return Gl(this)},l.vk=function(){return this.v},l.Bj=function(){return Jv(this)},l.Cj=function(){return this.D!=null?this.D:this.B},l.Dj=function(){return this.F},l.wj=function(t){return oae(this,t)},l.wk=function(t){this.v=t},l.xk=function(t){wtt(this,t)},l.yk=function(t){this.C=t},l.Lh=function(t){l$(this,t)},l.Ib=function(){return xH(this)},l.C=null,l.D=null,l.G=-1,O(Tn,"EClassifierImpl",351),M(88,351,{105:1,92:1,90:1,26:1,138:1,147:1,191:1,56:1,108:1,49:1,97:1,88:1,351:1,150:1,473:1,114:1,115:1,676:1},YL),l.uk=function(t){return XKt(this,t.Tg())},l._g=function(t,n,r){var s;switch(t){case 0:return!this.Ab&&(this.Ab=new at(ti,this,0,3)),this.Ab;case 1:return this.zb;case 2:return this.D!=null?this.D:this.B;case 3:return Jv(this);case 4:return null;case 5:return this.F;case 6:return n?Gl(this):x8(this);case 7:return!this.A&&(this.A=new qu(mu,this,7)),this.A;case 8:return Mn(),!!(this.Bb&256);case 9:return Mn(),!!(this.Bb&512);case 10:return jo(this);case 11:return!this.q&&(this.q=new at(nf,this,11,10)),this.q;case 12:return b4(this);case 13:return fC(this);case 14:return fC(this),this.r;case 15:return b4(this),this.k;case 16:return L4e(this);case 17:return fae(this);case 18:return xd(this);case 19:return rz(this);case 20:return b4(this),this.o;case 21:return!this.s&&(this.s=new at(ju,this,21,17)),this.s;case 22:return jc(this);case 23:return Qse(this)}return ph(this,t-Jn((on(),E2)),gn((s=u(_n(this,16),26),s||E2),t),n,r)},l.hh=function(t,n,r){var s,o,h;switch(n){case 0:return!this.Ab&&(this.Ab=new at(ti,this,0,3)),ou(this.Ab,t,r);case 6:return this.Cb&&(r=(o=this.Db>>16,o>=0?pse(this,r):this.Cb.ih(this,-1-o,null,r))),Kl(this,t,6,r);case 11:return!this.q&&(this.q=new at(nf,this,11,10)),ou(this.q,t,r);case 21:return!this.s&&(this.s=new at(ju,this,21,17)),ou(this.s,t,r)}return h=u(gn((s=u(_n(this,16),26),s||(on(),E2)),n),66),h.Nj().Qj(this,du(this),n-Jn((on(),E2)),t,r)},l.jh=function(t,n,r){var s,o;switch(n){case 0:return!this.Ab&&(this.Ab=new at(ti,this,0,3)),Xa(this.Ab,t,r);case 6:return Kl(this,null,6,r);case 7:return!this.A&&(this.A=new qu(mu,this,7)),Xa(this.A,t,r);case 11:return!this.q&&(this.q=new at(nf,this,11,10)),Xa(this.q,t,r);case 21:return!this.s&&(this.s=new at(ju,this,21,17)),Xa(this.s,t,r);case 22:return Xa(jc(this),t,r)}return o=u(gn((s=u(_n(this,16),26),s||(on(),E2)),n),66),o.Nj().Rj(this,du(this),n-Jn((on(),E2)),t,r)},l.lh=function(t){var n;switch(t){case 0:return!!this.Ab&&this.Ab.i!=0;case 1:return this.zb!=null;case 2:return this.D!=null&&this.D==this.F;case 3:return!!Jv(this);case 4:return!1;case 5:return this.F!=null&&this.F!=this.D&&this.F!=this.B;case 6:return!!x8(this);case 7:return!!this.A&&this.A.i!=0;case 8:return(this.Bb&256)!=0;case 9:return(this.Bb&512)!=0;case 10:return!!this.u&&jc(this.u.a).i!=0&&!(this.n&&ise(this.n));case 11:return!!this.q&&this.q.i!=0;case 12:return b4(this).i!=0;case 13:return fC(this).i!=0;case 14:return fC(this),this.r.i!=0;case 15:return b4(this),this.k.i!=0;case 16:return L4e(this).i!=0;case 17:return fae(this).i!=0;case 18:return xd(this).i!=0;case 19:return rz(this).i!=0;case 20:return b4(this),!!this.o;case 21:return!!this.s&&this.s.i!=0;case 22:return!!this.n&&ise(this.n);case 23:return Qse(this).i!=0}return dh(this,t-Jn((on(),E2)),gn((n=u(_n(this,16),26),n||E2),t))},l.oh=function(t){var n;return n=this.i==null||this.q&&this.q.i!=0?null:dI(this,t),n||a6e(this,t)},l.sh=function(t,n){var r;switch(t){case 0:!this.Ab&&(this.Ab=new at(ti,this,0,3)),_r(this.Ab),!this.Ab&&(this.Ab=new at(ti,this,0,3)),fs(this.Ab,u(n,14));return;case 1:l$(this,Hr(n));return;case 2:Vte(this,Hr(n));return;case 5:x7(this,Hr(n));return;case 7:!this.A&&(this.A=new qu(mu,this,7)),_r(this.A),!this.A&&(this.A=new qu(mu,this,7)),fs(this.A,u(n,14));return;case 8:Nye(this,It(Mt(n)));return;case 9:Pye(this,It(Mt(n)));return;case 10:pC(jo(this)),fs(jo(this),u(n,14));return;case 11:!this.q&&(this.q=new at(nf,this,11,10)),_r(this.q),!this.q&&(this.q=new at(nf,this,11,10)),fs(this.q,u(n,14));return;case 21:!this.s&&(this.s=new at(ju,this,21,17)),_r(this.s),!this.s&&(this.s=new at(ju,this,21,17)),fs(this.s,u(n,14));return;case 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1:(!this.c&&(this.c=new ds(this,0)),u(u(Wc(this.c,(Fi(),zb)),153),215)).Wb(n);return;case 2:!this.b&&(this.b=new ds(this,2)),XM(this.b,n);return;case 3:Mwe(this,Hr(n));return;case 4:Mwe(this,Ube(this.a,n));return;case 5:Ac(this,u(n,148));return}yh(this,t-Jn((Fi(),i5)),gn(this.j&2?(!this.k&&(this.k=new ch),this.k).ck():i5,t),n)},l.zh=function(){return Fi(),i5},l.Bh=function(t){switch(t){case 0:!this.c&&(this.c=new ds(this,0)),_r(this.c);return;case 1:(!this.c&&(this.c=new ds(this,0)),u(Wc(this.c,(Fi(),zb)),153)).$b();return;case 2:!this.b&&(this.b=new ds(this,2)),_r(this.b);return;case 3:!this.c&&(this.c=new ds(this,0)),vz(this.c,(Fi(),QS),null);return;case 4:Mwe(this,Ube(this.a,null));return;case 5:this.a=null;return}wh(this,t-Jn((Fi(),i5)),gn(this.j&2?(!this.k&&(this.k=new ch),this.k).ck():i5,t))},O(As,"SimpleAnyTypeImpl",668),M(669,506,{105:1,92:1,90:1,56:1,49:1,97:1,2023:1,669:1},OHe),l._g=function(t,n,r){switch(t){case 0:return r?(!this.a&&(this.a=new ds(this,0)),this.a):(!this.a&&(this.a=new ds(this,0)),this.a.b);case 1:return r?(!this.b&&(this.b=new Nl((on(),oo),wc,this,1)),this.b):(!this.b&&(this.b=new Nl((on(),oo),wc,this,1)),hD(this.b));case 2:return r?(!this.c&&(this.c=new Nl((on(),oo),wc,this,2)),this.c):(!this.c&&(this.c=new Nl((on(),oo),wc,this,2)),hD(this.c));case 3:return!this.a&&(this.a=new ds(this,0)),Wc(this.a,(Fi(),dN));case 4:return!this.a&&(this.a=new ds(this,0)),Wc(this.a,(Fi(),gN));case 5:return!this.a&&(this.a=new ds(this,0)),Wc(this.a,(Fi(),ZS));case 6:return!this.a&&(this.a=new ds(this,0)),Wc(this.a,(Fi(),JS))}return ph(this,t-Jn((Fi(),Pw)),gn(this.j&2?(!this.k&&(this.k=new ch),this.k).ck():Pw,t),n,r)},l.jh=function(t,n,r){var s;switch(n){case 0:return!this.a&&(this.a=new ds(this,0)),vI(this.a,t,r);case 1:return!this.b&&(this.b=new Nl((on(),oo),wc,this,1)),vj(this.b,t,r);case 2:return!this.c&&(this.c=new Nl((on(),oo),wc,this,2)),vj(this.c,t,r);case 5:return!this.a&&(this.a=new ds(this,0)),FUe(Wc(this.a,(Fi(),ZS)),t,r)}return s=u(gn(this.j&2?(!this.k&&(this.k=new ch),this.k).ck():(Fi(),Pw),n),66),s.Nj().Rj(this,vme(this),n-Jn((Fi(),Pw)),t,r)},l.lh=function(t){switch(t){case 0:return!!this.a&&this.a.i!=0;case 1:return!!this.b&&this.b.f!=0;case 2:return!!this.c&&this.c.f!=0;case 3:return!this.a&&(this.a=new ds(this,0)),!YF(Wc(this.a,(Fi(),dN)));case 4:return!this.a&&(this.a=new ds(this,0)),!YF(Wc(this.a,(Fi(),gN)));case 5:return!this.a&&(this.a=new ds(this,0)),!YF(Wc(this.a,(Fi(),ZS)));case 6:return!this.a&&(this.a=new ds(this,0)),!YF(Wc(this.a,(Fi(),JS)))}return dh(this,t-Jn((Fi(),Pw)),gn(this.j&2?(!this.k&&(this.k=new ch),this.k).ck():Pw,t))},l.sh=function(t,n){switch(t){case 0:!this.a&&(this.a=new ds(this,0)),XM(this.a,n);return;case 1:!this.b&&(this.b=new Nl((on(),oo),wc,this,1)),sH(this.b,n);return;case 2:!this.c&&(this.c=new Nl((on(),oo),wc,this,2)),sH(this.c,n);return;case 3:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),dN))),!this.a&&(this.a=new ds(this,0)),t_(Wc(this.a,dN),u(n,14));return;case 4:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),gN))),!this.a&&(this.a=new ds(this,0)),t_(Wc(this.a,gN),u(n,14));return;case 5:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),ZS))),!this.a&&(this.a=new ds(this,0)),t_(Wc(this.a,ZS),u(n,14));return;case 6:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),JS))),!this.a&&(this.a=new ds(this,0)),t_(Wc(this.a,JS),u(n,14));return}yh(this,t-Jn((Fi(),Pw)),gn(this.j&2?(!this.k&&(this.k=new ch),this.k).ck():Pw,t),n)},l.zh=function(){return Fi(),Pw},l.Bh=function(t){switch(t){case 0:!this.a&&(this.a=new ds(this,0)),_r(this.a);return;case 1:!this.b&&(this.b=new Nl((on(),oo),wc,this,1)),this.b.c.$b();return;case 2:!this.c&&(this.c=new Nl((on(),oo),wc,this,2)),this.c.c.$b();return;case 3:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),dN)));return;case 4:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),gN)));return;case 5:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),ZS)));return;case 6:!this.a&&(this.a=new ds(this,0)),d6(Wc(this.a,(Fi(),JS)));return}wh(this,t-Jn((Fi(),Pw)),gn(this.j&2?(!this.k&&(this.k=new ch),this.k).ck():Pw,t))},l.Ib=function(){var t;return this.j&4?_f(this):(t=new Ph(_f(this)),t.a+=" (mixed: ",QT(t,this.a),t.a+=")",t.a)},O(As,"XMLTypeDocumentRootImpl",669),M(1919,704,{105:1,92:1,90:1,471:1,147:1,56:1,108:1,49:1,97:1,150:1,114:1,115:1,2024:1},bm),l.Ih=function(t,n){switch(t.yj()){case 7:case 8:case 9:case 10:case 16:case 22:case 23:case 24:case 25:case 26:case 32:case 33:case 34:case 36:case 37:case 44:case 45:case 50:case 51:case 53:case 55:case 56:case 57:case 58:case 60:case 61:case 4:return n==null?null:Qo(n);case 19:case 28:case 29:case 35:case 38:case 39:case 41:case 46:case 52:case 54:case 5:return Hr(n);case 6:return _Kt(u(n,190));case 12:case 47:case 49:case 11:return ult(this,t,n);case 13:return n==null?null:fvn(u(n,240));case 15:case 14:return n==null?null:xZt(Ue(ft(n)));case 17:return fst((Fi(),n));case 18:return fst(n);case 21:case 20:return n==null?null:EZt(u(n,155).a);case 27:return CKt(u(n,190));case 30:return Ait((Fi(),u(n,15)));case 31:return Ait(u(n,15));case 40:return AKt((Fi(),n));case 42:return dst((Fi(),n));case 43:return dst(n);case 59:case 48:return SKt((Fi(),n));default:throw J(new Ln($7+t.ne()+dw))}},l.Jh=function(t){var n,r,s,o,h;switch(t.G==-1&&(t.G=(r=Gl(t),r?Dg(r.Mh(),t):-1)),t.G){case 0:return n=new Tpe,n;case 1:return s=new fR,s;case 2:return o=new NHe,o;case 3:return h=new OHe,h;default:throw J(new Ln(Pce+t.zb+dw))}},l.Kh=function(t,n){var r,s,o,h,d,v,x,_,L,P,z,q,W,X,le,Ce;switch(t.yj()){case 5:case 52:case 4:return n;case 6:return zcn(n);case 8:case 7:return n==null?null:Lhn(n);case 9:return n==null?null:xD(Wl((s=Xc(n,!0),s.length>0&&(zr(0,s.length),s.charCodeAt(0)==43)?s.substr(1):s),-128,127)<<24>>24);case 10:return n==null?null:xD(Wl((o=Xc(n,!0),o.length>0&&(zr(0,o.length),o.charCodeAt(0)==43)?o.substr(1):o),-128,127)<<24>>24);case 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n==null?null:lb(xz((q=Xc(n,!0),q.length>0&&(zr(0,q.length),q.charCodeAt(0)==43)?q.substr(1):q)));case 37:return n==null?null:lb(xz((W=Xc(n,!0),W.length>0&&(zr(0,W.length),W.charCodeAt(0)==43)?W.substr(1):W)));case 40:return Jon((Fi(),n));case 42:return Brt((Fi(),n));case 43:return Brt(n);case 44:return n==null?null:new Ip((X=Xc(n,!0),X.length>0&&(zr(0,X.length),X.charCodeAt(0)==43)?X.substr(1):X));case 45:return n==null?null:new Ip((le=Xc(n,!0),le.length>0&&(zr(0,le.length),le.charCodeAt(0)==43)?le.substr(1):le));case 46:return Xc(n,!1);case 47:return Hr(aw(this,(Fi(),O4t),n));case 59:case 48:return Zon((Fi(),n));case 49:return Hr(aw(this,(Fi(),N4t),n));case 50:return n==null?null:Z8(Wl((Ce=Xc(n,!0),Ce.length>0&&(zr(0,Ce.length),Ce.charCodeAt(0)==43)?Ce.substr(1):Ce),_G,32767)<<16>>16);case 51:return n==null?null:Z8(Wl((h=Xc(n,!0),h.length>0&&(zr(0,h.length),h.charCodeAt(0)==43)?h.substr(1):h),_G,32767)<<16>>16);case 53:return Hr(aw(this,(Fi(),P4t),n));case 55:return n==null?null:Z8(Wl((d=Xc(n,!0),d.length>0&&(zr(0,d.length),d.charCodeAt(0)==43)?d.substr(1):d),_G,32767)<<16>>16);case 56:return n==null?null:Z8(Wl((v=Xc(n,!0),v.length>0&&(zr(0,v.length),v.charCodeAt(0)==43)?v.substr(1):v),_G,32767)<<16>>16);case 57:return n==null?null:lb(xz((x=Xc(n,!0),x.length>0&&(zr(0,x.length),x.charCodeAt(0)==43)?x.substr(1):x)));case 58:return n==null?null:lb(xz((_=Xc(n,!0),_.length>0&&(zr(0,_.length),_.charCodeAt(0)==43)?_.substr(1):_)));case 60:return n==null?null:ct(Wl((r=Xc(n,!0),r.length>0&&(zr(0,r.length),r.charCodeAt(0)==43)?r.substr(1):r),$a,Ei));case 61:return n==null?null:ct(Wl(Xc(n,!0),$a,Ei));default:throw J(new Ln($7+t.ne()+dw))}};var R4t,tLe,F4t,nLe;O(As,"XMLTypeFactoryImpl",1919),M(586,179,{105:1,92:1,90:1,147:1,191:1,56:1,235:1,108:1,49:1,97:1,150:1,179:1,114:1,115:1,675:1,1945:1,586:1},mYe),l.N=!1,l.O=!1;var j4t=!1;O(As,"XMLTypePackageImpl",586),M(1852,1,{837:1},e6),l._j=function(){return 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f=0;f<5;f++)a+=` + .subgraph-lvl-${f} { + fill: ${i[`surface${f}`]}; + stroke: ${i[`surfacePeer${f}`]}; + } + `;return a},iqt=Object.freeze(Object.defineProperty({__proto__:null,diagram:{db:hMt,renderer:nqt,parser:Dde,styles:i=>`.label { + font-family: ${i.fontFamily}; + color: ${i.nodeTextColor||i.textColor}; + } + .cluster-label text { + fill: ${i.titleColor}; + } + .cluster-label span { + color: ${i.titleColor}; + } + + .label text,span { + fill: ${i.nodeTextColor||i.textColor}; + color: ${i.nodeTextColor||i.textColor}; + } + + .node rect, + .node circle, + .node ellipse, + .node polygon, + .node path { + fill: ${i.mainBkg}; + stroke: ${i.nodeBorder}; + stroke-width: 1px; + } + + .node .label { + text-align: center; + } + .node.clickable { + cursor: pointer; + } + + .arrowheadPath { + fill: ${i.arrowheadColor}; + } + + .edgePath .path { + stroke: ${i.lineColor}; + stroke-width: 2.0px; + } + + .flowchart-link { + stroke: ${i.lineColor}; + fill: none; + } + + .edgeLabel { + background-color: ${i.edgeLabelBackground}; + rect { + opacity: 0.85; + background-color: ${i.edgeLabelBackground}; + fill: ${i.edgeLabelBackground}; + } + text-align: center; + } + + .cluster rect { + fill: ${i.clusterBkg}; + stroke: ${i.clusterBorder}; + stroke-width: 1px; + } + + .cluster text { + fill: ${i.titleColor}; + } + + .cluster span { + color: ${i.titleColor}; + } + /* .cluster div { + color: ${i.titleColor}; + } */ + + div.mermaidTooltip { + position: absolute; + text-align: center; + max-width: 200px; + padding: 2px; + font-family: ${i.fontFamily}; + font-size: 12px; + background: ${i.tertiaryColor}; + border: 1px solid ${i.border2}; + border-radius: 2px; + pointer-events: none; + z-index: 100; + } + + .flowchartTitleText { + text-anchor: middle; + font-size: 18px; + fill: ${i.textColor}; + } + .subgraph { + stroke-width:2; + rx:3; + } + // .subgraph-lvl-1 { + // fill:#ccc; + // // stroke:black; + // } + + .flowchart-label text { + text-anchor: middle; + } + + ${rqt(i)} 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w.attr("x",a.x+a.textMargin*2),w.text(f),p},lqt=function(i,a){function f(w,y,b,E,S){return w+","+y+" "+(w+b)+","+y+" "+(w+b)+","+(y+E-S)+" "+(w+b-S*1.2)+","+(y+E)+" "+w+","+(y+E)}const p=i.append("polygon");p.attr("points",f(a.x,a.y,50,20,7)),p.attr("class","labelBox"),a.y=a.y+a.labelMargin,a.x=a.x+.5*a.labelMargin,rje(i,a)},hqt=function(i,a,f){const p=i.append("g"),w=Oge();w.x=a.x,w.y=a.y,w.fill=a.fill,w.width=f.width,w.height=f.height,w.class="journey-section section-type-"+a.num,w.rx=3,w.ry=3,KK(p,w),sje(f)(a.text,p,w.x,w.y,w.width,w.height,{class:"journey-section section-type-"+a.num},f,a.colour)};let ije=-1;const fqt=function(i,a,f){const p=a.x+f.width/2,w=i.append("g");ije++;const y=300+5*30;w.append("line").attr("id","task"+ije).attr("x1",p).attr("y1",a.y).attr("x2",p).attr("y2",y).attr("class","task-line").attr("stroke-width","1px").attr("stroke-dasharray","4 2").attr("stroke","#666"),cqt(w,{cx:p,cy:300+(5-a.score)*30,score:a.score});const 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p=i.append("g"),y=p.append("text").text(a.descr).attr("dy","1em").attr("alignment-baseline","middle").attr("dominant-baseline","middle").attr("text-anchor","middle").call(aje,a.width).node().getBBox(),b=f.fontSize&&f.fontSize.replace?f.fontSize.replace("px",""):f.fontSize;return p.remove(),y.height+b*1.1*.5+a.padding},wqt=function(i,a,f){i.append("path").attr("id","node-"+a.id).attr("class","node-bkg node-"+a.type).attr("d",`M0 ${a.height-5} v${-a.height+2*5} q0,-5 5,-5 h${a.width-2*5} q5,0 5,5 v${a.height-5} H0 Z`),i.append("line").attr("class","node-line-"+f).attr("x1",0).attr("y1",a.height).attr("x2",a.width).attr("y2",a.height)},v9={drawRect:KK,drawCircle:uqt,drawSection:hqt,drawText:rje,drawLabel:lqt,drawTask:fqt,drawBackgroundRect:dqt,getTextObj:gqt,getNoteRect:Oge,initGraphics:pqt,drawNode:bqt,getVirtualNodeHeight:vqt},mqt=function(i,a,f,p){var te,xe,De,he;const w=Tt(),y=w.leftMargin??50;(xe=(te=p.db).clear)==null||xe.call(te),p.parser.parse(i+` 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w=E,b},kqt={setConf:()=>{},draw:mqt},xqt=i=>{let a="";for(let f=0;f` + .edge { + stroke-width: 3; + } + ${xqt(i)} + .section-root rect, .section-root path, .section-root circle { + fill: ${i.git0}; + } + .section-root text { + fill: ${i.gitBranchLabel0}; + } + .icon-container { + height:100%; + display: flex; + justify-content: center; + align-items: center; + } + .edge { + fill: none; + } + .eventWrapper { + filter: brightness(120%); + } +`}},Symbol.toStringTag,{value:"Module"}));var Nge=function(){var i=function(ye,ke,Ae,de){for(Ae=Ae||{},de=ye.length;de--;Ae[ye[de]]=ke);return 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A3=A(Ra,m.hoverData.downs);A3&&(m.hoverData.dragging=!0,m.hoverData.justStartedPan=!0,qc[4]=0,m.data.bgActivePosistion=F5(is),m.redrawHint("select",!0),m.redraw())}Ra&&Ra.pannable()&&Ra.active()&&Ra.unactivate()}}else{if(Ra&&Ra.pannable()&&Ra.active()&&Ra.unactivate(),(!Ra||!Ra.grabbed())&&uo!=Lc&&(Lc&&k(Lc,["mouseout","tapdragout"],We,{x:qr[0],y:qr[1]}),uo&&k(uo,["mouseover","tapdragover"],We,{x:qr[0],y:qr[1]}),m.hoverData.last=uo),Ra)if(Yf){if(ar.boxSelectionEnabled()&&ov)Ra&&Ra.grabbed()&&(ue(Sl),Ra.emit("freeon"),Sl.emit("free"),m.dragData.didDrag&&(Ra.emit("dragfreeon"),Sl.emit("dragfree"))),l6();else if(Ra&&Ra.grabbed()&&m.nodeIsDraggable(Ra)){var qd=!m.dragData.didDrag;qd&&m.redrawHint("eles",!0),m.dragData.didDrag=!0,m.hoverData.draggingEles||ne(Sl,{inDragLayer:!0});var _1={x:0,y:0};if(te(lo[0])&&te(lo[1])&&(_1.x+=lo[0],_1.y+=lo[1],qd)){var Vd=m.hoverData.dragDelta;Vd&&te(Vd[0])&&te(Vd[1])&&(_1.x+=Vd[0],_1.y+=Vd[1])}m.hoverData.draggingEles=!0,Sl.silentShift(_1).emit("position 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Lc=Ir.collection(m.getAllInBox(or[0],or[1],or[2],or[3]));m.redrawHint("select",!0),Lc.length>0&&m.redrawHint("eles",!0),Ir.emit({type:"boxend",originalEvent:We,position:{x:ar[0],y:ar[1]}});var Ra=function(Yf){return Yf.selectable()&&!Yf.selected()};Ir.selectionType()==="additive"||Uo||Ir.