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LouisLeNezet committed Jun 14, 2024
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The **phaseimpute** pipeline is constituted of 5 main steps:

| Metro map | Modes |
| ---------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| <img src="docs/images/metro/MetroMap.png" alt="metromap" width="800"/> | - **Pre-processing**: Phasing, QC, variant filtering, variant annotation of the reference panel <br> - **Phase**: Phasing of the target dataset on the reference panel <br> - **Simulate**: Simulation of the target dataset from high quality target data <br> - **Concordance**: Concordance between the target dataset and a truth dataset <br> - **Post-processing**: Variant filtering based on their imputation quality |
| Metro map | Modes |
| ---------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| <img src="docs/images/metro/MetroMap.png" alt="metromap" width="800"/> | - **Panel preparation**: Phasing, QC, variant filtering, variant annotation of the reference panel <br> - **Imputation**: Impute the target dataset on the reference panel <br> - **Simulate**: Simulation of the target dataset from high quality target data <br> - **Concordance**: Concordance between the target dataset and a truth dataset |

## Usage

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A final samplesheet file for the reference panel may look something like the one below. This is for 3 chromosomes.

```console
```csv
chr,vcf
1,ALL.chr1.phase3_shapeit2_mvncall_integrated_v5a.20130502.genotypes.vcf.gz
2,ALL.chr2.phase3_shapeit2_mvncall_integrated_v5a.20130502.genotypes.vcf.gz
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Here is a short description of the different steps of the pipeline.
For more information please refer to the [documentation](https://nf-core.github.io/phaseimpute/usage/).

| steps | Flow chart | Description |
| ------------------ | ---------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Panel prep** | <img src="docs/images/metro/PreProcessing.png" alt="phase_metro" width="600"/> | The preprocessing mode is responsible to the preparation of the multiple input file that will be used by the phasing process. <br> The main processes are : <br> - **Haplotypes phasing** of the reference panel using [**Shapeit5**](https://odelaneau.github.io/shapeit5/). <br> - **Filter** the reference panel to select only the necessary variants. <br> - **Chunking the reference panel** in a subset of region for all the chromosomes. <br> - **Extract** the positions where to perform the imputation. |
| **Impute** | <img src="docs/images/metro/Phase.png" alt="phase_metro" width="600"/> | The imputation mode is the core mode of this pipeline. <br> It is constituted of 3 main steps: <br> - **Phasing**: Phasing of the target dataset on the reference panel using either: <br> &emsp; - [**Glimpse1**](https://odelaneau.github.io/GLIMPSE/glimpse1/index.html) <br> &emsp; It's come with the necessety to compute the genotype likelihoods of the target dataset. <br> &emsp; This steps is done using [BCFTOOLS_mpileup](https://samtools.github.io/bcftools/bcftools.html#mpileup) <br> &emsp; - [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) For this steps the reference panel is transformed to binary chunks. <br> &emsp; - [**Stitch**](https://github.com/rwdavies/stitch) <br> &emsp; - [**Quilt**](https://github.com/rwdavies/QUILT) <br> - **Ligation**: all the different chunks are merged together. <br> - **Sampling** (optional) |
| **Simulate** | <img src="docs/images/metro/Simulate.png" alt="simulate_metro" width="600"/> | The simulation mode is used to create artificial low informative genetic information from high density data. This allow to compare the imputed result to a _truth_ and therefore evaluate the quality of the imputation. <br> For the moment it is possible to simulate: <br> - Low-pass data by **downsample** BAM or CRAM using [SAMTOOLS_view -s]() at different depth <br> - Genotype data by **SNP selecting** the position used by a designated SNP chip. <br> The simulation mode will also compute the **Genotype likelihoods** of the high density data. |
| **Validate** | <img src="docs/images/metro/Concordance.png" alt="concordance_metro" width="600"/> | This mode compare two vcf together to compute a summary of the differences between them. <br> To do so it use either: <br> - [**Glimpse1**](https://odelaneau.github.io/GLIMPSE/glimpse1/index.html) concordance process. <br> - [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) concordance process <br> - Or convert the two vcf fill to `.zarr` using [**Scikit allele**](https://scikit-allel.readthedocs.io/en/stable/) and [**anndata**](https://anndata.readthedocs.io/en/latest/) before comparing the SNPs. |
| **Postprocessing** | <img src="docs/images/metro/PostProcessing.png" alt="postprocessing_metro" width="600"/> | This final process unable to loop the whole pipeline for increasing the performance of the imputation. To do so it filter out the best imputed position and rerun the analysis using this positions [to be developed]. |
| steps | Flow chart | Description |
| --------------- | -------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **--panelprep** | <img src="docs/images/metro/PanelPrep.png" alt="Panel preparation" width="600"/> | The preprocessing mode is responsible to the preparation of the multiple input file that will be used by the phasing process. <br> The main processes are : <br> - **Haplotypes phasing** of the reference panel using [**Shapeit5**](https://odelaneau.github.io/shapeit5/). <br> - **Normalize** the reference panel to select only the necessary variants. <br> - **Chunking the reference panel** in a subset of region for all the chromosomes. <br> - **Extract** the positions where to perform the imputation. |
| **--impute** | <img src="docs/images/metro/Impute.png" alt="Impute target" width="600"/> | The imputation mode is the core mode of this pipeline. <br> It is constituted of 3 main steps: <br> - **Imputation**: Impute the target dataset on the reference panel using either: <br> &emsp; - [**Glimpse1**](https://odelaneau.github.io/GLIMPSE/glimpse1/index.html): It's come with the necessety to compute the genotype likelihoods of the target dataset (done using [BCFTOOLS_mpileup](https://samtools.github.io/bcftools/bcftools.html#mpileup)). <br> &emsp; - [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) <br> &emsp; - [**Stitch**](https://github.com/rwdavies/stitch) This steps does not require a reference panel but needs to merge the samples. <br> &emsp; - [**Quilt**](https://github.com/rwdavies/QUILT) <br> - **Ligation**: all the different chunks are merged together then all chromosomes are reunited to output one VCF per sample. |
| **--simulate** | <img src="docs/images/metro/Simulate.png" alt="simulate_metro" width="600"/> | The simulation mode is used to create artificial low informative genetic information from high density data. This allow to compare the imputed result to a _truth_ and therefore evaluate the quality of the imputation. <br> For the moment it is possible to simulate: <br> - Low-pass data by **downsample** BAM or CRAM using [SAMTOOLS_VIEW -s](https://www.htslib.org/doc/samtools-view.html) at different depth. |
| **--validate** | <img src="docs/images/metro/Validate.png" alt="concordance_metro" width="600"/> | This mode compare two vcf together to compute a summary of the differences between them. <br> This step use [**Glimpse2**](https://odelaneau.github.io/GLIMPSE/glimpse2/index.html) concordance process. |

## Pipeline output

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