Anne-Mette Bjerregaard
Department of Bio and Health Informatics
Technical University of Denmark
Lyngby, Denmark.
Personalization of immunotherapies such as cancer vaccines and adoptive T cell therapy
will depend on identification of patient-specific neo-epitopes that can be specifically
targeted. MuPeXI, the Mutant Peptide Extractor and Informer, is a program that uses
somatic mutation data, HLA binding prediction, self-similarity comparison and gene
expression to identify and assess potential neo-epitopes as targets for immunotherapy.
MuPeXI.py extracts peptides of user-defined lengths around missense variant mutations,
indels and frameshifts. Information from each mutation is annotated together with the
mutant and normal peptides in the file output.
To run MuPeXI the following software and packages must be installed:
These packages are included if downloading python through Anaconda; the full anaconda package list can be found here. The Python 2.7 standard library list can be found here. If installing Anaconda it should not be necessary to do the second step of the installation guide.
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Install all software listed above.
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Install Biopython, pandas and nympy with the following command:
pip install biopython pip install numpy pip install pandas -
Download or clone the MuPeXI repository to your local system
git clone https://github.com/ambj/MuPeXI.git -
If not already on your system, reference files from GRCh38 should be obtained. These include cDNA, peptide and cosmic references, look under References (below) for a detailed description.
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Fill in the config.ini file
Instructions on how to fill in the file are found within the file. Theconfig.inifile is automatically detected in the same directory asMuPeXI.pyscript but can also be placed elsewhere and referred to by the-coption.State the path to netMHCpan 3.0 and VEP in the config.ini file.
[netMHC] # Please specify the netMHCpan 3.0 binary path MHC = your/path/to/netMHCpan-3.0/netMHCpan [EnsemblVEP] # Please specify binary path to Ensembls Variant effect predictor (VEP), and the directory of containing the cache database. VEP = your/path/to/ensembl-tools-release-85/scripts/variant_effect_predictor/variant_effect_predictor.pl VEPdir = your/path/to/ensembl-tools-release-85/scripts/variant_effect_predictorYou should be aware that the version of VEP library you use should match the references used (peptide and cDNA). E.g. in the example above is used version/release 85 of GRCh38. The path to reference files should also be stated in the config.ini file, together with FULL path to the small C script named "pepmatch_db" downloaded with MuPeXI. All reference peptides of the defined length, extracted from the proteome reference, can be defined as a file in the config.ini file. This will save time, avoiding chop-up of the proteome reference for each run. As many files as peptides length should be stated, if not stated MuPeXI runs the chop-up for the peptide lengths where no peptide reference file is provided.
[References] # Please specify the binary path to the references used (optional) cDNA = your/path/to/human_GRCh38/cDNA/Homo_sapiens.GRCh38.78.cdna.all.fa pep = your/path/to/human_GRCh38/pep/Homo_sapiens.GRCh38.78.pep.all.fa cosmic = your/path/to/cosmic/Census_allWed_Feb_17_09-33-40_2016.tsv pep9 = your/path/to/reference_peptide_9.txt [PeptideMatch] PM = your/path/to/MuPeXI/apps/pepmatch_dbIf the user wishes for MuPeXI to do a lift-over from GRCh37 / HG19 to GRCh38 this is possible if a local version of picard tools 2.5 is installed. The paths to java8 and picard-tools should also be stated in the config.ini file.
[LiftOver] fasta = your/path/to/references/GRCh38.fa chain = your/path/to/references/HG19toGRCh38.chain java8 = your/path/to/java8 picard = your/path/to/picard-tools-2.5.0
After installation MuPeXI is called as follows. Here is an example where the reference
files are stated in the config.ini file and netMHCpan-3.0 is run for the HLA types
HLA-A01:01 and HLA-B08:01. The config file is specified using the -c option and the
expression file with the -e option.
path/to/MuPeXI.py -v mutation_call_file.vcf -a HLA-A01:01,HLA-B08:01 -c path/to/config.ini -e expression_file.tsv
MuPeXI can be used for both peptide extraction, giving immunogenicity information for peptide selection, and for printing of fasta file mutant-peptide-library for optimal mass spectrometry peptide detection.
All options can be explored using the usage information with the -h option:
> path/to/MuPeXI.py -h
MuPeXI - Mutant Peptide Extractor and Informer
version 2016-08-11
The current version of this program is available from
https://github.com/ambj/MuPeXI
MuPeXI.py accepts a VCF file describing somatic mutations as input, and from this
derives a set of mutated peptides of specified length(s). These mutated peptides
are returned in a table along with various annotations that may be useful for
predicting the immunogenicity of each peptide.
Usage: ./MuPeXI.py -v <VCF-file> [options]
DEFAULT
Required arguments:
-v, --vcf-file <file> VCF file of variant calls, preferably from
MuTect (only SNVs) or MuTect2 (SNVs and indels)
Recommended arguments:
-a, --alleles HLA alleles, comma separated. HLA-A02:01
-l, --length Peptide length, given as single number, 9
range (9-11) or comma separated (9,10,11).