$(g).unmerge(Lc).unselect(),Lc.emit("box").stdFilter(Ra).select().emit("boxselect"),m.redraw()}if(m.hoverData.dragging&&(m.hoverData.dragging=!1,m.redrawHint("select",!0),m.redrawHint("eles",!0),m.redraw()),!or[4]){m.redrawHint("drag",!0),m.redrawHint("eles",!0);var lo=is&&is.grabbed();ue(qr),lo&&(is.emit("freeon"),qr.emit("free"),m.dragData.didDrag&&(is.emit("dragfreeon"),qr.emit("dragfree")))}}or[4]=0,m.hoverData.down=null,m.hoverData.cxtStarted=!1,m.hoverData.draggingEles=!1,m.hoverData.selecting=!1,m.hoverData.isOverThresholdDrag=!1,m.dragData.didDrag=!1,m.hoverData.dragged=!1,m.hoverData.dragDelta=[],m.hoverData.mdownPos=null,m.hoverData.mdownGPos=null}},!1);var Je=function(We){if(!m.scrollingPage){var On=m.cy,Ir=On.zoom(),ar=On.pan(),or=m.projectIntoViewport(We.clientX,We.clientY),qa=[or[0]*Ir+ar.x,or[1]*Ir+ar.y];if(m.hoverData.draggingEles||m.hoverData.dragging||m.hoverData.cxtStarted||Re()){We.preventDefault();return}if(On.panningEnabled()&&On.userPanningEnabled()&&On.zoomingEnabled()&&On.userZoomingEnabled()){We.preventDefault(),m.data.wheelZooming=!0,clearTimeout(m.data.wheelTimeout),m.data.wheelTimeout=setTimeout(function(){m.data.wheelZooming=!1,m.redrawHint("eles",!0),m.redraw()},150);var qr;We.deltaY!=null?qr=We.deltaY/-250:We.wheelDeltaY!=null?qr=We.wheelDeltaY/1e3:qr=We.wheelDelta/1e3,qr=qr*m.wheelSensitivity;var is=We.deltaMode===1;is&&(qr*=33);var Uo=On.zoom()*Math.pow(10,qr);We.type==="gesturechange"&&(Uo=m.gestureStartZoom*We.scale),On.zoom({level:Uo,renderedPosition:{x:qa[0],y:qa[1]}}),On.emit(We.type==="gesturechange"?"pinchzoom":"scrollzoom")}}};m.registerBinding(m.container,"wheel",Je,!0),m.registerBinding(window,"scroll",function(We){m.scrollingPage=!0,clearTimeout(m.scrollingPageTimeout),m.scrollingPageTimeout=setTimeout(function(){m.scrollingPage=!1},250)},!0),m.registerBinding(m.container,"gesturestart",function(We){m.gestureStartZoom=m.cy.zoom(),m.hasTouchStarted||We.preventDefault()},!0),m.registerBinding(m.container,"gesturechange",function(Ar){m.hasTouchStarted||Je(Ar)},!0),m.registerBinding(m.container,"mouseout",function(We){var On=m.projectIntoViewport(We.clientX,We.clientY);m.cy.emit({originalEvent:We,type:"mouseout",position:{x:On[0],y:On[1]}})},!1),m.registerBinding(m.container,"mouseover",function(We){var On=m.projectIntoViewport(We.clientX,We.clientY);m.cy.emit({originalEvent:We,type:"mouseover",position:{x:On[0],y:On[1]}})},!1);var Ct,lt,un,Rt,$t,bn,Cn,Kn,kn,Wn,sr,yr,hr,nr=function(We,On,Ir,ar){return Math.sqrt((Ir-We)*(Ir-We)+(ar-On)*(ar-On))},fn=function(We,On,Ir,ar){return(Ir-We)*(Ir-We)+(ar-On)*(ar-On)},vr;m.registerBinding(m.container,"touchstart",vr=function(We){if(m.hasTouchStarted=!0,!!Ze(We)){be(),m.touchData.capture=!0,m.data.bgActivePosistion=void 0;var On=m.cy,Ir=m.touchData.now,ar=m.touchData.earlier;if(We.touches[0]){var or=m.projectIntoViewport(We.touches[0].clientX,We.touches[0].clientY);Ir[0]=or[0],Ir[1]=or[1]}if(We.touches[1]){var or=m.projectIntoViewport(We.touches[1].clientX,We.touches[1].clientY);Ir[2]=or[0],Ir[3]=or[1]}if(We.touches[2]){var or=m.projectIntoViewport(We.touches[2].clientX,We.touches[2].clientY);Ir[4]=or[0],Ir[5]=or[1]}if(We.touches[1]){m.touchData.singleTouchMoved=!0,ue(m.dragData.touchDragEles);var qa=m.findContainerClientCoords();kn=qa[0],Wn=qa[1],sr=qa[2],yr=qa[3],Ct=We.touches[0].clientX-kn,lt=We.touches[0].clientY-Wn,un=We.touches[1].clientX-kn,Rt=We.touches[1].clientY-Wn,hr=0<=Ct&&Ct<=sr&&0<=un&&un<=sr&&0<=lt&<<=yr&&0<=Rt&&Rt<=yr;var qr=On.pan(),is=On.zoom();$t=nr(Ct,lt,un,Rt),bn=fn(Ct,lt,un,Rt),Cn=[(Ct+un)/2,(lt+Rt)/2],Kn=[(Cn[0]-qr.x)/is,(Cn[1]-qr.y)/is];var Uo=200,qc=Uo*Uo;if(bn=1){for(var yp=m.touchData.startPosition=[],Xf=0;Xf=m.touchTapThreshold2}if(On&&m.touchData.cxt){We.preventDefault();var yp=We.touches[0].clientX-kn,Xf=We.touches[0].clientY-Wn,gg=We.touches[1].clientX-kn,fd=We.touches[1].clientY-Wn,ov=fn(yp,Xf,gg,fd),mm=ov/bn,l6=150,S3=l6*l6,h6=1.5,gT=h6*h6;if(mm>=gT||ov>=S3){m.touchData.cxt=!1,m.data.bgActivePosistion=void 0,m.redrawHint("select",!0);var A3={originalEvent:We,type:"cxttapend",position:{x:or[0],y:or[1]}};m.touchData.start?(m.touchData.start.unactivate().emit(A3),m.touchData.start=null):ar.emit(A3)}}if(On&&m.touchData.cxt){var A3={originalEvent:We,type:"cxtdrag",position:{x:or[0],y:or[1]}};m.data.bgActivePosistion=void 0,m.redrawHint("select",!0),m.touchData.start?m.touchData.start.emit(A3):ar.emit(A3),m.touchData.start&&(m.touchData.start._private.grabbed=!1),m.touchData.cxtDragged=!0;var qd=m.findNearestElement(or[0],or[1],!0,!0);(!m.touchData.cxtOver||qd!==m.touchData.cxtOver)&&(m.touchData.cxtOver&&m.touchData.cxtOver.emit({originalEvent:We,type:"cxtdragout",position:{x:or[0],y:or[1]}}),m.touchData.cxtOver=qd,qd&&qd.emit({originalEvent:We,type:"cxtdragover",position:{x:or[0],y:or[1]}}))}else if(On&&We.touches[2]&&ar.boxSelectionEnabled())We.preventDefault(),m.data.bgActivePosistion=void 0,this.lastThreeTouch=+new Date,m.touchData.selecting||ar.emit({originalEvent:We,type:"boxstart",position:{x:or[0],y:or[1]}}),m.touchData.selecting=!0,m.touchData.didSelect=!0,Ir[4]=1,!Ir||Ir.length===0||Ir[0]===void 0?(Ir[0]=(or[0]+or[2]+or[4])/3,Ir[1]=(or[1]+or[3]+or[5])/3,Ir[2]=(or[0]+or[2]+or[4])/3+1,Ir[3]=(or[1]+or[3]+or[5])/3+1):(Ir[2]=(or[0]+or[2]+or[4])/3,Ir[3]=(or[1]+or[3]+or[5])/3),m.redrawHint("select",!0),m.redraw();else if(On&&We.touches[1]&&!m.touchData.didSelect&&ar.zoomingEnabled()&&ar.panningEnabled()&&ar.userZoomingEnabled()&&ar.userPanningEnabled()){We.preventDefault(),m.data.bgActivePosistion=void 0,m.redrawHint("select",!0);var _1=m.dragData.touchDragEles;if(_1){m.redrawHint("drag",!0);for(var Vd=0;Vd<_1.length;Vd++){var pT=_1[Vd]._private;pT.grabbed=!1,pT.rscratch.inDragLayer=!1}}var $2=m.touchData.start,yp=We.touches[0].clientX-kn,Xf=We.touches[0].clientY-Wn,gg=We.touches[1].clientX-kn,fd=We.touches[1].clientY-Wn,QR=nr(yp,Xf,gg,fd),Dee=QR/$t;if(hr){var Iee=yp-Ct,Oee=Xf-lt,Nee=gg-un,Pee=fd-Rt,Bee=(Iee+Nee)/2,Ree=(Oee+Pee)/2,Gx=ar.zoom(),iM=Gx*Dee,bT=ar.pan(),ZR=Kn[0]*Gx+bT.x,JR=Kn[1]*Gx+bT.y,Fee={x:-iM/Gx*(ZR-bT.x-Bee)+ZR,y:-iM/Gx*(JR-bT.y-Ree)+JR};if($2&&$2.active()){var _1=m.dragData.touchDragEles;ue(_1),m.redrawHint("drag",!0),m.redrawHint("eles",!0),$2.unactivate().emit("freeon"),_1.emit("free"),m.dragData.didDrag&&($2.emit("dragfreeon"),_1.emit("dragfree"))}ar.viewport({zoom:iM,pan:Fee,cancelOnFailedZoom:!0}),ar.emit("pinchzoom"),$t=QR,Ct=yp,lt=Xf,un=gg,Rt=fd,m.pinching=!0}if(We.touches[0]){var is=m.projectIntoViewport(We.touches[0].clientX,We.touches[0].clientY);or[0]=is[0],or[1]=is[1]}if(We.touches[1]){var is=m.projectIntoViewport(We.touches[1].clientX,We.touches[1].clientY);or[2]=is[0],or[3]=is[1]}if(We.touches[2]){var is=m.projectIntoViewport(We.touches[2].clientX,We.touches[2].clientY);or[4]=is[0],or[5]=is[1]}}else if(We.touches[0]&&!m.touchData.didSelect){var kp=m.touchData.start,sM=m.touchData.last,qd;if(!m.hoverData.draggingEles&&!m.swipePanning&&(qd=m.findNearestElement(or[0],or[1],!0,!0)),On&&kp!=null&&We.preventDefault(),On&&kp!=null&&m.nodeIsDraggable(kp))if(qc){var 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Vd=0;Vd0&&!m.hoverData.draggingEles&&!m.swipePanning&&m.data.bgActivePosistion!=null&&(m.data.bgActivePosistion=void 0,m.redrawHint("select",!0),m.redraw())}},!1);var ni;m.registerBinding(window,"touchcancel",ni=function(We){var On=m.touchData.start;m.touchData.capture=!1,On&&On.unactivate()});var Ti,ia,Ba,Li;if(m.registerBinding(window,"touchend",Ti=function(We){var On=m.touchData.start,Ir=m.touchData.capture;if(Ir)We.touches.length===0&&(m.touchData.capture=!1),We.preventDefault();else return;var ar=m.selection;m.swipePanning=!1,m.hoverData.draggingEles=!1;var or=m.cy,qa=or.zoom(),qr=m.touchData.now,is=m.touchData.earlier;if(We.touches[0]){var Uo=m.projectIntoViewport(We.touches[0].clientX,We.touches[0].clientY);qr[0]=Uo[0],qr[1]=Uo[1]}if(We.touches[1]){var Uo=m.projectIntoViewport(We.touches[1].clientX,We.touches[1].clientY);qr[2]=Uo[0],qr[3]=Uo[1]}if(We.touches[2]){var Uo=m.projectIntoViewport(We.touches[2].clientX,We.touches[2].clientY);qr[4]=Uo[0],qr[5]=Uo[1]}On&&On.unactivate();var qc;if(m.touchData.cxt){if(qc={originalEvent:We,type:"cxttapend",position:{x:qr[0],y:qr[1]}},On?On.emit(qc):or.emit(qc),!m.touchData.cxtDragged){var uo={originalEvent:We,type:"cxttap",position:{x:qr[0],y:qr[1]}};On?On.emit(uo):or.emit(uo)}m.touchData.start&&(m.touchData.start._private.grabbed=!1),m.touchData.cxt=!1,m.touchData.start=null,m.redraw();return}if(!We.touches[2]&&or.boxSelectionEnabled()&&m.touchData.selecting){m.touchData.selecting=!1;var Lc=or.collection(m.getAllInBox(ar[0],ar[1],ar[2],ar[3]));ar[0]=void 0,ar[1]=void 0,ar[2]=void 0,ar[3]=void 0,ar[4]=0,m.redrawHint("select",!0),or.emit({type:"boxend",originalEvent:We,position:{x:qr[0],y:qr[1]}});var Ra=function(S3){return S3.selectable()&&!S3.selected()};Lc.emit("box").stdFilter(Ra).select().emit("boxselect"),Lc.nonempty()&&m.redrawHint("eles",!0),m.redraw()}if(On!=null&&On.unactivate(),We.touches[2])m.data.bgActivePosistion=void 0,m.redrawHint("select",!0);else if(!We.touches[1]){if(!We.touches[0]){if(!We.touches[0]){m.data.bgActivePosistion=void 0,m.redrawHint("select",!0);var lo=m.dragData.touchDragEles;if(On!=null){var Sl=On._private.grabbed;ue(lo),m.redrawHint("drag",!0),m.redrawHint("eles",!0),Sl&&(On.emit("freeon"),lo.emit("free"),m.dragData.didDrag&&(On.emit("dragfreeon"),lo.emit("dragfree"))),k(On,["touchend","tapend","vmouseup","tapdragout"],We,{x:qr[0],y:qr[1]}),On.unactivate(),m.touchData.start=null}else{var Yf=m.findNearestElement(qr[0],qr[1],!0,!0);k(Yf,["touchend","tapend","vmouseup","tapdragout"],We,{x:qr[0],y:qr[1]})}var mp=m.touchData.startPosition[0]-qr[0],yp=mp*mp,Xf=m.touchData.startPosition[1]-qr[1],gg=Xf*Xf,fd=yp+gg,ov=fd*qa*qa;m.touchData.singleTouchMoved||(On||or.$(":selected").unselect(["tapunselect"]),k(On,["tap","vclick"],We,{x:qr[0],y:qr[1]}),ia=!1,We.timeStamp-Li<=or.multiClickDebounceTime()?(Ba&&clearTimeout(Ba),ia=!0,Li=null,k(On,["dbltap","vdblclick"],We,{x:qr[0],y:qr[1]})):(Ba=setTimeout(function(){ia||k(On,["onetap","voneclick"],We,{x:qr[0],y:qr[1]})},or.multiClickDebounceTime()),Li=We.timeStamp)),On!=null&&!m.dragData.didDrag&&On._private.selectable&&ov"u"){var wi=[],Ts=function(We){return{clientX:We.clientX,clientY:We.clientY,force:1,identifier:We.pointerId,pageX:We.pageX,pageY:We.pageY,radiusX:We.width/2,radiusY:We.height/2,screenX:We.screenX,screenY:We.screenY,target:We.target}},Yi=function(We){return{event:We,touch:Ts(We)}},Di=function(We){wi.push(Yi(We))},es=function(We){for(var On=0;On0)return kn[0]}return null},ne=Object.keys(U),ae=0;ae0?Z:XP(D,I,g,k,T,A,F)},checkPoint:function(g,k,T,A,D,I,F){var H=wx(A,D),C=2*H;if(tv(g,k,this.points,I,F,A,D-C,[0,-1],T)||tv(g,k,this.points,I,F,A-C,D,[0,-1],T))return!0;var G=A/2+2*T,U=D/2+2*T,Z=[I-G,F-U,I-G,F,I+G,F,I+G,F-U];return!!(Gd(g,k,Z)||m3(g,k,C,C,I+A/2-H,F+D/2-H,T)||m3(g,k,C,C,I-A/2+H,F+D/2-H,T))}}},iv.registerNodeShapes=function(){var m=this.nodeShapes={},g=this;this.generateEllipse(),this.generatePolygon("triangle",ud(3,0)),this.generateRoundPolygon("round-triangle",ud(3,0)),this.generatePolygon("rectangle",ud(4,0)),m.square=m.rectangle,this.generateRoundRectangle(),this.generateCutRectangle(),this.generateBarrel(),this.generateBottomRoundrectangle();{var k=[0,1,1,0,0,-1,-1,0];this.generatePolygon("diamond",k),this.generateRoundPolygon("round-diamond",k)}this.generatePolygon("pentagon",ud(5,0)),this.generateRoundPolygon("round-pentagon",ud(5,0)),this.generatePolygon("hexagon",ud(6,0)),this.generateRoundPolygon("round-hexagon",ud(6,0)),this.generatePolygon("heptagon",ud(7,0)),this.generateRoundPolygon("round-heptagon",ud(7,0)),this.generatePolygon("octagon",ud(8,0)),this.generateRoundPolygon("round-octagon",ud(8,0));var T=new Array(20);{var A=TL(5,0),D=TL(5,Math.PI/5),I=.5*(3-Math.sqrt(5));I*=1.57;for(var F=0;F=g.deqFastCost*Be)break}else if(C){if(Se>=g.deqCost*ne||Se>=g.deqAvgCost*Z)break}else if(Le>=g.deqNoDrawCost*QL)break;var Ke=g.deq(T,_e,ue);if(Ke.length>0)for(var qe=0;qe0&&(g.onDeqd(T,ae),!C&&g.shouldRedraw(T,ae,_e,ue)&&D())},F=g.priority||om;A.beforeRender(I,F(T))}}}},tee=function(){function m(g){var k=arguments.length>1&&arguments[1]!==void 0?arguments[1]:am;p(this,m),this.idsByKey=new R2,this.keyForId=new R2,this.cachesByLvl=new R2,this.lvls=[],this.getKey=g,this.doesEleInvalidateKey=k}return y(m,[{key:"getIdsFor",value:function(k){k==null&&yc("Can not get id list for null key");var T=this.idsByKey,A=this.idsByKey.get(k);return A||(A=new R5,T.set(k,A)),A}},{key:"addIdForKey",value:function(k,T){k!=null&&this.getIdsFor(k).add(T)}},{key:"deleteIdForKey",value:function(k,T){k!=null&&this.getIdsFor(k).delete(T)}},{key:"getNumberOfIdsForKey",value:function(k){return k==null?0:this.getIdsFor(k).size}},{key:"updateKeyMappingFor",value:function(k){var T=k.id(),A=this.keyForId.get(T),D=this.getKey(k);this.deleteIdForKey(A,T),this.addIdForKey(D,T),this.keyForId.set(T,D)}},{key:"deleteKeyMappingFor",value:function(k){var T=k.id(),A=this.keyForId.get(T);this.deleteIdForKey(A,T),this.keyForId.delete(T)}},{key:"keyHasChangedFor",value:function(k){var T=k.id(),A=this.keyForId.get(T),D=this.getKey(k);return A!==D}},{key:"isInvalid",value:function(k){return this.keyHasChangedFor(k)||this.doesEleInvalidateKey(k)}},{key:"getCachesAt",value:function(k){var T=this.cachesByLvl,A=this.lvls,D=T.get(k);return D||(D=new R2,T.set(k,D),A.push(k)),D}},{key:"getCache",value:function(k,T){return this.getCachesAt(T).get(k)}},{key:"get",value:function(k,T){var A=this.getKey(k),D=this.getCache(A,T);return D!=null&&this.updateKeyMappingFor(k),D}},{key:"getForCachedKey",value:function(k,T){var A=this.keyForId.get(k.id()),D=this.getCache(A,T);return D}},{key:"hasCache",value:function(k,T){return this.getCachesAt(T).has(k)}},{key:"has",value:function(k,T){var A=this.getKey(k);return this.hasCache(A,T)}},{key:"setCache",value:function(k,T,A){A.key=k,this.getCachesAt(T).set(k,A)}},{key:"set",value:function(k,T,A){var D=this.getKey(k);this.setCache(D,T,A),this.updateKeyMappingFor(k)}},{key:"deleteCache",value:function(k,T){this.getCachesAt(T).delete(k)}},{key:"delete",value:function(k,T){var A=this.getKey(k);this.deleteCache(A,T)}},{key:"invalidateKey",value:function(k){var T=this;this.lvls.forEach(function(A){return T.deleteCache(k,A)})}},{key:"invalidate",value:function(k){var T=k.id(),A=this.keyForId.get(T);this.deleteKeyMappingFor(k);var D=this.doesEleInvalidateKey(k);return D&&this.invalidateKey(A),D||this.getNumberOfIdsForKey(A)===0}}]),m}(),cT=25,uT=50,i6=-4,ZL=3,JL=7.99,nee=8,ree=1024,iee=1024,HR=1024,see=.2,aee=.8,oee=10,cee=.15,uee=.1,lee=.9,hee=.9,fee=100,dee=1,s6={dequeue:"dequeue",downscale:"downscale",highQuality:"highQuality"},gee=Vf({getKey:null,doesEleInvalidateKey:am,drawElement:null,getBoundingBox:null,getRotationPoint:null,getRotationOffset:null,isVisible:cd,allowEdgeTxrCaching:!0,allowParentTxrCaching:!0}),Fx=function(g,k){var T=this;T.renderer=g,T.onDequeues=[];var A=gee(k);Oe(T,A),T.lookup=new tee(A.getKey,A.doesEleInvalidateKey),T.setupDequeueing()},Oh=Fx.prototype;Oh.reasons=s6,Oh.getTextureQueue=function(m){var g=this;return g.eleImgCaches=g.eleImgCaches||{},g.eleImgCaches[m]=g.eleImgCaches[m]||[]},Oh.getRetiredTextureQueue=function(m){var g=this,k=g.eleImgCaches.retired=g.eleImgCaches.retired||{},T=k[m]=k[m]||[];return T},Oh.getElementQueue=function(){var m=this,g=m.eleCacheQueue=m.eleCacheQueue||new gx(function(k,T){return T.reqs-k.reqs});return g},Oh.getElementKeyToQueue=function(){var m=this,g=m.eleKeyToCacheQueue=m.eleKeyToCacheQueue||{};return g},Oh.getElement=function(m,g,k,T,A){var D=this,I=this.renderer,F=I.cy.zoom(),H=this.lookup;if(!g||g.w===0||g.h===0||isNaN(g.w)||isNaN(g.h)||!m.visible()||m.removed()||!D.allowEdgeTxrCaching&&m.isEdge()||!D.allowParentTxrCaching&&m.isParent())return null;if(T==null&&(T=Math.ceil(yL(F*k))),T=JL||T>ZL)return null;var C=Math.pow(2,T),G=g.h*C,U=g.w*C,Z=I.eleTextBiggerThanMin(m,C);if(!this.isVisible(m,Z))return null;var ne=H.get(m,T);if(ne&&ne.invalidated&&(ne.invalidated=!1,ne.texture.invalidatedWidth-=ne.width),ne)return ne;var ae;if(G<=cT?ae=cT:G<=uT?ae=uT:ae=Math.ceil(G/uT)*uT,G>HR||U>iee)return null;var ue=D.getTextureQueue(ae),_e=ue[ue.length-2],be=function(){return D.recycleTexture(ae,U)||D.addTexture(ae,U)};_e||(_e=ue[ue.length-1]),_e||(_e=be()),_e.width-_e.usedWidthT;ut--)$e=D.getElement(m,g,k,ut,s6.downscale);ot()}else return D.queueElement(m,qe.level-1),qe;else{var Je;if(!Le&&!Be&&!Ke)for(var Ct=T-1;Ct>=i6;Ct--){var lt=H.get(m,Ct);if(lt){Je=lt;break}}if(Se(Je))return D.queueElement(m,T),Je;_e.context.translate(_e.usedWidth,0),_e.context.scale(C,C),this.drawElement(_e.context,m,g,Z,!1),_e.context.scale(1/C,1/C),_e.context.translate(-_e.usedWidth,0)}return ne={x:_e.usedWidth,texture:_e,level:T,scale:C,width:U,height:G,scaledLabelShown:Z},_e.usedWidth+=Math.ceil(U+nee),_e.eleCaches.push(ne),H.set(m,T,ne),D.checkTextureFullness(_e),ne},Oh.invalidateElements=function(m){for(var g=0;g=see*m.width&&this.retireTexture(m)},Oh.checkTextureFullness=function(m){var g=this,k=g.getTextureQueue(m.height);m.usedWidth/m.width>aee&&m.fullnessChecks>=oee?cm(k,m):m.fullnessChecks++},Oh.retireTexture=function(m){var g=this,k=m.height,T=g.getTextureQueue(k),A=this.lookup;cm(T,m),m.retired=!0;for(var D=m.eleCaches,I=0;I=g)return I.retired=!1,I.usedWidth=0,I.invalidatedWidth=0,I.fullnessChecks=0,wL(I.eleCaches),I.context.setTransform(1,0,0,1,0,0),I.context.clearRect(0,0,I.width,I.height),cm(A,I),T.push(I),I}},Oh.queueElement=function(m,g){var k=this,T=k.getElementQueue(),A=k.getElementKeyToQueue(),D=this.getKey(m),I=A[D];if(I)I.level=Math.max(I.level,g),I.eles.merge(m),I.reqs++,T.updateItem(I);else{var F={eles:m.spawn().merge(m),level:g,reqs:1,key:D};T.push(F),A[D]=F}},Oh.dequeue=function(m){for(var g=this,k=g.getElementQueue(),T=g.getElementKeyToQueue(),A=[],D=g.lookup,I=0;I0;I++){var F=k.pop(),H=F.key,C=F.eles[0],G=D.hasCache(C,F.level);if(T[H]=null,G)continue;A.push(F);var U=g.getBoundingBox(C);g.getElement(C,U,m,F.level,s6.dequeue)}return A},Oh.removeFromQueue=function(m){var g=this,k=g.getElementQueue(),T=g.getElementKeyToQueue(),A=this.getKey(m),D=T[A];D!=null&&(D.eles.length===1?(D.reqs=dp,k.updateItem(D),k.pop(),T[A]=null):D.eles.unmerge(m))},Oh.onDequeue=function(m){this.onDequeues.push(m)},Oh.offDequeue=function(m){cm(this.onDequeues,m)},Oh.setupDequeueing=oT.setupDequeueing({deqRedrawThreshold:fee,deqCost:cee,deqAvgCost:uee,deqNoDrawCost:lee,deqFastCost:hee,deq:function(g,k,T){return g.dequeue(k,T)},onDeqd:function(g,k){for(var T=0;T=lT||k>jx)return null}T.validateLayersElesOrdering(k,m);var H=T.layersByLevel,C=Math.pow(2,k),G=H[k]=H[k]||[],U,Z=T.levelIsComplete(k,m),ne,ae=function(){var ot=function(un){if(T.validateLayersElesOrdering(un,m),T.levelIsComplete(un,m))return ne=H[un],!0},ut=function(un){if(!ne)for(var Rt=k+un;a6<=Rt&&Rt<=jx&&!ot(Rt);Rt+=un);};ut(1),ut(-1);for(var Je=G.length-1;Je>=0;Je--){var Ct=G[Je];Ct.invalid&&cm(G,Ct)}};if(!Z)ae();else return G;var ue=function(){if(!U){U=zd();for(var ot=0;otGge)return null;var Ct=T.makeLayer(U,k);if(ut!=null){var lt=G.indexOf(ut)+1;G.splice(lt,0,Ct)}else(ot.insert===void 0||ot.insert)&&G.unshift(Ct);return Ct};if(T.skipping&&!F)return null;for(var be=null,Se=m.length/pee,Le=!F,Be=0;Be=Se||!YP(be.bb,Ke.boundingBox()))&&(be=_e({insert:!0,after:be}),!be))return null;ne||Le?T.queueLayer(be,Ke):T.drawEleInLayer(be,Ke,k,g),be.eles.push(Ke),Re[k]=be}return ne||(Le?null:G)},x1.getEleLevelForLayerLevel=function(m,g){return m},x1.drawEleInLayer=function(m,g,k,T){var A=this,D=this.renderer,I=m.context,F=g.boundingBox();F.w===0||F.h===0||!g.visible()||(k=A.getEleLevelForLayerLevel(k,T),D.setImgSmoothing(I,!1),D.drawCachedElement(I,g,null,null,k,qge),D.setImgSmoothing(I,!0))},x1.levelIsComplete=function(m,g){var k=this,T=k.layersByLevel[m];if(!T||T.length===0)return!1;for(var A=0,D=0;D0||I.invalid)return!1;A+=I.eles.length}return A===g.length},x1.validateLayersElesOrdering=function(m,g){var k=this.layersByLevel[m];if(k)for(var T=0;T0){g=!0;break}}return g},x1.invalidateElements=function(m){var g=this;m.length!==0&&(g.lastInvalidationTime=pi(),!(m.length===0||!g.haveLayers())&&g.updateElementsInLayers(m,function(T,A,D){g.invalidateLayer(T)}))},x1.invalidateLayer=function(m){if(this.lastInvalidationTime=pi(),!m.invalid){var g=m.level,k=m.eles,T=this.layersByLevel[g];cm(T,m),m.elesQueue=[],m.invalid=!0,m.replacement&&(m.replacement.invalid=!0);for(var A=0;A3&&arguments[3]!==void 0?arguments[3]:!0,A=arguments.length>4&&arguments[4]!==void 0?arguments[4]:!0,D=arguments.length>5&&arguments[5]!==void 0?arguments[5]:!0,I=this,F=g._private.rscratch;if(!(D&&!g.visible())&&!(F.badLine||F.allpts==null||isNaN(F.allpts[0]))){var H;k&&(H=k,m.translate(-H.x1,-H.y1));var C=D?g.pstyle("opacity").value:1,G=D?g.pstyle("line-opacity").value:1,U=g.pstyle("curve-style").value,Z=g.pstyle("line-style").value,ne=g.pstyle("width").pfValue,ae=g.pstyle("line-cap").value,ue=C*G,_e=C*G,be=function(){var 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N!=0&&(S=this.lworldOrgX+(E-this.ldeviceOrgX)*this.lworldExtX/N),S},b.prototype.inverseTransformY=function(E){var S=0,N=this.ldeviceExtY;return N!=0&&(S=this.lworldOrgY+(E-this.ldeviceOrgY)*this.lworldExtY/N),S},b.prototype.inverseTransformPoint=function(E){var S=new y(this.inverseTransformX(E.x),this.inverseTransformY(E.y));return S},f.exports=b},function(f,p,w){function y($){if(Array.isArray($)){for(var V=0,Q=Array($.length);V<$.length;V++)Q[V]=$[V];return Q}else return Array.from($)}var b=w(15),E=w(7),S=w(0),N=w(8),B=w(9);function R(){b.call(this),this.useSmartIdealEdgeLengthCalculation=E.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.idealEdgeLength=E.DEFAULT_EDGE_LENGTH,this.springConstant=E.DEFAULT_SPRING_STRENGTH,this.repulsionConstant=E.DEFAULT_REPULSION_STRENGTH,this.gravityConstant=E.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=E.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=E.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=E.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.displacementThresholdPerNode=3*E.DEFAULT_EDGE_LENGTH/100,this.coolingFactor=E.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.initialCoolingFactor=E.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.totalDisplacement=0,this.oldTotalDisplacement=0,this.maxIterations=E.MAX_ITERATIONS}R.prototype=Object.create(b.prototype);for(var j in b)R[j]=b[j];R.prototype.initParameters=function(){b.prototype.initParameters.call(this,arguments),this.totalIterations=0,this.notAnimatedIterations=0,this.useFRGridVariant=E.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION,this.grid=[]},R.prototype.calcIdealEdgeLengths=function(){for(var $,V,Q,oe,ce,se,ge=this.getGraphManager().getAllEdges(),ye=0;yeE.ADAPTATION_LOWER_NODE_LIMIT&&(this.coolingFactor=Math.max(this.coolingFactor*E.COOLING_ADAPTATION_FACTOR,this.coolingFactor-($-E.ADAPTATION_LOWER_NODE_LIMIT)/(E.ADAPTATION_UPPER_NODE_LIMIT-E.ADAPTATION_LOWER_NODE_LIMIT)*this.coolingFactor*(1-E.COOLING_ADAPTATION_FACTOR))),this.maxNodeDisplacement=E.MAX_NODE_DISPLACEMENT_INCREMENTAL):($>E.ADAPTATION_LOWER_NODE_LIMIT?this.coolingFactor=Math.max(E.COOLING_ADAPTATION_FACTOR,1-($-E.ADAPTATION_LOWER_NODE_LIMIT)/(E.ADAPTATION_UPPER_NODE_LIMIT-E.ADAPTATION_LOWER_NODE_LIMIT)*(1-E.COOLING_ADAPTATION_FACTOR)):this.coolingFactor=1,this.initialCoolingFactor=this.coolingFactor,this.maxNodeDisplacement=E.MAX_NODE_DISPLACEMENT),this.maxIterations=Math.max(this.getAllNodes().length*5,this.maxIterations),this.totalDisplacementThreshold=this.displacementThresholdPerNode*this.getAllNodes().length,this.repulsionRange=this.calcRepulsionRange()},R.prototype.calcSpringForces=function(){for(var $=this.getAllEdges(),V,Q=0;Q<$.length;Q++)V=$[Q],this.calcSpringForce(V,V.idealLength)},R.prototype.calcRepulsionForces=function(){var $=arguments.length>0&&arguments[0]!==void 0?arguments[0]:!0,V=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1,Q,oe,ce,se,ge=this.getAllNodes(),ye;if(this.useFRGridVariant)for(this.totalIterations%E.GRID_CALCULATION_CHECK_PERIOD==1&&$&&this.updateGrid(),ye=new Set,Q=0;Qke||ye>ke)&&($.gravitationForceX=-this.gravityConstant*ce,$.gravitationForceY=-this.gravityConstant*se)):(ke=V.getEstimatedSize()*this.compoundGravityRangeFactor,(ge>ke||ye>ke)&&($.gravitationForceX=-this.gravityConstant*ce*this.compoundGravityConstant,$.gravitationForceY=-this.gravityConstant*se*this.compoundGravityConstant))},R.prototype.isConverged=function(){var $,V=!1;return this.totalIterations>this.maxIterations/3&&(V=Math.abs(this.totalDisplacement-this.oldTotalDisplacement)<2),$=this.totalDisplacement=ge.length||ke>=ge[0].length)){for(var Ae=0;AeR}}]),N}();f.exports=S},function(f,p,w){var y=function(){function S(N,B){for(var R=0;R2&&arguments[2]!==void 0?arguments[2]:1,j=arguments.length>3&&arguments[3]!==void 0?arguments[3]:-1,$=arguments.length>4&&arguments[4]!==void 0?arguments[4]:-1;b(this,S),this.sequence1=N,this.sequence2=B,this.match_score=R,this.mismatch_penalty=j,this.gap_penalty=$,this.iMax=N.length+1,this.jMax=B.length+1,this.grid=new Array(this.iMax);for(var V=0;V=0;N--){var B=this.listeners[N];B.event===E&&B.callback===S&&this.listeners.splice(N,1)}},b.emit=function(E,S){for(var N=0;NB.coolingFactor*B.maxNodeDisplacement&&(this.displacementX=B.coolingFactor*B.maxNodeDisplacement*E.sign(this.displacementX)),Math.abs(this.displacementY)>B.coolingFactor*B.maxNodeDisplacement&&(this.displacementY=B.coolingFactor*B.maxNodeDisplacement*E.sign(this.displacementY)),this.child==null?this.moveBy(this.displacementX,this.displacementY):this.child.getNodes().length==0?this.moveBy(this.displacementX,this.displacementY):this.propogateDisplacementToChildren(this.displacementX,this.displacementY),B.totalDisplacement+=Math.abs(this.displacementX)+Math.abs(this.displacementY),this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0},S.prototype.propogateDisplacementToChildren=function(B,R){for(var j=this.getChild().getNodes(),$,V=0;V0)this.positionNodesRadially(de);else{this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var ve=new Set(this.getAllNodes()),te=this.nodesWithGravity.filter(function(xe){return ve.has(xe)});this.graphManager.setAllNodesToApplyGravitation(te),this.positionNodesRandomly()}}return this.initSpringEmbedder(),this.runSpringEmbedder(),!0},ke.prototype.tick=function(){if(this.totalIterations++,this.totalIterations===this.maxIterations&&!this.isTreeGrowing&&!this.isGrowthFinished)if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;if(this.totalIterations%j.CONVERGENCE_CHECK_PERIOD==0&&!this.isTreeGrowing&&!this.isGrowthFinished){if(this.isConverged())if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;this.coolingCycle++,this.layoutQuality==0?this.coolingAdjuster=this.coolingCycle:this.layoutQuality==1&&(this.coolingAdjuster=this.coolingCycle/3),this.coolingFactor=Math.max(this.initialCoolingFactor-Math.pow(this.coolingCycle,Math.log(100*(this.initialCoolingFactor-this.finalTemperature))/Math.log(this.maxCoolingCycle))/100*this.coolingAdjuster,this.finalTemperature),this.animationPeriod=Math.ceil(this.initialAnimationPeriod*Math.sqrt(this.coolingFactor))}if(this.isTreeGrowing){if(this.growTreeIterations%10==0)if(this.prunedNodesAll.length>0){this.graphManager.updateBounds(),this.updateGrid(),this.growTree(this.prunedNodesAll),this.graphManager.resetAllNodesToApplyGravitation();var de=new Set(this.getAllNodes()),ve=this.nodesWithGravity.filter(function(De){return de.has(De)});this.graphManager.setAllNodesToApplyGravitation(ve),this.graphManager.updateBounds(),this.updateGrid(),this.coolingFactor=j.DEFAULT_COOLING_FACTOR_INCREMENTAL}else this.isTreeGrowing=!1,this.isGrowthFinished=!0;this.growTreeIterations++}if(this.isGrowthFinished){if(this.isConverged())return!0;this.afterGrowthIterations%10==0&&(this.graphManager.updateBounds(),this.updateGrid()),this.coolingFactor=j.DEFAULT_COOLING_FACTOR_INCREMENTAL*((100-this.afterGrowthIterations)/100),this.afterGrowthIterations++}var te=!this.isTreeGrowing&&!this.isGrowthFinished,xe=this.growTreeIterations%10==1&&this.isTreeGrowing||this.afterGrowthIterations%10==1&&this.isGrowthFinished;return this.totalDisplacement=0,this.graphManager.updateBounds(),this.calcSpringForces(),this.calcRepulsionForces(te,xe),this.calcGravitationalForces(),this.moveNodes(),this.animate(),!1},ke.prototype.getPositionsData=function(){for(var de=this.graphManager.getAllNodes(),ve={},te=0;te1){var ee;for(ee=0;eexe&&(xe=Math.floor(Ie.y)),he=Math.floor(Ie.x+R.DEFAULT_COMPONENT_SEPERATION)}this.transform(new Q($.WORLD_CENTER_X-Ie.x/2,$.WORLD_CENTER_Y-Ie.y/2))},ke.radialLayout=function(de,ve,te){var xe=Math.max(this.maxDiagonalInTree(de),R.DEFAULT_RADIAL_SEPARATION);ke.branchRadialLayout(ve,null,0,359,0,xe);var De=ge.calculateBounds(de),he=new ye;he.setDeviceOrgX(De.getMinX()),he.setDeviceOrgY(De.getMinY()),he.setWorldOrgX(te.x),he.setWorldOrgY(te.y);for(var Ie=0;Ie1;){var cn=Bt[0];Bt.splice(0,1);var Nn=pe.indexOf(cn);Nn>=0&&pe.splice(Nn,1),jt--,Et--}ve!=null?At=(pe.indexOf(Bt[0])+1)%jt:At=0;for(var Ot=Math.abs(xe-te)/Et,oi=At;wt!=Et;oi=++oi%jt){var kt=pe[oi].getOtherEnd(de);if(kt!=ve){var Dt=(te+wt*Ot)%360,vt=(Dt+Ot)%360;ke.branchRadialLayout(kt,de,Dt,vt,De+he,he),wt++}}},ke.maxDiagonalInTree=function(de){for(var ve=ce.MIN_VALUE,te=0;teve&&(ve=De)}return ve},ke.prototype.calcRepulsionRange=function(){return 2*(this.level+1)*this.idealEdgeLength},ke.prototype.groupZeroDegreeMembers=function(){var de=this,ve={};this.memberGroups={},this.idToDummyNode={};for(var te=[],xe=this.graphManager.getAllNodes(),De=0;De"u"&&(ve[ee]=[]),ve[ee]=ve[ee].concat(he)}Object.keys(ve).forEach(function(rt){if(ve[rt].length>1){var me="DummyCompound_"+rt;de.memberGroups[me]=ve[rt];var gt=ve[rt][0].getParent(),pe=new N(de.graphManager);pe.id=me,pe.paddingLeft=gt.paddingLeft||0,pe.paddingRight=gt.paddingRight||0,pe.paddingBottom=gt.paddingBottom||0,pe.paddingTop=gt.paddingTop||0,de.idToDummyNode[me]=pe;var Et=de.getGraphManager().add(de.newGraph(),pe),wt=gt.getChild();wt.add(pe);for(var jt=0;jt=0;de--){var ve=this.compoundOrder[de],te=ve.id,xe=ve.paddingLeft,De=ve.paddingTop;this.adjustLocations(this.tiledMemberPack[te],ve.rect.x,ve.rect.y,xe,De)}},ke.prototype.repopulateZeroDegreeMembers=function(){var de=this,ve=this.tiledZeroDegreePack;Object.keys(ve).forEach(function(te){var xe=de.idToDummyNode[te],De=xe.paddingLeft,he=xe.paddingTop;de.adjustLocations(ve[te],xe.rect.x,xe.rect.y,De,he)})},ke.prototype.getToBeTiled=function(de){var ve=de.id;if(this.toBeTiled[ve]!=null)return this.toBeTiled[ve];var te=de.getChild();if(te==null)return this.toBeTiled[ve]=!1,!1;for(var xe=te.getNodes(),De=0;De0)return this.toBeTiled[ve]=!1,!1;if(he.getChild()==null){this.toBeTiled[he.id]=!1;continue}if(!this.getToBeTiled(he))return this.toBeTiled[ve]=!1,!1}return this.toBeTiled[ve]=!0,!0},ke.prototype.getNodeDegree=function(de){de.id;for(var ve=de.getEdges(),te=0,xe=0;xert&&(rt=gt.rect.height)}te+=rt+de.verticalPadding}},ke.prototype.tileCompoundMembers=function(de,ve){var te=this;this.tiledMemberPack=[],Object.keys(de).forEach(function(xe){var De=ve[xe];te.tiledMemberPack[xe]=te.tileNodes(de[xe],De.paddingLeft+De.paddingRight),De.rect.width=te.tiledMemberPack[xe].width,De.rect.height=te.tiledMemberPack[xe].height})},ke.prototype.tileNodes=function(de,ve){var te=R.TILING_PADDING_VERTICAL,xe=R.TILING_PADDING_HORIZONTAL,De={rows:[],rowWidth:[],rowHeight:[],width:0,height:ve,verticalPadding:te,horizontalPadding:xe};de.sort(function(ee,rt){return ee.rect.width*ee.rect.height>rt.rect.width*rt.rect.height?-1:ee.rect.width*ee.rect.height0&&(Ie+=de.horizontalPadding),de.rowWidth[te]=Ie,de.width0&&(ee+=de.verticalPadding);var rt=0;ee>de.rowHeight[te]&&(rt=de.rowHeight[te],de.rowHeight[te]=ee,rt=de.rowHeight[te]-rt),de.height+=rt,de.rows[te].push(ve)},ke.prototype.getShortestRowIndex=function(de){for(var ve=-1,te=Number.MAX_VALUE,xe=0;xete&&(ve=xe,te=de.rowWidth[xe]);return ve},ke.prototype.canAddHorizontal=function(de,ve,te){var xe=this.getShortestRowIndex(de);if(xe<0)return!0;var De=de.rowWidth[xe];if(De+de.horizontalPadding+ve<=de.width)return!0;var he=0;de.rowHeight[xe]0&&(he=te+de.verticalPadding-de.rowHeight[xe]);var Ie;de.width-De>=ve+de.horizontalPadding?Ie=(de.height+he)/(De+ve+de.horizontalPadding):Ie=(de.height+he)/de.width,he=te+de.verticalPadding;var ee;return de.widthhe&&ve!=te){xe.splice(-1,1),de.rows[te].push(De),de.rowWidth[ve]=de.rowWidth[ve]-he,de.rowWidth[te]=de.rowWidth[te]+he,de.width=de.rowWidth[instance.getLongestRowIndex(de)];for(var Ie=Number.MIN_VALUE,ee=0;eeIe&&(Ie=xe[ee].height);ve>0&&(Ie+=de.verticalPadding);var rt=de.rowHeight[ve]+de.rowHeight[te];de.rowHeight[ve]=Ie,de.rowHeight[te]0)for(var wt=De;wt<=he;wt++)Et[0]+=this.grid[wt][Ie-1].length+this.grid[wt][Ie].length-1;if(he0)for(var wt=Ie;wt<=ee;wt++)Et[3]+=this.grid[De-1][wt].length+this.grid[De][wt].length-1;for(var jt=ce.MAX_VALUE,At,Bt,cn=0;cn0){var ee;ee=ye.getGraphManager().add(ye.newGraph(),te),this.processChildrenList(ee,ve,ye)}}},Q.prototype.stop=function(){return this.stopped=!0,this};var ce=function(ge){ge("layout","cose-bilkent",Q)};typeof cytoscape<"u"&&ce(cytoscape),p.exports=ce}])})})(qqt);const 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b/pr-preview/pr-51/site_libs/quarto-html/anchor.min.js new file mode 100644 index 00000000..5ac814d1 --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-html/anchor.min.js @@ -0,0 +1,9 @@ +// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat +// +// AnchorJS - v5.0.0 - 2023-01-18 +// https://www.bryanbraun.com/anchorjs/ +// Copyright (c) 2023 Bryan Braun; Licensed MIT +// +// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat +!function(A,e){"use strict";"function"==typeof define&&define.amd?define([],e):"object"==typeof module&&module.exports?module.exports=e():(A.AnchorJS=e(),A.anchors=new A.AnchorJS)}(globalThis,function(){"use strict";return function(A){function 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00000000..d9fd98f0 --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-html/quarto-syntax-highlighting.css @@ -0,0 +1,203 @@ +/* quarto syntax highlight colors */ +:root { + --quarto-hl-ot-color: #003B4F; + --quarto-hl-at-color: #657422; + --quarto-hl-ss-color: #20794D; + --quarto-hl-an-color: #5E5E5E; + --quarto-hl-fu-color: #4758AB; + --quarto-hl-st-color: #20794D; + --quarto-hl-cf-color: #003B4F; + --quarto-hl-op-color: #5E5E5E; + --quarto-hl-er-color: #AD0000; + --quarto-hl-bn-color: #AD0000; + --quarto-hl-al-color: #AD0000; + --quarto-hl-va-color: #111111; + --quarto-hl-bu-color: inherit; + --quarto-hl-ex-color: inherit; + --quarto-hl-pp-color: #AD0000; + --quarto-hl-in-color: #5E5E5E; + --quarto-hl-vs-color: #20794D; + --quarto-hl-wa-color: #5E5E5E; + --quarto-hl-do-color: #5E5E5E; + --quarto-hl-im-color: #00769E; + --quarto-hl-ch-color: #20794D; + --quarto-hl-dt-color: #AD0000; + --quarto-hl-fl-color: #AD0000; + --quarto-hl-co-color: #5E5E5E; + --quarto-hl-cv-color: #5E5E5E; + --quarto-hl-cn-color: #8f5902; + --quarto-hl-sc-color: #5E5E5E; + --quarto-hl-dv-color: #AD0000; + --quarto-hl-kw-color: #003B4F; +} + +/* other quarto variables */ +:root { + --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; +} + +pre > code.sourceCode > span { + color: #003B4F; +} + +code span { + color: #003B4F; +} + +code.sourceCode > span { + color: #003B4F; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #003B4F; +} + +code span.ot { + color: #003B4F; + font-style: inherit; +} + +code span.at { + color: #657422; + font-style: inherit; +} + +code span.ss { + color: #20794D; + font-style: inherit; +} + +code span.an { + color: #5E5E5E; + font-style: inherit; +} + +code span.fu { + color: #4758AB; + font-style: inherit; +} + +code span.st { + color: #20794D; + font-style: inherit; +} + +code span.cf { + color: #003B4F; + font-style: inherit; +} + +code span.op { + color: #5E5E5E; + font-style: inherit; +} + +code span.er { + color: #AD0000; + font-style: inherit; +} + +code span.bn { + color: #AD0000; + font-style: inherit; +} + +code span.al { + color: #AD0000; + font-style: inherit; +} + +code span.va { + color: #111111; + font-style: inherit; +} + +code span.bu { + font-style: inherit; +} + +code span.ex { + font-style: inherit; +} + +code span.pp { + color: #AD0000; + font-style: inherit; +} + +code span.in { + color: #5E5E5E; + font-style: inherit; +} + +code span.vs { + color: #20794D; + font-style: inherit; +} + +code span.wa { + color: #5E5E5E; + font-style: italic; +} + +code span.do { + color: #5E5E5E; + font-style: italic; +} + +code span.im { + color: #00769E; + font-style: inherit; +} + +code span.ch { + color: #20794D; + font-style: inherit; +} + +code span.dt { + color: #AD0000; + font-style: inherit; +} + +code span.fl { + color: #AD0000; + font-style: inherit; +} + +code span.co { + color: #5E5E5E; + font-style: inherit; +} + +code span.cv { + color: #5E5E5E; + font-style: italic; +} + +code span.cn { + color: #8f5902; + font-style: inherit; +} + +code span.sc { + color: #5E5E5E; + font-style: inherit; +} + +code span.dv { + color: #AD0000; + font-style: inherit; +} + +code span.kw { + color: #003B4F; + font-style: inherit; +} + +.prevent-inlining { + content: " { + // Find any conflicting margin elements and add margins to the + // top to prevent overlap + const marginChildren = window.document.querySelectorAll( + ".column-margin.column-container > * " + ); + + let lastBottom = 0; + for (const marginChild of marginChildren) { + if (marginChild.offsetParent !