-e, --expression-file Expression file, tab separated
((ENST*/ENSG*) mean)
Optional arguments affecting output files:
-o, --output-file Output file name. <VEP-file>.mupexi
-d, --out-dir Output directory - full path. current directory
-p, --prefix Prefix for output files - will be applied <VCF-file>
to all (.mupexi, .log, .fasta) unless specified
by -o or -L.
-L, --log-file Logfile name. <VCF-file>.log
-m, --mismatch-number Maximum number of mismatches to search for in 4
normal peptide match.
-a, --assembly The assembly version to run VEP. GRCh38
Optional arguments affecting computational process:
-F, --fork Number of processors running VEP. 1
Other options (these do not take values)
-f, --make-fasta Create FASTA file with long peptides
- mutation in the middle
-c, --config-file Path to the config.ini file current directory
-t, --keep-temp Retain all temporary files
-M, --mismatch-only Print only mismatches in normal peptide sequence
and otherwise use dots (...AA.....)
-w, --webface Run in webserver mode
-g, --liftover Perform liftover HG19 to GRCh38.
Requires local picard installation with paths
stated in the config file
-E, --expression-type Setting if the expression values in the expression transcript
files are determined on transcript or gene level.
(transcript/gene)
-h, --help Print this help information
REMEMBER to state references in the config.ini file
MuPeXI accepts a VCF file of somatic mutation calls optimally obtained from either MuTect or MuTect2. The VCF files do not need to be modified; the "raw" output VCF file can be put directly into MuPeXI.
Compact example of a VCF file:
##fileformat=VCFv4.2
##GATKCommandLine.MuTect2=<ID=MuTect2,Version=3.5-0-g36282e4
##SAMPLE=<ID=NORMAL,SampleName=TCGA-XV-A9W5_N
##SAMPLE=<ID=TUMOR,SampleName=TCGA-XV-A9W5_T
##reference=file:///home/projects/pr_46630/data/references/human_GRCh38/GCA_000001405.15_GRCh38_full_analysis_set.fa
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT TUMOR NORMAL
chr1 948711 . C G . germline_risk . . . .
chr1 1657358 . T TA . alt_allele_in_normal . . . .
chr1 1986752 rs4233028 A G . germline_risk . . . .
chr1 3431704 rs2493274 G C . germline_risk . . . .
chr1 3631978 rs2244942 T C . germline_risk . . . .
chr1 3839305 rs1891940 T C . clustered_events;germline_risk . . . .
A full example of a VCF file can be found on the MuPeXI webserver here.
It is optional, but preferable, to provide a file with expression values as input to add the expression of each transcript where a mutated peptide was extracted. The expression files used for testing MuPeXI were generated from raw RNA-seq data using Kallisto. The files should be tab separated and include Ensembl transcript ID (ENST) and mean expression WITHOUT a header.
ENST00000456328.2 0.868567715
ENST00000450305.2 0
ENST00000488147.1 2.72373575
ENST00000619216.1 0
ENST00000473358.1 0
ENST00000469289.1 0
ENST00000607096.1 0
A full example of an expression file can be found on the MuPeXI webserver here.
It should be noted that MuPeXI takes both expression values determined on transcript and
gene level, though transcript is preferable. If gene level is used (ENSG...) the -E gene
option should be used.
The following references are required for MuPeXI to run:
- Peptide
The peptide reference is a FASTA file containing all peptides of the human proteome. - cDNA
The cDNA reference is a FASTA file containing all cDNA sequences of the human proteome.
These references can be acquired from the
Ensembl website.
The most recent release is found under Gene annotation > Download genes, cDNAs, ncRNA,
protein (FASTA) > pep (for peptide reference) and > cdna (for cDNA reference).
It should be emphasized that it is of very high importance that the references and VEP
match in release version (e.g. release-85).
The following reference are optional but preferable:
- Cosmic
TSV file containing known cancer driver genes. The cancer gene census can be downloaded from the COSMIC website.
MuPeXI can output up to three files.
The output files are the following:
- .mupexi The main output file containing a TSV file with the extracted mutated peptides and all the information needed to choose the wanted peptides.
- . log The log file containing information about the run.