== null) { + // clear the top margin so we recompute it + marginChild.style.marginTop = null; + const top = marginChild.getBoundingClientRect().top + window.scrollY; + console.log({ + childtop: marginChild.getBoundingClientRect().top, + scroll: window.scrollY, + top, + lastBottom, + }); + if (top < lastBottom) { + const margin = lastBottom - top; + marginChild.style.marginTop = `${margin}px`; + } + const styles = window.getComputedStyle(marginChild); + const marginTop = parseFloat(styles["marginTop"]); + + console.log({ + top, + height: marginChild.getBoundingClientRect().height, + marginTop, + total: top + marginChild.getBoundingClientRect().height + marginTop, + }); + lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; + } + } +}; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Recompute the position of margin elements anytime the body size changes + if (window.ResizeObserver) { + const resizeObserver = new window.ResizeObserver( + throttle(layoutMarginEls, 50) + ); + resizeObserver.observe(window.document.body); + } + + const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]'); + const sidebarEl = window.document.getElementById("quarto-sidebar"); + const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left"); + const marginSidebarEl = window.document.getElementById( + "quarto-margin-sidebar" + ); + // function to determine whether the element has a previous sibling that is active + const prevSiblingIsActiveLink = (el) => { + const sibling = el.previousElementSibling; + if (sibling && sibling.tagName === "A") { + return sibling.classList.contains("active"); + } else { + return false; + } + }; + + // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior) + function fireSlideEnter(e) { + const event = window.document.createEvent("Event"); + event.initEvent("slideenter", true, true); + window.document.dispatchEvent(event); + } + const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); + tabs.forEach((tab) => { + tab.addEventListener("shown.bs.tab", fireSlideEnter); + }); + + // fire slideEnter for tabby tab activations (for htmlwidget resize behavior) + document.addEventListener("tabby", fireSlideEnter, false); + + // Track scrolling and mark TOC links as active + // get table of contents and sidebar (bail if we don't have at least one) + const tocLinks = tocEl + ? [...tocEl.querySelectorAll("a[data-scroll-target]")] + : []; + const makeActive = (link) => tocLinks[link].classList.add("active"); + const removeActive = (link) => tocLinks[link].classList.remove("active"); + const removeAllActive = () => + [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); + + // activate the anchor for a section associated with this TOC entry + tocLinks.forEach((link) => { + link.addEventListener("click", () => { + if (link.href.indexOf("#") !== -1) { + const anchor = link.href.split("#")[1]; + const heading = window.document.querySelector( + `[data-anchor-id=${anchor}]` + ); + if (heading) { + // Add the class + heading.classList.add("reveal-anchorjs-link"); + + // function to show the anchor + const handleMouseout = () => { + heading.classList.remove("reveal-anchorjs-link"); + heading.removeEventListener("mouseout", handleMouseout); + }; + + // add a function to clear the anchor when the user mouses out of it + heading.addEventListener("mouseout", handleMouseout); + } + } + }); + }); + + const sections = tocLinks.map((link) => { + const target = link.getAttribute("data-scroll-target"); + if (target.startsWith("#")) { + return window.document.getElementById(decodeURI(`${target.slice(1)}`)); + } else { + return window.document.querySelector(decodeURI(`${target}`)); + } + }); + + const sectionMargin = 200; + let currentActive = 0; + // track whether we've initialized state the first time + let init = false; + + const updateActiveLink = () => { + // The index from bottom to top (e.g. reversed list) + let sectionIndex = -1; + if ( + window.innerHeight + window.pageYOffset >= + window.document.body.offsetHeight + ) { + sectionIndex = 0; + } else { + sectionIndex = [...sections].reverse().findIndex((section) => { + if (section) { + return window.pageYOffset >= section.offsetTop - sectionMargin; + } else { + return false; + } + }); + } + if (sectionIndex > -1) { + const current = sections.length - sectionIndex - 1; + if (current !== currentActive) { + removeAllActive(); + currentActive = current; + makeActive(current); + if (init) { + window.dispatchEvent(sectionChanged); + } + init = true; + } + } + }; + + const inHiddenRegion = (top, bottom, hiddenRegions) => { + for (const region of hiddenRegions) { + if (top <= region.bottom && bottom >= region.top) { + return true; + } + } + return false; + }; + + const categorySelector = "header.quarto-title-block .quarto-category"; + const activateCategories = (href) => { + // Find any categories + // Surround them with a link pointing back to: + // #category=Authoring + try { + const categoryEls = window.document.querySelectorAll(categorySelector); + for (const categoryEl of categoryEls) { + const categoryText = categoryEl.textContent; + if (categoryText) { + const link = `${href}#category=${encodeURIComponent(categoryText)}`; + const linkEl = window.document.createElement("a"); + linkEl.setAttribute("href", link); + for (const child of categoryEl.childNodes) { + linkEl.append(child); + } + categoryEl.appendChild(linkEl); + } + } + } catch { + // Ignore errors + } + }; + function hasTitleCategories() { + return window.document.querySelector(categorySelector) !== null; + } + + function offsetRelativeUrl(url) { + const offset = getMeta("quarto:offset"); + return offset ? offset + url : url; + } + + function offsetAbsoluteUrl(url) { + const offset = getMeta("quarto:offset"); + const baseUrl = new URL(offset, window.location); + + const projRelativeUrl = url.replace(baseUrl, ""); + if (projRelativeUrl.startsWith("/")) { + return projRelativeUrl; + } else { + return "/" + projRelativeUrl; + } + } + + // read a meta tag value + function getMeta(metaName) { + const metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; + } + + async function findAndActivateCategories() { + const currentPagePath = offsetAbsoluteUrl(window.location.href); + const response = await fetch(offsetRelativeUrl("listings.json")); + if (response.status == 200) { + return response.json().then(function (listingPaths) { + const listingHrefs = []; + for (const listingPath of listingPaths) { + const pathWithoutLeadingSlash = listingPath.listing.substring(1); + for (const item of listingPath.items) { + if ( + item === currentPagePath || + item === currentPagePath + "index.html" + ) { + // Resolve this path against the offset to be sure + // we already are using the correct path to the listing + // (this adjusts the listing urls to be rooted against + // whatever root the page is actually running against) + const relative = offsetRelativeUrl(pathWithoutLeadingSlash); + const baseUrl = window.location; + const resolvedPath = new URL(relative, baseUrl); + listingHrefs.push(resolvedPath.pathname); + break; + } + } + } + + // Look up the tree for a nearby linting and use that if we find one + const nearestListing = findNearestParentListing( + offsetAbsoluteUrl(window.location.pathname), + listingHrefs + ); + if (nearestListing) { + activateCategories(nearestListing); + } else { + // See if the referrer is a listing page for this item + const referredRelativePath = offsetAbsoluteUrl(document.referrer); + const referrerListing = listingHrefs.find((listingHref) => { + const isListingReferrer = + listingHref === referredRelativePath || + listingHref === referredRelativePath + "index.html"; + return isListingReferrer; + }); + + if (referrerListing) { + // Try to use the referrer if possible + activateCategories(referrerListing); + } else if (listingHrefs.length > 0) { + // Otherwise, just fall back to the first listing + activateCategories(listingHrefs[0]); + } + } + }); + } + } + if (hasTitleCategories()) { + findAndActivateCategories(); + } + + const findNearestParentListing = (href, listingHrefs) => { + if (!href || !listingHrefs) { + return undefined; + } + // Look up the tree for a nearby linting and use that if we find one + const relativeParts = href.substring(1).split("/"); + while (relativeParts.length > 0) { + const path = relativeParts.join("/"); + for (const listingHref of listingHrefs) { + if (listingHref.startsWith(path)) { + return listingHref; + } + } + relativeParts.pop(); + } + + return undefined; + }; + + const manageSidebarVisiblity = (el, placeholderDescriptor) => { + let isVisible = true; + let elRect; + + return (hiddenRegions) => { + if (el === null) { + return; + } + + // Find the last element of the TOC + const lastChildEl = el.lastElementChild; + + if (lastChildEl) { + // Converts the sidebar to a menu + const convertToMenu = () => { + for (const child of el.children) { + child.style.opacity = 0; + child.style.overflow = "hidden"; + } + + nexttick(() => { + const toggleContainer = window.document.createElement("div"); + toggleContainer.style.width = "100%"; + toggleContainer.classList.add("zindex-over-content"); + toggleContainer.classList.add("quarto-sidebar-toggle"); + toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom + toggleContainer.id = placeholderDescriptor.id; + toggleContainer.style.position = "fixed"; + + const toggleIcon = window.document.createElement("i"); + toggleIcon.classList.add("quarto-sidebar-toggle-icon"); + toggleIcon.classList.add("bi"); + toggleIcon.classList.add("bi-caret-down-fill"); + + const toggleTitle = window.document.createElement("div"); + const titleEl = window.document.body.querySelector( + placeholderDescriptor.titleSelector + ); + if (titleEl) { + toggleTitle.append( + titleEl.textContent || titleEl.innerText, + toggleIcon + ); + } + toggleTitle.classList.add("zindex-over-content"); + toggleTitle.classList.add("quarto-sidebar-toggle-title"); + toggleContainer.append(toggleTitle); + + const toggleContents = window.document.createElement("div"); + toggleContents.classList = el.classList; + toggleContents.classList.add("zindex-over-content"); + toggleContents.classList.add("quarto-sidebar-toggle-contents"); + for (const child of el.children) { + if (child.id === "toc-title") { + continue; + } + + const clone = child.cloneNode(true); + clone.style.opacity = 1; + clone.style.display = null; + toggleContents.append(clone); + } + toggleContents.style.height = "0px"; + const positionToggle = () => { + // position the element (top left of parent, same width as parent) + if (!elRect) { + elRect = el.getBoundingClientRect(); + } + toggleContainer.style.left = `${elRect.left}px`; + toggleContainer.style.top = `${elRect.top}px`; + toggleContainer.style.width = `${elRect.width}px`; + }; + positionToggle(); + + toggleContainer.append(toggleContents); + el.parentElement.prepend(toggleContainer); + + // Process clicks + let tocShowing = false; + // Allow the caller to control whether this is dismissed + // when it is clicked (e.g. sidebar navigation supports + // opening and closing the nav tree, so don't dismiss on click) + const clickEl = placeholderDescriptor.dismissOnClick + ? toggleContainer + : toggleTitle; + + const closeToggle = () => { + if (tocShowing) { + toggleContainer.classList.remove("expanded"); + toggleContents.style.height = "0px"; + tocShowing = false; + } + }; + + // Get rid of any expanded toggle if the user scrolls + window.document.addEventListener( + "scroll", + throttle(() => { + closeToggle(); + }, 50) + ); + + // Handle positioning of the toggle + window.addEventListener( + "resize", + throttle(() => { + elRect = undefined; + positionToggle(); + }, 50) + ); + + window.addEventListener("quarto-hrChanged", () => { + elRect = undefined; + }); + + // Process the click + clickEl.onclick = () => { + if (!tocShowing) { + toggleContainer.classList.add("expanded"); + toggleContents.style.height = null; + tocShowing = true; + } else { + closeToggle(); + } + }; + }); + }; + + // Converts a sidebar from a menu back to a sidebar + const convertToSidebar = () => { + for (const child of el.children) { + child.style.opacity = 1; + child.style.overflow = null; + } + + const placeholderEl = window.document.getElementById( + placeholderDescriptor.id + ); + if (placeholderEl) { + placeholderEl.remove(); + } + + el.classList.remove("rollup"); + }; + + if (isReaderMode()) { + convertToMenu(); + isVisible = false; + } else { + // Find the top and bottom o the element that is being managed + const elTop = el.offsetTop; + const elBottom = + elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; + + if (!isVisible) { + // If the element is current not visible reveal if there are + // no conflicts with overlay regions + if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToSidebar(); + isVisible = true; + } + } else { + // If the element is visible, hide it if it conflicts with overlay regions + // and insert a placeholder toggle (or if we're in reader mode) + if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToMenu(); + isVisible = false; + } + } + } + } + }; + }; + + const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]'); + for (const tabEl of tabEls) { + const id = tabEl.getAttribute("data-bs-target"); + if (id) { + const columnEl = document.querySelector( + `${id} .column-margin, .tabset-margin-content` + ); + if (columnEl) + tabEl.addEventListener("shown.bs.tab", function (event) { + const el = event.srcElement; + if (el) { + const visibleCls = `${el.id}-margin-content`; + // walk up until we find a parent tabset + let panelTabsetEl = el.parentElement; + while (panelTabsetEl) { + if (panelTabsetEl.classList.contains("panel-tabset")) { + break; + } + panelTabsetEl = panelTabsetEl.parentElement; + } + + if (panelTabsetEl) { + const prevSib = panelTabsetEl.previousElementSibling; + if ( + prevSib && + prevSib.classList.contains("tabset-margin-container") + ) { + const childNodes = prevSib.querySelectorAll( + ".tabset-margin-content" + ); + for (const childEl of childNodes) { + if (childEl.classList.contains(visibleCls)) { + childEl.classList.remove("collapse"); + } else { + childEl.classList.add("collapse"); + } + } + } + } + } + + layoutMarginEls(); + }); + } + } + + // Manage the visibility of the toc and the sidebar + const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { + id: "quarto-toc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { + id: "quarto-sidebarnav-toggle", + titleSelector: ".title", + dismissOnClick: false, + }); + let tocLeftScrollVisibility; + if (leftTocEl) { + tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { + id: "quarto-lefttoc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + } + + // Find the first element that uses formatting in special columns + const conflictingEls = window.document.body.querySelectorAll( + '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' + ); + + // Filter all the possibly conflicting elements into ones + // the do conflict on the left or ride side + const arrConflictingEls = Array.from(conflictingEls); + const leftSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return false; + } + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + className.startsWith("column-") && + !className.endsWith("right") && + !className.endsWith("container") && + className !== "column-margin" + ); + }); + }); + const rightSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return true; + } + + const hasMarginCaption = Array.from(el.classList).find((className) => { + return className == "margin-caption"; + }); + if (hasMarginCaption) { + return true; + } + + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + !className.endsWith("container") && + className.startsWith("column-") && + !className.endsWith("left") + ); + }); + }); + + const kOverlapPaddingSize = 10; + function toRegions(els) { + return els.map((el) => { + const boundRect = el.getBoundingClientRect(); + const top = + boundRect.top + + document.documentElement.scrollTop - + kOverlapPaddingSize; + return { + top, + bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, + }; + }); + } + + let hasObserved = false; + const visibleItemObserver = (els) => { + let visibleElements = [...els]; + const intersectionObserver = new IntersectionObserver( + (entries, _observer) => { + entries.forEach((entry) => { + if (entry.isIntersecting) { + if (visibleElements.indexOf(entry.target) === -1) { + visibleElements.push(entry.target); + } + } else { + visibleElements = visibleElements.filter((visibleEntry) => { + return visibleEntry !== entry; + }); + } + }); + + if (!hasObserved) { + hideOverlappedSidebars(); + } + hasObserved = true; + }, + {} + ); + els.forEach((el) => { + intersectionObserver.observe(el); + }); + + return { + getVisibleEntries: () => { + return visibleElements; + }, + }; + }; + + const rightElementObserver = visibleItemObserver(rightSideConflictEls); + const leftElementObserver = visibleItemObserver(leftSideConflictEls); + + const hideOverlappedSidebars = () => { + marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries())); + sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries())); + if (tocLeftScrollVisibility) { + tocLeftScrollVisibility( + toRegions(leftElementObserver.getVisibleEntries()) + ); + } + }; + + window.quartoToggleReader = () => { + // Applies a slow class (or removes it) + // to update the transition speed + const slowTransition = (slow) => { + const manageTransition = (id, slow) => { + const el = document.getElementById(id); + if (el) { + if (slow) { + el.classList.add("slow"); + } else { + el.classList.remove("slow"); + } + } + }; + + manageTransition("TOC", slow); + manageTransition("quarto-sidebar", slow); + }; + const readerMode = !isReaderMode(); + setReaderModeValue(readerMode); + + // If we're entering reader mode, slow the transition + if (readerMode) { + slowTransition(readerMode); + } + highlightReaderToggle(readerMode); + hideOverlappedSidebars(); + + // If we're exiting reader mode, restore the non-slow transition + if (!readerMode) { + slowTransition(!readerMode); + } + }; + + const highlightReaderToggle = (readerMode) => { + const els = document.querySelectorAll(".quarto-reader-toggle"); + if (els) { + els.forEach((el) => { + if (readerMode) { + el.classList.add("reader"); + } else { + el.classList.remove("reader"); + } + }); + } + }; + + const setReaderModeValue = (val) => { + if (window.location.protocol !== "file:") { + window.localStorage.setItem("quarto-reader-mode", val); + } else { + localReaderMode = val; + } + }; + + const isReaderMode = () => { + if (window.location.protocol !== "file:") { + return window.localStorage.getItem("quarto-reader-mode") === "true"; + } else { + return localReaderMode; + } + }; + let localReaderMode = null; + + const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded"); + const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1; + + // Walk the TOC and collapse/expand nodes + // Nodes are expanded if: + // - they are top level + // - they have children that are 'active' links + // - they are directly below an link that is 'active' + const walk = (el, depth) => { + // Tick depth when we enter a UL + if (el.tagName === "UL") { + depth = depth + 1; + } + + // It this is active link + let isActiveNode = false; + if (el.tagName === "A" && el.classList.contains("active")) { + isActiveNode = true; + } + + // See if there is an active child to this element + let hasActiveChild = false; + for (child of el.children) { + hasActiveChild = walk(child, depth) || hasActiveChild; + } + + // Process the collapse state if this is an UL + if (el.tagName === "UL") { + if (tocOpenDepth === -1 && depth > 1) { + el.classList.add("collapse"); + } else if ( + depth <= tocOpenDepth || + hasActiveChild || + prevSiblingIsActiveLink(el) + ) { + el.classList.remove("collapse"); + } else { + el.classList.add("collapse"); + } + + // untick depth when we leave a UL + depth = depth - 1; + } + return hasActiveChild || isActiveNode; + }; + + // walk the TOC and expand / collapse any items that should be shown + + if (tocEl) { + walk(tocEl, 0); + updateActiveLink(); + } + + // Throttle the scroll event and walk peridiocally + window.document.addEventListener( + "scroll", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 5) + ); + window.addEventListener( + "resize", + throttle(() => { + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 10) + ); + hideOverlappedSidebars(); + highlightReaderToggle(isReaderMode()); +}); + +// grouped tabsets +window.addEventListener("pageshow", (_event) => { + function getTabSettings() { + const data = localStorage.getItem("quarto-persistent-tabsets-data"); + if (!data) { + localStorage.setItem("quarto-persistent-tabsets-data", "{}"); + return {}; + } + if (data) { + return JSON.parse(data); + } + } + + function setTabSettings(data) { + localStorage.setItem( + "quarto-persistent-tabsets-data", + JSON.stringify(data) + ); + } + + function setTabState(groupName, groupValue) { + const data = getTabSettings(); + data[groupName] = groupValue; + setTabSettings(data); + } + + function toggleTab(tab, active) { + const tabPanelId = tab.getAttribute("aria-controls"); + const tabPanel = document.getElementById(tabPanelId); + if (active) { + tab.classList.add("active"); + tabPanel.classList.add("active"); + } else { + tab.classList.remove("active"); + tabPanel.classList.remove("active"); + } + } + + function toggleAll(selectedGroup, selectorsToSync) { + for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) { + const active = selectedGroup === thisGroup; + for (const tab of tabs) { + toggleTab(tab, active); + } + } + } + + function findSelectorsToSyncByLanguage() { + const result = {}; + const tabs = Array.from( + document.querySelectorAll(`div[data-group] a[id^='tabset-']`) + ); + for (const item of tabs) { + const div = item.parentElement.parentElement.parentElement; + const group = div.getAttribute("data-group"); + if (!result[group]) { + result[group] = {}; + } + const selectorsToSync = result[group]; + const value = item.innerHTML; + if (!selectorsToSync[value]) { + selectorsToSync[value] = []; + } + selectorsToSync[value].push(item); + } + return result; + } + + function setupSelectorSync() { + const selectorsToSync = findSelectorsToSyncByLanguage(); + Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => { + Object.entries(tabSetsByValue).forEach(([value, items]) => { + items.forEach((item) => { + item.addEventListener("click", (_event) => { + setTabState(group, value); + toggleAll(value, selectorsToSync[group]); + }); + }); + }); + }); + return selectorsToSync; + } + + const selectorsToSync = setupSelectorSync(); + for (const [group, selectedName] of Object.entries(getTabSettings())) { + const selectors = selectorsToSync[group]; + // it's possible that stale state gives us empty selections, so we explicitly check here. + if (selectors) { + toggleAll(selectedName, selectors); + } + } +}); + +function throttle(func, wait) { + let waiting = false; + return function () { + if (!waiting) { + func.apply(this, arguments); + waiting = true; + setTimeout(function () { + waiting = false; + }, wait); + } + }; +} + +function nexttick(func) { + return setTimeout(func, 0); +} diff --git a/pr-preview/pr-51/site_libs/quarto-html/tippy.css b/pr-preview/pr-51/site_libs/quarto-html/tippy.css new file mode 100644 index 00000000..e6ae635c --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-html/tippy.css @@ -0,0 +1 @@ +.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 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a specific listing + const listingIds = Object.keys(window["quarto-listings"]); + for (const listingId of listingIds) { + const page = hash[getListingPageKey(listingId)]; + if (page) { + showPage(listingId, page); + } + } + } + + const listingIds = Object.keys(window["quarto-listings"]); + for (const listingId of listingIds) { + // The actual list + const list = window["quarto-listings"][listingId]; + + // Update the handlers for pagination events + refreshPaginationHandlers(listingId); + + // Render any visible items that need it + renderVisibleProgressiveImages(list); + + // Whenever the list is updated, we also need to + // attach handlers to the new pagination elements + // and refresh any newly visible items. + list.on("updated", function () { + renderVisibleProgressiveImages(list); + setTimeout(() => refreshPaginationHandlers(listingId)); + + // Show or hide the no matching message + toggleNoMatchingMessage(list); + }); + } +}; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Attach click handlers to categories + const categoryEls = window.document.querySelectorAll( + ".quarto-listing-category .category" + ); + + for (const categoryEl of categoryEls) { + const category = categoryEl.getAttribute("data-category"); + categoryEl.onclick = () => { + activateCategory(category); + setCategoryHash(category); + }; + } + + // Attach a click handler to the category title + // (there should be only one, but since it is a class name, handle N) + const categoryTitleEls = window.document.querySelectorAll( + ".quarto-listing-category-title" + ); + for (const categoryTitleEl of categoryTitleEls) { + categoryTitleEl.onclick = () => { + activateCategory(""); + setCategoryHash(""); + }; + } + + categoriesLoaded = true; +}); + +function toggleNoMatchingMessage(list) { + const selector = `#${list.listContainer.id} .listing-no-matching`; + const noMatchingEl = window.document.querySelector(selector); + if (noMatchingEl) { + if (list.visibleItems.length === 0) { + noMatchingEl.classList.remove("d-none"); + } else { + if (!noMatchingEl.classList.contains("d-none")) { + noMatchingEl.classList.add("d-none"); + } + } + } +} + +function setCategoryHash(category) { + setHash({ category }); +} + +function setPageHash(listingId, page) { + const currentHash = getHash() || {}; + currentHash[getListingPageKey(listingId)] = page; + setHash(currentHash); +} + +function getListingPageKey(listingId) { + return `${listingId}-page`; +} + +function refreshPaginationHandlers(listingId) { + const listingEl = window.document.getElementById(listingId); + const paginationEls = listingEl.querySelectorAll( + ".pagination li.page-item:not(.disabled) .page.page-link" + ); + for (const paginationEl of paginationEls) { + paginationEl.onclick = (sender) => { + setPageHash(listingId, sender.target.getAttribute("data-i")); + showPage(listingId, sender.target.getAttribute("data-i")); + return false; + }; + } +} + +function renderVisibleProgressiveImages(list) { + // Run through the visible items and render any progressive images + for (const item of list.visibleItems) { + const itemEl = item.elm; + if (itemEl) { + const progressiveImgs = itemEl.querySelectorAll( + `img[${kProgressiveAttr}]` + ); + for (const progressiveImg of progressiveImgs) { + const srcValue = progressiveImg.getAttribute(kProgressiveAttr); + if (srcValue) { + progressiveImg.setAttribute("src", srcValue); + } + progressiveImg.removeAttribute(kProgressiveAttr); + } + } + } +} + +function getHash() { + // Hashes are of the form + // #name:value|name1:value1|name2:value2 + const currentUrl = new URL(window.location); + const hashRaw = currentUrl.hash ? currentUrl.hash.slice(1) : undefined; + return parseHash(hashRaw); +} + +const kAnd = "&"; +const kEquals = "="; + +function parseHash(hash) { + if (!hash) { + return undefined; + } + const hasValuesStrs = hash.split(kAnd); + const hashValues = hasValuesStrs + .map((hashValueStr) => { + const vals = hashValueStr.split(kEquals); + if (vals.length === 2) { + return { name: vals[0], value: vals[1] }; + } else { + return undefined; + } + }) + .filter((value) => { + return value !== undefined; + }); + + const hashObj = {}; + hashValues.forEach((hashValue) => { + hashObj[hashValue.name] = decodeURIComponent(hashValue.value); + }); + return hashObj; +} + +function makeHash(obj) { + return Object.keys(obj) + .map((key) => { + return `${key}${kEquals}${obj[key]}`; + }) + .join(kAnd); +} + +function setHash(obj) { + const hash = makeHash(obj); + window.history.pushState(null, null, `#${hash}`); +} + +function showPage(listingId, page) { + const list = window["quarto-listings"][listingId]; + if (list) { + list.show((page - 1) * list.page + 1, list.page); + } +} + +function activateCategory(category) { + // Deactivate existing categories + const activeEls = window.document.querySelectorAll( + ".quarto-listing-category .category.active" + ); + for (const activeEl of activeEls) { + activeEl.classList.remove("active"); + } + + // Activate this category + const categoryEl = window.document.querySelector( + `.quarto-listing-category .category[data-category='${category}'` + ); + if (categoryEl) { + categoryEl.classList.add("active"); + } + + // Filter the listings to this category + filterListingCategory(category); +} + +function filterListingCategory(category) { + const listingIds = Object.keys(window["quarto-listings"]); + for (const listingId of listingIds) { + const list = window["quarto-listings"][listingId]; + if (list) { + if (category === "") { + // resets the filter + list.filter(); + } else { + // filter to this category + list.filter(function (item) { + const itemValues = item.values(); + if (itemValues.categories !== null) { + const categories = itemValues.categories.split(","); + return categories.includes(category); + } else { + return false; + } + }); + } + } + } +} diff --git a/pr-preview/pr-51/site_libs/quarto-nav/headroom.min.js b/pr-preview/pr-51/site_libs/quarto-nav/headroom.min.js new file mode 100644 index 00000000..b08f1dff --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-nav/headroom.min.js @@ -0,0 +1,7 @@ +/*! + * headroom.js v0.12.0 - Give your page some headroom. 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00000000..6221d4b5 --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-nav/quarto-nav.js @@ -0,0 +1,277 @@ +const headroomChanged = new CustomEvent("quarto-hrChanged", { + detail: {}, + bubbles: true, + cancelable: false, + composed: false, +}); + +window.document.addEventListener("DOMContentLoaded", function () { + let init = false; + + // Manage the back to top button, if one is present. + let lastScrollTop = window.pageYOffset || document.documentElement.scrollTop; + const scrollDownBuffer = 5; + const scrollUpBuffer = 35; + const btn = document.getElementById("quarto-back-to-top"); + const hideBackToTop = () => { + btn.style.display = "none"; + }; + const showBackToTop = () => { + btn.style.display = "inline-block"; + }; + if (btn) { + window.document.addEventListener( + "scroll", + function () { + const currentScrollTop = + window.pageYOffset || document.documentElement.scrollTop; + + // Shows and hides the button 'intelligently' as the user scrolls + if (currentScrollTop - scrollDownBuffer > lastScrollTop) { + hideBackToTop(); + lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop; + } else if (currentScrollTop < lastScrollTop - scrollUpBuffer) { + showBackToTop(); + lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop; + } + + // Show the button at the bottom, hides it at the top + if (currentScrollTop <= 0) { + hideBackToTop(); + } else if ( + window.innerHeight + currentScrollTop >= + document.body.offsetHeight + ) { + showBackToTop(); + } + }, + false + ); + } + + function throttle(func, wait) { + var timeout; + return function () { + const context = this; + const args = arguments; + const later = function () { + clearTimeout(timeout); + timeout = null; + func.apply(context, args); + }; + + if (!timeout) { + timeout = setTimeout(later, wait); + } + }; + } + + function headerOffset() { + // Set an offset if there is are fixed top navbar + const headerEl = window.document.querySelector("header.fixed-top"); + if (headerEl) { + return headerEl.clientHeight; + } else { + return 0; + } + } + + function footerOffset() { + const footerEl = window.document.querySelector("footer.footer"); + if (footerEl) { + return footerEl.clientHeight; + } else { + return 0; + } + } + + function updateDocumentOffsetWithoutAnimation() { + updateDocumentOffset(false); + } + + function updateDocumentOffset(animated) { + // set body offset + const topOffset = headerOffset(); + const bodyOffset = topOffset + footerOffset(); + const bodyEl = window.document.body; + bodyEl.setAttribute("data-bs-offset", topOffset); + bodyEl.style.paddingTop = topOffset + "px"; + + // deal with sidebar offsets + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + if (!animated) { + sidebar.classList.add("notransition"); + // Remove the no transition class after the animation has time to complete + setTimeout(function () { + sidebar.classList.remove("notransition"); + }, 201); + } + + if (window.Headroom && sidebar.classList.contains("sidebar-unpinned")) { + sidebar.style.top = "0"; + sidebar.style.maxHeight = "100vh"; + } else { + sidebar.style.top = topOffset + "px"; + sidebar.style.maxHeight = "calc(100vh - " + topOffset + "px)"; + } + }); + + // allow space for footer + const mainContainer = window.document.querySelector(".quarto-container"); + if (mainContainer) { + mainContainer.style.minHeight = "calc(100vh - " + bodyOffset + "px)"; + } + + // link offset + let linkStyle = window.document.querySelector("#quarto-target-style"); + if (!linkStyle) { + linkStyle = window.document.createElement("style"); + linkStyle.setAttribute("id", "quarto-target-style"); + window.document.head.appendChild(linkStyle); + } + while (linkStyle.firstChild) { + linkStyle.removeChild(linkStyle.firstChild); + } + if (topOffset > 0) { + linkStyle.appendChild( + window.document.createTextNode(` + section:target::before { + content: ""; + display: block; + height: ${topOffset}px; + margin: -${topOffset}px 0 0; + }`) + ); + } + if (init) { + window.dispatchEvent(headroomChanged); + } + init = true; + } + + // initialize headroom + var header = window.document.querySelector("#quarto-header"); + if (header && window.Headroom) { + const headroom = new window.Headroom(header, { + tolerance: 5, + onPin: function () { + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + sidebar.classList.remove("sidebar-unpinned"); + }); + updateDocumentOffset(); + }, + onUnpin: function () { + const sidebars = window.document.querySelectorAll( + ".sidebar, .headroom-target" + ); + sidebars.forEach((sidebar) => { + sidebar.classList.add("sidebar-unpinned"); + }); + updateDocumentOffset(); + }, + }); + headroom.init(); + + let frozen = false; + window.quartoToggleHeadroom = function () { + if (frozen) { + headroom.unfreeze(); + frozen = false; + } else { + headroom.freeze(); + frozen = true; + } + }; + } + + window.addEventListener( + "hashchange", + function (e) { + if ( + getComputedStyle(document.documentElement).scrollBehavior !