- .fasta
The FASTA file with the long peptides, before they are chopped up into user defined
length, with the mutation centered. (use the option
-f)
The prediction output (.mupexi) for each peptide pair consists of the following columns:
| Column Name | Description |
|---|---|
| HLA allele | Allele name |
| Normal peptide | Peptide from reference corresponding to the mutant peptide. |
| Normal MHC affinity | Predicted binding affinity of normal peptide in nanoMolar units. |
| Normal MHC % rank | %Rank of prediction score for nomal peptides. |
| Mutant peptide | The extracted mutant peptide. |
| Mutant MHC affinity | Predicted binding affinity of mutant peptide in nanoMolar units. |
| Mutant MHC % rank | %Rank of prediction score for mutant peptides. |
| Gene ID | Ensembl gene ID |
| Transcript ID | Ensembl transcript ID |
| Amino acid change | Amino acid change annotated in VEP file. |
| Allele Frequency | Genomic allele frequency detected by MuTect2. |
| Mismatches | Mismatches between normal and mutant peptide. |
| Peptide position | Position of amino acid change in the peptide. Can be a range in the case of insertions and frameshifts. |
| Chr | Chromosome position annotated in the VEP file. |
| Genomic position | Genome nucleotide position annotated in the VEP file. |
| Protein position | Amino acid position annotated in the VEP file. |
| Mutation cons. | The consequence annotated in the VEP file translated into single letter abbreviations: M; Missense variant, I; In-frame insertion, D; In-frame deletion, F; Frameshift variant |
| Gene symbol | HUGO symbol corresponding to the Ensembl transcript id. |
| Cancer driver gene | Yes if the HUGO symbol is in the cosmic reference list, No if it is not. |
| Expression Level | Expression of the transcript which the mutant peptide was extracted from. |
| Mutant affinity score | Calculated binding affinity score of the mutant peptide, based on a negative logistic function of the mutant MHC %Rank score. This is used to calculate the final prioritization score. |
| Normal affinity score | Calculated binding affinity score of the normal peptide, based on a positive logistic function of the normal MHC %Rank score. This is used to calculate the final prioritization score. |
| Expression score | Calculated Expression score of the transcript expression level. This is used to calculate the final prioritization score. |
| Priority score | Calculated prioritization dependent on HLA binding, gene expression, normal and mutant peptide binding ratio and allele frequency. |
NetMHCpan output: %Rank of prediction score to a set of 200.000 random natural 9mer peptides. For more information go to NetMHCpan output format.
To run the provided test files with MuPeXI the following command can be run:
path/to/MuPeXI.py -v test.vcf -c path/to/config.ini -e expression_test.tsv
For additional fasta file output:
path/to/MuPeXI.py -v test.vcf -c path/to/config.ini -e expression_test.tsv -f
Print only the mismatch amino acid for the normal peptide:
path/to/MuPeXI.py -v test.vcf -c path/to/config.ini -e expression_test.tsv -m
Raw sequencing data should be obtained and the following steps is a recommendation on how to processes this data prior to using MuPeXI.
The following data should be obtained:
- WXS (or WGS) of tumor and corresponding normal sample
- RNAseq of tumor sample
Raw sequencing data is processed to extract variant calls, and optionally gene expression values. Therefore, either whole exome (WXS) or whole genome (WGS) sequencing data is required from both tumor and matching normal sample. For optimal utilization of MuPeXI, RNA sequencing (RNAseq) data should be obtained as well from the tumor sample.
First, it is important to check the quality of both WXS and RNAseq data. This can be done by running the wrapper tool Trim Galore, which combines the functions of Cutadapt and FastQC: trimming the reads below an average phred score of 20 (default value), cutting out standard adaptors, such as those from Illumina, and in the end running FastQC to display the FastQC report. This enables the user to check if the quality is satisfactory and if non-standard adapters are seen in the overrepresented sequences.
For the WXS pipeline the preprocessing steps for variant calling should be done following
the
GATK best practice guidelines.
The reads are aligned using default BWA mem options;
here it is important to provide the Read Group for the following steps to be possible.
Then indel realignment and base recalibration are done to reduce false positive variant
calls; a detailed description of these steps can be found on the GATK website.
Single nucleotide variant (SNV) and indel calling should be done using
MuTect2.
MuTect2 is designed to call variants, both SNVs and indels, from tumor samples evaluating
reads from matched tumor and normal samples.
The standard output format from MuTect2 is a VCF file.
If MuTect or Mutect2 is not used for variant calling, the genomic allele frequency will
not be taken into account in the MuPeXI priority score.
After quality check the expression scores are obtained by pseudo-aligning the raw reads using Kallisto. Since this is very fast, the runs are bootstrapped (e.g. 500 times) giving a variance of each expression score obtained. The expression score is normalized by Kallisto in transcripts per million (TPM).
If the HLA alleles for the sample(s) have not been typed by other means, they can be
inferred from sequencing data by several different algorithms. Among these are
ATHLATES,
Polysolver,
OptiType and
PHLAT.
We used OptiType with default settings, first filtering the reads with
RazerS3.
The outputs files from the NGS analysis; VCF file, HLA alleles and expression file, are
now ready to be processed by MuPeXI.
Pre-processing of raw sequencing data. Flowchart of an example NGS pipeline to
process raw sequencing data in preparation to predict neo-epitopes with MuPeXI.
BWA: Burrows-Wheeler Aligner. GATK: Genome Analysis Toolkit. WXS: Whole exome sequencing.