== "smooth" + ) { + window.scrollTo(0, window.pageYOffset - headerOffset()); + } + }, + false + ); + + // Observe size changed for the header + const headerEl = window.document.querySelector("header.fixed-top"); + if (headerEl && window.ResizeObserver) { + const observer = new window.ResizeObserver(() => { + setTimeout(updateDocumentOffsetWithoutAnimation, 0); + }); + observer.observe(headerEl, { + attributes: true, + childList: true, + characterData: true, + }); + } else { + window.addEventListener( + "resize", + throttle(updateDocumentOffsetWithoutAnimation, 50) + ); + } + setTimeout(updateDocumentOffsetWithoutAnimation, 250); + + // fixup index.html links if we aren't on the filesystem + if (window.location.protocol !== "file:") { + const links = window.document.querySelectorAll("a"); + for (let i = 0; i < links.length; i++) { + if (links[i].href) { + 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this._bitapSearch.searchIn(e)}}],[{key:"type",get:function(){return"fuzzy"}},{key:"multiRegex",get:function(){return/^"(.*)"$/}},{key:"singleRegex",get:function(){return/^(.*)$/}}]),n}(z),H=function(e){a(n,e);var t=l(n);function n(e){return r(this,n),t.call(this,e)}return o(n,[{key:"search",value:function(e){for(var t,n=0,r=[],i=this.pattern.length;(t=e.indexOf(this.pattern,n))>-1;)n=t+i,r.push([t,n-1]);var o=!!r.length;return{isMatch:o,score:o?0:1,indices:r}}}],[{key:"type",get:function(){return"include"}},{key:"multiRegex",get:function(){return/^'"(.*)"$/}},{key:"singleRegex",get:function(){return/^'(.*)$/}}]),n}(z),Q=[K,H,B,J,V,U,q,G],X=Q.length,Y=/ +(?=(?:[^\"]*\"[^\"]*\")*[^\"]*$)/;function Z(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{};return e.split("|").map((function(e){for(var n=e.trim().split(Y).filter((function(e){return e&&!!e.trim()})),r=[],i=0,o=n.length;i1&&void 0!==arguments[1]?arguments[1]:{},i=n.isCaseSensitive,o=void 0===i?I.isCaseSensitive:i,c=n.includeMatches,a=void 0===c?I.includeMatches:c,s=n.minMatchCharLength,u=void 0===s?I.minMatchCharLength:s,h=n.ignoreLocation,l=void 0===h?I.ignoreLocation:h,f=n.findAllMatches,d=void 0===f?I.findAllMatches:f,v=n.location,g=void 0===v?I.location:v,y=n.threshold,p=void 0===y?I.threshold:y,m=n.distance,k=void 0===m?I.distance:m;r(this,e),this.query=null,this.options={isCaseSensitive:o,includeMatches:a,minMatchCharLength:u,findAllMatches:d,ignoreLocation:l,location:g,threshold:p,distance:k},this.pattern=o?t:t.toLowerCase(),this.query=Z(this.pattern,this.options)}return o(e,[{key:"searchIn",value:function(e){var t=this.query;if(!t)return{isMatch:!1,score:1};var n=this.options,r=n.includeMatches;e=n.isCaseSensitive?e:e.toLowerCase();for(var i=0,o=[],c=0,a=0,s=t.length;a-1&&(n.refIndex=e.idx),t.matches.push(n)}}))}function ve(e,t){t.score=e.score}function ge(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:{},r=n.includeMatches,i=void 0===r?I.includeMatches:r,o=n.includeScore,c=void 0===o?I.includeScore:o,a=[];return i&&a.push(de),c&&a.push(ve),e.map((function(e){var n=e.idx,r={item:t[n],refIndex:n};return a.length&&a.forEach((function(t){t(e,r)})),r}))}var ye=function(){function e(n){var i=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},o=arguments.length>2?arguments[2]:void 0;r(this,e),this.options=t(t({},I),i),this.options.useExtendedSearch,this._keyStore=new S(this.options.keys),this.setCollection(n,o)}return o(e,[{key:"setCollection",value:function(e,t){if(this._docs=e,t&&!(t instanceof $))throw new Error("Incorrect 'index' type");this._myIndex=t||F(this.options.keys,this._docs,{getFn:this.options.getFn,fieldNormWeight:this.options.fieldNormWeight})}},{key:"add",value:function(e){k(e)&&(this._docs.push(e),this._myIndex.add(e))}},{key:"remove",value:function(){for(var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:function(){return!1},t=[],n=0,r=this._docs.length;n1&&void 0!==arguments[1]?arguments[1]:{},n=t.limit,r=void 0===n?-1:n,i=this.options,o=i.includeMatches,c=i.includeScore,a=i.shouldSort,s=i.sortFn,u=i.ignoreFieldNorm,h=g(e)?g(this._docs[0])?this._searchStringList(e):this._searchObjectList(e):this._searchLogical(e);return fe(h,{ignoreFieldNorm:u}),a&&h.sort(s),y(r)&&r>-1&&(h=h.slice(0,r)),ge(h,this._docs,{includeMatches:o,includeScore:c})}},{key:"_searchStringList",value:function(e){var t=re(e,this.options),n=this._myIndex.records,r=[];return n.forEach((function(e){var n=e.v,i=e.i,o=e.n;if(k(n)){var c=t.searchIn(n),a=c.isMatch,s=c.score,u=c.indices;a&&r.push({item:n,idx:i,matches:[{score:s,value:n,norm:o,indices:u}]})}})),r}},{key:"_searchLogical",value:function(e){var t=this,n=function(e,t){var n=(arguments.length>2&&void 0!==arguments[2]?arguments[2]:{}).auto,r=void 0===n||n,i=function e(n){var i=Object.keys(n),o=ue(n);if(!o&&i.length>1&&!se(n))return e(le(n));if(he(n)){var c=o?n[ce]:i[0],a=o?n[ae]:n[c];if(!g(a))throw new Error(x(c));var s={keyId:j(c),pattern:a};return r&&(s.searcher=re(a,t)),s}var u={children:[],operator:i[0]};return i.forEach((function(t){var r=n[t];v(r)&&r.forEach((function(t){u.children.push(e(t))}))})),u};return se(e)||(e=le(e)),i(e)}(e,this.options),r=function e(n,r,i){if(!n.children){var o=n.keyId,c=n.searcher,a=t._findMatches({key:t._keyStore.get(o),value:t._myIndex.getValueForItemAtKeyId(r,o),searcher:c});return a&&a.length?[{idx:i,item:r,matches:a}]:[]}for(var s=[],u=0,h=n.children.length;u1&&void 0!==arguments[1]?arguments[1]:{},n=t.getFn,r=void 0===n?I.getFn:n,i=t.fieldNormWeight,o=void 0===i?I.fieldNormWeight:i,c=e.keys,a=e.records,s=new $({getFn:r,fieldNormWeight:o});return s.setKeys(c),s.setIndexRecords(a),s},ye.config=I,function(){ne.push.apply(ne,arguments)}(te),ye},"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):(e="undefined"!=typeof globalThis?globalThis:e||self).Fuse=t(); \ No newline at end of file diff --git a/pr-preview/pr-51/site_libs/quarto-search/quarto-search.js b/pr-preview/pr-51/site_libs/quarto-search/quarto-search.js new file mode 100644 index 00000000..2912961f --- /dev/null +++ b/pr-preview/pr-51/site_libs/quarto-search/quarto-search.js @@ -0,0 +1,1149 @@ +const kQueryArg = "q"; +const kResultsArg = "show-results"; + +// If items don't provide a URL, then both the navigator and the onSelect +// function aren't called (and therefore, the default implementation is used) +// +// We're using this sentinel URL to signal to those handlers that this +// item is a more item (along with the type) and can be handled appropriately +const kItemTypeMoreHref = "0767FDFD-0422-4E5A-BC8A-3BE11E5BBA05"; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Ensure that search is available on this page. If it isn't, + // should return early and not do anything + var searchEl = window.document.getElementById("quarto-search"); + if (!searchEl) return; + + const { autocomplete } = window["@algolia/autocomplete-js"]; + + let quartoSearchOptions = {}; + let language = {}; + const searchOptionEl = window.document.getElementById( + "quarto-search-options" + ); + if (searchOptionEl) { + const jsonStr = searchOptionEl.textContent; + quartoSearchOptions = JSON.parse(jsonStr); + language = quartoSearchOptions.language; + } + + // note the search mode + if (quartoSearchOptions.type === "overlay") { + searchEl.classList.add("type-overlay"); + } else { + searchEl.classList.add("type-textbox"); + } + + // Used to determine highlighting behavior for this page + // A `q` query param is expected when the user follows a search + // to this page + const currentUrl = new URL(window.location); + const query = currentUrl.searchParams.get(kQueryArg); + const showSearchResults = currentUrl.searchParams.get(kResultsArg); + const mainEl = window.document.querySelector("main"); + + // highlight matches on the page + if (query && mainEl) { + // perform any highlighting + highlight(escapeRegExp(query), mainEl); + + // fix up the URL to remove the q query param + const replacementUrl = new URL(window.location); + replacementUrl.searchParams.delete(kQueryArg); + window.history.replaceState({}, "", replacementUrl); + } + + // function to clear highlighting on the page when the search query changes + // (e.g. if the user edits the query or clears it) + let highlighting = true; + const resetHighlighting = (searchTerm) => { + if (mainEl && highlighting && query && searchTerm !== query) { + clearHighlight(query, mainEl); + highlighting = false; + } + }; + + // Clear search highlighting when the user scrolls sufficiently + const resetFn = () => { + resetHighlighting(""); + window.removeEventListener("quarto-hrChanged", resetFn); + window.removeEventListener("quarto-sectionChanged", resetFn); + }; + + // Register this event after the initial scrolling and settling of events + // on the page + window.addEventListener("quarto-hrChanged", resetFn); + window.addEventListener("quarto-sectionChanged", resetFn); + + // Responsively switch to overlay mode if the search is present on the navbar + // Note that switching the sidebar to overlay mode requires more coordinate (not just + // the media query since we generate different HTML for sidebar overlays than we do + // for sidebar input UI) + const detachedMediaQuery = + quartoSearchOptions.type === "overlay" ? "all" : "(max-width: 991px)"; + + // If configured, include the analytics client to send insights + const plugins = configurePlugins(quartoSearchOptions); + + let lastState = null; + const { setIsOpen, setQuery, setCollections } = autocomplete({ + container: searchEl, + detachedMediaQuery: detachedMediaQuery, + defaultActiveItemId: 0, + panelContainer: "#quarto-search-results", + panelPlacement: quartoSearchOptions["panel-placement"], + debug: false, + openOnFocus: true, + plugins, + classNames: { + form: "d-flex", + }, + translations: { + clearButtonTitle: language["search-clear-button-title"], + detachedCancelButtonText: language["search-detached-cancel-button-title"], + submitButtonTitle: language["search-submit-button-title"], + }, + initialState: { + query, + }, + getItemUrl({ item }) { + return item.href; + }, + onStateChange({ state }) { + // Perhaps reset highlighting + resetHighlighting(state.query); + + // If the panel just opened, ensure the panel is positioned properly + if (state.isOpen) { + if (lastState && !lastState.isOpen) { + setTimeout(() => { + positionPanel(quartoSearchOptions["panel-placement"]); + }, 150); + } + } + + // Perhaps show the copy link + showCopyLink(state.query, quartoSearchOptions); + + lastState = state; + }, + reshape({ sources, state }) { + return sources.map((source) => { + try { + const items = source.getItems(); + + // Validate the items + validateItems(items); + + // group the items by document + const groupedItems = new Map(); + items.forEach((item) => { + const hrefParts = item.href.split("#"); + const baseHref = hrefParts[0]; + const isDocumentItem = hrefParts.length === 1; + + const items = groupedItems.get(baseHref); + if (!items) { + groupedItems.set(baseHref, [item]); + } else { + // If the href for this item matches the document + // exactly, place this item first as it is the item that represents + // the document itself + if (isDocumentItem) { + items.unshift(item); + } else { + items.push(item); + } + groupedItems.set(baseHref, items); + } + }); + + const reshapedItems = []; + let count = 1; + for (const [_key, value] of groupedItems) { + const firstItem = value[0]; + reshapedItems.push({ + ...firstItem, + type: kItemTypeDoc, + }); + + const collapseMatches = quartoSearchOptions["collapse-after"]; + const collapseCount = + typeof collapseMatches === "number" ? collapseMatches : 1; + + if (value.length > 1) { + const target = `search-more-${count}`; + const isExpanded = + state.context.expanded && + state.context.expanded.includes(target); + + const remainingCount = value.length - collapseCount; + + for (let i = 1; i < value.length; i++) { + if (collapseMatches && i === collapseCount) { + reshapedItems.push({ + target, + title: isExpanded + ? language["search-hide-matches-text"] + : remainingCount === 1 + ? `${remainingCount} ${language["search-more-match-text"]}` + : `${remainingCount} ${language["search-more-matches-text"]}`, + type: kItemTypeMore, + href: kItemTypeMoreHref, + }); + } + + if (isExpanded || !collapseMatches || i < collapseCount) { + reshapedItems.push({ + ...value[i], + type: kItemTypeItem, + target, + }); + } + } + } + count += 1; + } + + return { + ...source, + getItems() { + return reshapedItems; + }, + }; + } catch (error) { + // Some form of error occurred + return { + ...source, + getItems() { + return [ + { + title: error.name || "An Error Occurred While Searching", + text: + error.message || + "An unknown error occurred while attempting to perform the requested search.", + type: kItemTypeError, + }, + ]; + }, + }; + } + }); + }, + navigator: { + navigate({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + window.location.assign(itemUrl); + } + }, + navigateNewTab({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + const windowReference = window.open(itemUrl, "_blank", "noopener"); + if (windowReference) { + windowReference.focus(); + } + } + }, + navigateNewWindow({ itemUrl }) { + if (itemUrl !== offsetURL(kItemTypeMoreHref)) { + window.open(itemUrl, "_blank", "noopener"); + } + }, + }, + getSources({ state, setContext, setActiveItemId, refresh }) { + return [ + { + sourceId: "documents", + getItemUrl({ item }) { + if (item.href) { + return offsetURL(item.href); + } else { + return undefined; + } + }, + onSelect({ + item, + state, + setContext, + setIsOpen, + setActiveItemId, + refresh, + }) { + if (item.type === kItemTypeMore) { + toggleExpanded(item, state, setContext, setActiveItemId, refresh); + + // Toggle more + setIsOpen(true); + } + }, + getItems({ query }) { + if (query === null || query === "") { + return []; + } + + const limit = quartoSearchOptions.limit; + if (quartoSearchOptions.algolia) { + return algoliaSearch(query, limit, quartoSearchOptions.algolia); + } else { + // Fuse search options + const fuseSearchOptions = { + isCaseSensitive: false, + shouldSort: true, + minMatchCharLength: 2, + limit: limit, + }; + + return readSearchData().then(function (fuse) { + return fuseSearch(query, fuse, fuseSearchOptions); + }); + } + }, + templates: { + noResults({ createElement }) { + const hasQuery = lastState.query; + + return createElement( + "div", + { + class: `quarto-search-no-results${ + hasQuery ? "" : " no-query" + }`, + }, + language["search-no-results-text"] + ); + }, + header({ items, createElement }) { + // count the documents + const count = items.filter((item) => { + return item.type === kItemTypeDoc; + }).length; + + if (count > 0) { + return createElement( + "div", + { class: "search-result-header" }, + `${count} ${language["search-matching-documents-text"]}` + ); + } else { + return createElement( + "div", + { class: "search-result-header-no-results" }, + `` + ); + } + }, + footer({ _items, createElement }) { + if ( + quartoSearchOptions.algolia && + quartoSearchOptions.algolia["show-logo"] + ) { + const libDir = quartoSearchOptions.algolia["libDir"]; + const logo = createElement("img", { + src: offsetURL( + `${libDir}/quarto-search/search-by-algolia.svg` + ), + class: "algolia-search-logo", + }); + return createElement( + "a", + { href: "http://www.algolia.com/" }, + logo + ); + } + }, + + item({ item, createElement }) { + return renderItem( + item, + createElement, + state, + setActiveItemId, + setContext, + refresh + ); + }, + }, + }, + ]; + }, + }); + + window.quartoOpenSearch = () => { + setIsOpen(false); + setIsOpen(true); + focusSearchInput(); + }; + + document.addEventListener("keyup", (event) => { + const { key } = event; + const kbds = quartoSearchOptions["keyboard-shortcut"]; + if (kbds && kbds.includes(key)) { + event.preventDefault(); + window.quartoOpenSearch(); + } + }); + + // Remove the labeleledby attribute since it is pointing + // to a non-existent label + if (quartoSearchOptions.type === "overlay") { + const inputEl = window.document.querySelector( + "#quarto-search .aa-Autocomplete" + ); + if (inputEl) { + inputEl.removeAttribute("aria-labelledby"); + } + } + + // If the main document scrolls dismiss the search results + // (otherwise, since they're floating in the document they can scroll with the document) + window.document.body.onscroll = () => { + setIsOpen(false); + }; + + if (showSearchResults) { + setIsOpen(true); + focusSearchInput(); + } +}); + +function configurePlugins(quartoSearchOptions) { + const autocompletePlugins = []; + const algoliaOptions = quartoSearchOptions.algolia; + if ( + algoliaOptions && + algoliaOptions["analytics-events"] && + algoliaOptions["search-only-api-key"] && + algoliaOptions["application-id"] + ) { + const apiKey = algoliaOptions["search-only-api-key"]; + const appId = algoliaOptions["application-id"]; + + // Aloglia insights may not be loaded because they require cookie consent + // Use deferred loading so events will start being recorded when/if consent + // is granted. + const algoliaInsightsDeferredPlugin = deferredLoadPlugin(() => { + if ( + window.aa && + window["@algolia/autocomplete-plugin-algolia-insights"] + ) { + window.aa("init", { + appId, + apiKey, + useCookie: true, + }); + + const { createAlgoliaInsightsPlugin } = + window["@algolia/autocomplete-plugin-algolia-insights"]; + // Register the insights client + const algoliaInsightsPlugin = createAlgoliaInsightsPlugin({ + insightsClient: window.aa, + onItemsChange({ insights, insightsEvents }) { + const events = insightsEvents.map((event) => { + const maxEvents = event.objectIDs.slice(0, 20); + return { + ...event, + objectIDs: maxEvents, + }; + }); + + insights.viewedObjectIDs(...events); + }, + }); + return algoliaInsightsPlugin; + } + }); + + // Add the plugin + autocompletePlugins.push(algoliaInsightsDeferredPlugin); + return autocompletePlugins; + } +} + +// For plugins that may not load immediately, create a wrapper +// plugin and forward events and plugin data once the plugin +// is initialized. This is useful for cases like cookie consent +// which may prevent the analytics insights event plugin from initializing +// immediately. +function deferredLoadPlugin(createPlugin) { + let plugin = undefined; + let subscribeObj = undefined; + const wrappedPlugin = () => { + if (!plugin && subscribeObj) { + plugin = createPlugin(); + if (plugin && plugin.subscribe) { + plugin.subscribe(subscribeObj); + } + } + return plugin; + }; + + return { + subscribe: (obj) => { + subscribeObj = obj; + }, + onStateChange: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onStateChange) { + plugin.onStateChange(obj); + } + }, + onSubmit: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onSubmit) { + plugin.onSubmit(obj); + } + }, + onReset: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.onReset) { + plugin.onReset(obj); + } + }, + getSources: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.getSources) { + return plugin.getSources(obj); + } else { + return Promise.resolve([]); + } + }, + data: (obj) => { + const plugin = wrappedPlugin(); + if (plugin && plugin.data) { + plugin.data(obj); + } + }, + }; +} + +function validateItems(items) { + // Validate the first item + if (items.length > 0) { + const item = items[0]; + const missingFields = []; + if (item.href == undefined) { + missingFields.push("href"); + } + if (!item.title == undefined) { + missingFields.push("title"); + } + if (!item.text == undefined) { + missingFields.push("text"); + } + + if (missingFields.length === 1) { + throw { + name: `Error: Search index is missing the ${missingFields[0]} field.`, + message: `The items being returned for this search do not include all the required fields. Please ensure that your index items include the ${missingFields[0]} field or use index-fields in your _quarto.yml file to specify the field names.`, + }; + } else if (missingFields.length > 1) { + const missingFieldList = missingFields + .map((field) => { + return `${field}`; + }) + .join(", "); + + throw { + name: `Error: Search index is missing the following fields: ${missingFieldList}.`, + message: `The items being returned for this search do not include all the required fields. Please ensure that your index items includes the following fields: ${missingFieldList}, or use index-fields in your _quarto.yml file to specify the field names.`, + }; + } + } +} + +let lastQuery = null; +function showCopyLink(query, options) { + const language = options.language; + lastQuery = query; + // Insert share icon + const inputSuffixEl = window.document.body.querySelector( + ".aa-Form .aa-InputWrapperSuffix" + ); + + if (inputSuffixEl) { + let copyButtonEl = window.document.body.querySelector( + ".aa-Form .aa-InputWrapperSuffix .aa-CopyButton" + ); + + if (copyButtonEl === null) { + copyButtonEl = window.document.createElement("button"); + copyButtonEl.setAttribute("class", "aa-CopyButton"); + copyButtonEl.setAttribute("type", "button"); + copyButtonEl.setAttribute("title", language["search-copy-link-title"]); + copyButtonEl.onmousedown = (e) => { + e.preventDefault(); + e.stopPropagation(); + }; + + const linkIcon = "bi-clipboard"; + const checkIcon = "bi-check2"; + + const shareIconEl = window.document.createElement("i"); + shareIconEl.setAttribute("class", `bi ${linkIcon}`); + copyButtonEl.appendChild(shareIconEl); + inputSuffixEl.prepend(copyButtonEl); + + const clipboard = new window.ClipboardJS(".aa-CopyButton", { + text: function (_trigger) { + const copyUrl = new URL(window.location); + copyUrl.searchParams.set(kQueryArg, lastQuery); + copyUrl.searchParams.set(kResultsArg, "1"); + return copyUrl.toString(); + }, + }); + clipboard.on("success", function (e) { + // Focus the input + + // button target + const button = e.trigger; + const icon = button.querySelector("i.bi"); + + // flash "checked" + icon.classList.add(checkIcon); + icon.classList.remove(linkIcon); + setTimeout(function () { + icon.classList.remove(checkIcon); + icon.classList.add(linkIcon); + }, 1000); + }); + } + + // If there is a query, show the link icon + if (copyButtonEl) { + if (lastQuery && options["copy-button"]) { + copyButtonEl.style.display = "flex"; + } else { + copyButtonEl.style.display = "none"; + } + } + } +} + +/* Search Index Handling */ +// create the index +var fuseIndex = undefined; +async function readSearchData() { + // Initialize the search index on demand + if (fuseIndex === undefined) { + // create fuse index + const options = { + keys: [ + { name: "title", weight: 20 }, + { name: "section", weight: 20 }, + { name: "text", weight: 10 }, + ], + ignoreLocation: true, + threshold: 0.1, + }; + const fuse = new window.Fuse([], options); + + // fetch the main search.json + const response = await fetch(offsetURL("search.json")); + if (response.status == 200) { + return response.json().then(function (searchDocs) { + searchDocs.forEach(function (searchDoc) { + fuse.add(searchDoc); + }); + fuseIndex = fuse; + return fuseIndex; + }); + } else { + return Promise.reject( + new Error( + "Unexpected status from search index request: " + response.status + ) + ); + } + } + return fuseIndex; +} + +function inputElement() { + return window.document.body.querySelector(".aa-Form .aa-Input"); +} + +function focusSearchInput() { + setTimeout(() => { + const inputEl = inputElement(); + if (inputEl) { + inputEl.focus(); + } + }, 50); +} + +/* Panels */ +const kItemTypeDoc = "document"; +const kItemTypeMore = "document-more"; +const kItemTypeItem = "document-item"; +const kItemTypeError = "error"; + +function renderItem( + item, + createElement, + state, + setActiveItemId, + setContext, + refresh +) { + switch (item.type) { + case kItemTypeDoc: + return createDocumentCard( + createElement, + "file-richtext", + item.title, + item.section, + item.text, + item.href + ); + case kItemTypeMore: + return createMoreCard( + createElement, + item, + state, + setActiveItemId, + setContext, + refresh + ); + case kItemTypeItem: + return createSectionCard( + createElement, + item.section, + item.text, + item.href + ); + case kItemTypeError: + return createErrorCard(createElement, item.title, item.text); + default: + return undefined; + } +} + +function createDocumentCard(createElement, icon, title, section, text, href) { + const iconEl = createElement("i", { + class: `bi bi-${icon} search-result-icon`, + }); + const titleEl = createElement("p", { class: "search-result-title" }, title); + const titleContainerEl = createElement( + "div", + { class: "search-result-title-container" }, + [iconEl, titleEl] + ); + + const textEls = []; + if (section) { + const sectionEl = createElement( + "p", + { class: "search-result-section" }, + section + ); + textEls.push(sectionEl); + } + const descEl = createElement("p", { + class: "search-result-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + textEls.push(descEl); + + const textContainerEl = createElement( + "div", + { class: "search-result-text-container" }, + textEls + ); + + const containerEl = createElement( + "div", + { + class: "search-result-container", + }, + [titleContainerEl, textContainerEl] + ); + + const linkEl = createElement( + "a", + { + href: offsetURL(href), + class: "search-result-link", + }, + containerEl + ); + + const classes = ["search-result-doc", "search-item"]; + if (!section) { + classes.push("document-selectable"); + } + + return createElement( + "div", + { + class: classes.join(" "), + }, + linkEl + ); +} + +function createMoreCard( + createElement, + item, + state, + setActiveItemId, + setContext, + refresh +) { + const moreCardEl = createElement( + "div", + { + class: "search-result-more search-item", + onClick: (e) => { + // Handle expanding the sections by adding the expanded + // section to the list of expanded sections + toggleExpanded(item, state, setContext, setActiveItemId, refresh); + e.stopPropagation(); + }, + }, + item.title + ); + + return moreCardEl; +} + +function toggleExpanded(item, state, setContext, setActiveItemId, refresh) { + const expanded = state.context.expanded || []; + if (expanded.includes(item.target)) { + setContext({ + expanded: expanded.filter((target) => target !== item.target), + }); + } else { + setContext({ expanded: [...expanded, item.target] }); + } + + refresh(); + setActiveItemId(item.__autocomplete_id); +} + +function createSectionCard(createElement, section, text, href) { + const sectionEl = createSection(createElement, section, text, href); + return createElement( + "div", + { + class: "search-result-doc-section search-item", + }, + sectionEl + ); +} + +function createSection(createElement, title, text, href) { + const descEl = createElement("p", { + class: "search-result-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + + const titleEl = createElement("p", { class: "search-result-section" }, title); + const linkEl = createElement( + "a", + { + href: offsetURL(href), + class: "search-result-link", + }, + [titleEl, descEl] + ); + return linkEl; +} + +function createErrorCard(createElement, title, text) { + const descEl = createElement("p", { + class: "search-error-text", + dangerouslySetInnerHTML: { + __html: text, + }, + }); + + const titleEl = createElement("p", { + class: "search-error-title", + dangerouslySetInnerHTML: { + __html: ` ${title}`, + }, + }); + const errorEl = createElement("div", { class: "search-error" }, [ + titleEl, + descEl, + ]); + return errorEl; +} + +function positionPanel(pos) { + const panelEl = window.document.querySelector( + "#quarto-search-results .aa-Panel" + ); + const inputEl = window.document.querySelector( + "#quarto-search .aa-Autocomplete" + ); + + if (panelEl && inputEl) { + panelEl.style.top = `${Math.round(panelEl.offsetTop)}px`; + if (pos === "start") { + panelEl.style.left = `${Math.round(inputEl.left)}px`; + } else { + panelEl.style.right = `${Math.round(inputEl.offsetRight)}px`; + } + } +} + +/* Highlighting */ +// highlighting functions +function highlightMatch(query, text) { + if (text) { + const start = text.toLowerCase().indexOf(query.toLowerCase()); + if (start !== -1) { + const startMark = ""; + const endMark = ""; + + const end = start + query.length; + text = + text.slice(0, start) + + startMark + + text.slice(start, end) + + endMark + + text.slice(end); + const startInfo = clipStart(text, start); + const endInfo = clipEnd( + text, + startInfo.position + startMark.length + endMark.length + ); + text = + startInfo.prefix + + text.slice(startInfo.position, endInfo.position) + + endInfo.suffix; + + return text; + } else { + return text; + } + } else { + return text; + } +} + +function clipStart(text, pos) { + const clipStart = pos - 50; + if (clipStart < 0) { + // This will just return the start of the string + return { + position: 0, + prefix: "", + }; + } else { + // We're clipping before the start of the string, walk backwards to the first space. + const spacePos = findSpace(text, pos, -1); + return { + position: spacePos.position, + prefix: "", + }; + } +} + +function clipEnd(text, pos) { + const clipEnd = pos + 200; + if (clipEnd > text.length) { + return { + position: text.length, + suffix: "", + }; + } else { + const spacePos = findSpace(text, clipEnd, 1); + return { + position: spacePos.position, + suffix: spacePos.clipped ? "…" : "", + }; + } +} + +function findSpace(text, start, step) { + let stepPos = start; + while (stepPos > -1 && stepPos < text.length) { + const char = text[stepPos]; + if (char === " " || char === "," || char === ":") { + return { + position: step === 1 ? stepPos : stepPos - step, + clipped: stepPos > 1 && stepPos < text.length, + }; + } + stepPos = stepPos + step; + } + + return { + position: stepPos - step, + clipped: false, + }; +} + +// removes highlighting as implemented by the mark tag +function clearHighlight(searchterm, el) { + const childNodes = el.childNodes; + for (let i = childNodes.length - 1; i >= 0; i--) { + const node = childNodes[i]; + if (node.nodeType === Node.ELEMENT_NODE) { + if ( + node.tagName === "MARK" && + node.innerText.toLowerCase() === searchterm.toLowerCase() + ) { + el.replaceChild(document.createTextNode(node.innerText), node); + } else { + clearHighlight(searchterm, node); + } + } + } +} + +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string +} + +// highlight matches +function highlight(term, el) { + const termRegex = new RegExp(term, "ig"); + const childNodes = el.childNodes; + + // walk back to front avoid mutating elements in front of us + for (let i = childNodes.length - 1; i >= 0; i--) { + const node = childNodes[i]; + + if (node.nodeType === Node.TEXT_NODE) { + // Search text nodes for text to highlight + const text = node.nodeValue; + + let startIndex = 0; + let matchIndex = text.search(termRegex); + if (matchIndex > -1) { + const markFragment = document.createDocumentFragment(); + while (matchIndex > -1) { + const prefix = text.slice(startIndex, matchIndex); + markFragment.appendChild(document.createTextNode(prefix)); + + const mark = document.createElement("mark"); + mark.appendChild( + document.createTextNode( + text.slice(matchIndex, matchIndex + term.length) + ) + ); + markFragment.appendChild(mark); + + startIndex = matchIndex + term.length; + matchIndex = text.slice(startIndex).search(new RegExp(term, "ig")); + if (matchIndex > -1) { + matchIndex = startIndex + matchIndex; + } + } + if (startIndex < text.length) { + markFragment.appendChild( + document.createTextNode(text.slice(startIndex, text.length)) + ); + } + + el.replaceChild(markFragment, node); + } + } else if (node.nodeType === Node.ELEMENT_NODE) { + // recurse through elements + highlight(term, node); + } + } +} + +/* Link Handling */ +// get the offset from this page for a given site root relative url +function offsetURL(url) { + var offset = getMeta("quarto:offset"); + return offset ? offset + url : url; +} + +// read a meta tag value +function getMeta(metaName) { + var metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; +} + +function algoliaSearch(query, limit, algoliaOptions) { + const { getAlgoliaResults } = window["@algolia/autocomplete-preset-algolia"]; + + const applicationId = algoliaOptions["application-id"]; + const searchOnlyApiKey = algoliaOptions["search-only-api-key"]; + const indexName = algoliaOptions["index-name"]; + const indexFields = algoliaOptions["index-fields"]; + const searchClient = window.algoliasearch(applicationId, searchOnlyApiKey); + const searchParams = algoliaOptions["params"]; + const searchAnalytics = !!algoliaOptions["analytics-events"]; + + return getAlgoliaResults({ + searchClient, + queries: [ + { + indexName: indexName, + query, + params: { + hitsPerPage: limit, + clickAnalytics: searchAnalytics, + ...searchParams, + }, + }, + ], + transformResponse: (response) => { + if (!indexFields) { + return response.hits.map((hit) => { + return hit.map((item) => { + return { + ...item, + text: highlightMatch(query, item.text), + }; + }); + }); + } else { + const remappedHits = response.hits.map((hit) => { + return hit.map((item) => { + const newItem = { ...item }; + ["href", "section", "title", "text"].forEach((keyName) => { + const mappedName = indexFields[keyName]; + if ( + mappedName && + item[mappedName] !== undefined && + mappedName !== keyName + ) { + newItem[keyName] = item[mappedName]; + delete newItem[mappedName]; + } + }); + newItem.text = highlightMatch(query, newItem.text); + return newItem; + }); + }); + return remappedHits; + } + }, + }); +} + +function fuseSearch(query, fuse, fuseOptions) { + return fuse.search(query, fuseOptions).map((result) => { + const addParam = (url, name, value) => { + const anchorParts = url.split("#"); + const baseUrl = anchorParts[0]; + const sep = baseUrl.search("\\?") > 0 ? 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https://openpipelines.bio/team/malte_d_luecken/index.html + 2023-09-06T15:28:58.857Z + + + https://openpipelines.bio/team/dries_schaumont/index.html + 2023-09-06T15:28:58.857Z + + diff --git a/pr-preview/pr-51/styles.css b/pr-preview/pr-51/styles.css new file mode 100644 index 00000000..ab530325 --- /dev/null +++ b/pr-preview/pr-51/styles.css @@ -0,0 +1,57 @@ +/* css styles */ + +h1, h2 { + margin-top: 0; + border-bottom: 0; +} + +h1 { + font-size: 1.6rem; +} + +h2 { + font-size: 1.2rem; +} + +header > .quarto-title h1 { + font-size: 2.5rem; + font-weight: 800; + +} + +#navbarCollapse { + background-color: #ffffff; +} + +#quarto-header nav.navbar { + height: 4rem; + padding: 0; +} + +a.navbar-brand-logo > img { + max-height: 2.5rem; + margin: 2rem; +} + +.mermaid svg { + display: block; + margin: auto; +} +.cluster-label { + padding-bottom: 60px; + +} + +#fig-architecture path[class*="LS-titlebox"] { + display: none; + +} + +#fig-architecture .nodes > g[id*="titlebox"] > rect.label-container { + fill: none; + stroke: none; +} + +.home .title { + text-align: center; +} \ No newline at end of file diff --git a/pr-preview/pr-51/team/angela_oliveira_pisco/index.html b/pr-preview/pr-51/team/angela_oliveira_pisco/index.html new file mode 100644 index 00000000..5d8cad7d --- /dev/null +++ b/pr-preview/pr-51/team/angela_oliveira_pisco/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Angela Oliveira Pisco + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Angela Oliveira Pisco

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/dries_de_maeyer/index.html b/pr-preview/pr-51/team/dries_de_maeyer/index.html new file mode 100644 index 00000000..e70b5669 --- /dev/null +++ b/pr-preview/pr-51/team/dries_de_maeyer/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Dries De Maeyer + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Dries De Maeyer

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Dries Schaumont

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/index.html b/pr-preview/pr-51/team/index.html new file mode 100644 index 00000000..fae5839f --- /dev/null +++ b/pr-preview/pr-51/team/index.html @@ -0,0 +1,850 @@ + + + + + + + + + +OpenPipelines - Team + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Team

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+

Angela Oliveira Pisco

+
Contributor
+ + + + + + + + + +
+ + Director of Computational Biology + at + + Insitro + + +
+
+ + Core Member + at + + Open Problems + + +
+
+
+
+ +
+

Dries De Maeyer

+
Core Team Member
+ + + + + + + + + +
+ + Principal Scientist + at + + Janssen Pharmaceuticals + + +
+
+
+
+ +
+

Dries Schaumont

+
Core Team Member
+ + + + + + + + + + + + +
+ + Data Scientist + at + + Data Intuitive + + +
+
+
+
+ +
+

Malte D. Luecken

+
Core Team Member
+ + + + + + + + + + + + +
+ + Group Leader + at + + Helmholtz Munich + + +
+
+ + Core Member + at + + Open Problems + + +
+
+
+
+ +
+

Marijke Van Moerbeke

+
Contributor
+ + + + + + +
+ + Statistical Consultant + at + + OpenAnalytics + + +
+
+
+
+ +
+

Matthias Beyens

+
Contributor
+ + + + + + + + + + + + +
+ + Principal Scientist + at + + Janssen Pharmaceuticals + + +
+
+
+
+ +
+

Mauro Saporita

+
Contributor
+ + + + + + + + + +
+ + Lead Nextflow Developer + at + + Ardigen + + +
+
+
+
+ +
+

Povilas Gibas

+
Contributor
+ + + + + + + + + +
+ + Bioinformatician + at + + Ardigen + + +
+
+
+
+ +
+

Robrecht Cannoodt

+
Core Team Member
+ + + + + + + + + + + + +
+ + Data Science Engineer + at + + Data Intuitive + + +
+
+ + Core Member + at + + Open Problems + + +
+
+
+
+ +
+

Samuel D'Souza

+
Contributor
+ + + + + + +
+ + Data Engineer + at + + Chan Zuckerberg Biohub + + +
+
+
+
+ +
+

Toni Verbeiren

+
Core Team Member
+ + + + + + +
+ + Data Scientist and CEO + at + + Data Intuitive + + +
+
+
+
+ +
+

Vladimir Shitov

+
Contributor
+ + + + + + + + + + + + +
+ + PhD Candidate + at + + Helmholtz Munich + + +
+
+
+
+
+No matching items +
+
+ + + + +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/malte_d_luecken/index.html b/pr-preview/pr-51/team/malte_d_luecken/index.html new file mode 100644 index 00000000..19c08325 --- /dev/null +++ b/pr-preview/pr-51/team/malte_d_luecken/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Malte D. Luecken + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Malte D. Luecken

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/marijke_van_moerbeke/index.html b/pr-preview/pr-51/team/marijke_van_moerbeke/index.html new file mode 100644 index 00000000..649becbf --- /dev/null +++ b/pr-preview/pr-51/team/marijke_van_moerbeke/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Marijke Van Moerbeke + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Marijke Van Moerbeke

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/matthias_beyens/index.html b/pr-preview/pr-51/team/matthias_beyens/index.html new file mode 100644 index 00000000..eacbcacd --- /dev/null +++ b/pr-preview/pr-51/team/matthias_beyens/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Matthias Beyens + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Matthias Beyens

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/mauro_saporita/index.html b/pr-preview/pr-51/team/mauro_saporita/index.html new file mode 100644 index 00000000..f2813803 --- /dev/null +++ b/pr-preview/pr-51/team/mauro_saporita/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Mauro Saporita + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Mauro Saporita

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/povilas_gibas/index.html b/pr-preview/pr-51/team/povilas_gibas/index.html new file mode 100644 index 00000000..a9413f44 --- /dev/null +++ b/pr-preview/pr-51/team/povilas_gibas/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Povilas Gibas + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Povilas Gibas

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/robrecht_cannoodt/index.html b/pr-preview/pr-51/team/robrecht_cannoodt/index.html new file mode 100644 index 00000000..40f0c705 --- /dev/null +++ b/pr-preview/pr-51/team/robrecht_cannoodt/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Robrecht Cannoodt + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Robrecht Cannoodt

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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/samuel_dsouza/index.html b/pr-preview/pr-51/team/samuel_dsouza/index.html new file mode 100644 index 00000000..d62afeeb --- /dev/null +++ b/pr-preview/pr-51/team/samuel_dsouza/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Samuel D’Souza + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Samuel D’Souza

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+ + +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/team.css b/pr-preview/pr-51/team/team.css new file mode 100644 index 00000000..100ffefc --- /dev/null +++ b/pr-preview/pr-51/team/team.css @@ -0,0 +1,70 @@ +/* css styles */ +.people-person { + background: none; + border: none; + flex-basis: 250px; +} + +.people-widget { + font-size: 0.8rem; + text-align: center; + display: flex; + flex-wrap: wrap; + gap: 1.5em; + padding-top: 1em; +} + +.people-widget .portrait-title h2 { + font-size: 1rem; +} + +.people-widget .portrait-title h3 { + font-size: 0.7rem; +} + +.people-widget .avatar { + width: 80%; + max-width: 150px; + max-height: 150px; + object-fit: cover; + height: auto; + margin: 0 auto; +} + +@media (min-width: 576px) { + .people-widget .col-sm-auto { + width: 30%; + } +} +@media (min-width: 992px) { + .people-widget .col-sm-auto { + width: 20%; + } +} + +.avatar-circle { + border-radius: 50%; +} + +.avatar-square { + border-radius: 3px; +} + +.portrait-title h5 { + font-size: 1.4em; + font-weight: 300; + color: var(--bs-body-color); + margin: 20px 0 10px; +} + +.portrait-title h6 { + font-size: 1rem; + font-weight: 300; + color: var(--bs-secondary-text-color); + margin: 0 0 10px; +} + +.network-icon { + margin: 0.1em; + text-decoration: none; +} diff --git a/pr-preview/pr-51/team/toni_verbeiren/index.html b/pr-preview/pr-51/team/toni_verbeiren/index.html new file mode 100644 index 00000000..5b529bb2 --- /dev/null +++ b/pr-preview/pr-51/team/toni_verbeiren/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Toni Verbeiren + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + + + +
+ +
+
+

Toni Verbeiren

+
+
+
+
+ + +
+
+ + +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/team/vladimir_shitov/index.html b/pr-preview/pr-51/team/vladimir_shitov/index.html new file mode 100644 index 00000000..213c8400 --- /dev/null +++ b/pr-preview/pr-51/team/vladimir_shitov/index.html @@ -0,0 +1,463 @@ + + + + + + + + + +OpenPipelines - Vladimir Shitov + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ +
+ +
+ + + + +
+ +
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+

Vladimir Shitov

+
+
+
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+ + +
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+ + +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/user_guide/bug_reports.html b/pr-preview/pr-51/user_guide/bug_reports.html new file mode 100644 index 00000000..a04aeb06 --- /dev/null +++ b/pr-preview/pr-51/user_guide/bug_reports.html @@ -0,0 +1,546 @@ + + + + + + + + + +OpenPipelines - Bug reports + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
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+ +
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Bug reports

+
+ + + +
+ + + + +
+ + +
+ +

Issues with Openpipelines are being tracked on Github. In order for an issue to be fixed in a timely manner, creating a complete and reproducable is essential.

+ + + +
+ +
+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/user_guide/downstream.html b/pr-preview/pr-51/user_guide/downstream.html new file mode 100644 index 00000000..9dbf3d4a --- /dev/null +++ b/pr-preview/pr-51/user_guide/downstream.html @@ -0,0 +1,551 @@ + + + + + + + + + + +OpenPipelines - Downstream + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Downstream

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+ +
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+ Celltyping and cell-cell communication +
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Getting started

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User Guide

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+ + + +
+ + + + +
+ + +
+ +
+

Which workflow is right for me

+
+
+

Executing pipelines or build components

+
+

Using the nf-tower user-interface

+
+
+

Using the nf-tower CLI (tw)

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Using the nextflow CLI

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© OpenPipelines.bio 2022

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+ + + + \ No newline at end of file diff --git a/pr-preview/pr-51/user_guide/ingestion.html b/pr-preview/pr-51/user_guide/ingestion.html new file mode 100644 index 00000000..1d436806 --- /dev/null +++ b/pr-preview/pr-51/user_guide/ingestion.html @@ -0,0 +1,551 @@ + + + + + + + + + + +OpenPipelines - Ingestion + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Ingestion

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+ +
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+ From sequencing to count tables +
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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/user_guide/processing.html b/pr-preview/pr-51/user_guide/processing.html new file mode 100644 index 00000000..b2cb9b24 --- /dev/null +++ b/pr-preview/pr-51/user_guide/processing.html @@ -0,0 +1,551 @@ + + + + + + + + + + +OpenPipelines - Processing + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Processing

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+ +
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+ From count tables to integrated data +
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+ + + + + \ No newline at end of file diff --git a/pr-preview/pr-51/user_guide/running_pipelines.html b/pr-preview/pr-51/user_guide/running_pipelines.html new file mode 100644 index 00000000..22e99306 --- /dev/null +++ b/pr-preview/pr-51/user_guide/running_pipelines.html @@ -0,0 +1,640 @@ + + + + + + + + + +OpenPipelines - Running pipelines + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ +
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Running pipelines

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+ +
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+Note +
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TODO: Fill in these sections.

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    +
  • Examples should be using an OpenPipelines release or the main_build branch.
    • +
  • Point to the “Components” tab
    • +
+
+
+
+

Installing Viash and Nextflow

+

Before you try running OpenPipelines, please install Viash and Nextflow first.

+
+

Running pipelines from the CLI

+
bin/nextflow run . \
+  -main-script workflows/integration/multimodal_integration/main.nf \
+  -profile docker \
+  -resume 
+  --publish_dir foo/
+  --input "bar"
+  --output "test.txt"
+
+
+

Running pipelines from Nextflow Tower

+
+
+

Using param_list to pass large parameter sets

+

Using Viash’s VDSL3 nextflow platform, an optional -param_list argument can be used to pass a large number of inputs to a workflow. Additionally, the pipeline parameter values can be set for each input to the workflow independently. A param_list can either be a list of maps, a csv file, a json file, a yaml file, or simply a yaml blob:

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  • A csv file should have column names which correspond to the different arguments of this pipeline. Example: --param_list data.csv with columns id,input.
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  • A json or a yaml file should be a list of maps, each of which has keys corresponding to the arguments of the pipeline. Example: --param_list data.json with contents [ {'id': 'foo', 'input': 'foo.txt'}, {'id': 'bar', 'input': 'bar.txt'} ].
    • +
  • A yaml blob can also be passed directly as a string. Example: --param_list "[ {'id': 'foo', 'input': 'foo.txt'}, {'id': 'bar', 'input': 'bar.txt'} ]".
    • +
  • A list of maps can be in a nextflow.config file, where the keys of each map corresponds to the arguments of the pipeline. Example in a nextflow.config file: param_list: [ ['id': 'foo', 'input': 'foo.txt'], ['id': 'bar', 'input': 'bar.txt'] ].
    • +
+

When passing a csv, json or yaml file, relative path names are relativized to the location of the parameter file. No relativation is performed when param_list is a list of maps (as-is) or a yaml blob.

+

Using a param_list can be combined with setting parameters that are set for all parameter sets. These ‘gobal’ parameters will always be overwritten with their counterpart that was specified in a more specific manner for a single parameter set. For example, using --param_list "[ {'id': 'foo', 'input': 'foo.txt'}, {'id': 'bar'} ]" --input 'global.txt' will result in the following parameter sets being processed:

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    +
  • id: foo, input: foo.txt
    • +
  • id: bar, input: global.txt
    • +
+ + +
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+ +
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+

© OpenPipelines.bio 2022

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+ + + + \ No newline at end of file

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