vacation/vcf2maf repository overview

*** The purpose of this fork is a modification of the Dockerfile to facilitate post-VEP vcf2maf conversion and stable versioning of the vcf2maf Docker***

This docker is not set up or tested for executing VEP.

It is only being constructed for converting a VEP vcf file to an MAF file.

See https://github.com/mskcc/vcf2maf⁠ for the real deal and credit them if you use this please.

⁠vcf2maf

To convert a VCF⁠ into a MAF⁠, each variant must be mapped to only one of all possible gene transcripts/isoforms that it might affect. But even within a single isoform, a Missense_Mutation close enough to a Splice_Site, can be labeled as either in MAF format, but not as both. This selection of a single effect per variant, is often subjective. And that's what this project attempts to standardize. The vcf2maf and maf2maf scripts leave most of that responsibility to Ensembl's VEP⁠, but allows you to override their "canonical" isoforms, or use a custom ExAC VCF for annotation. Though the most useful feature is the extensive support in parsing a wide range of crappy MAF-like or VCF-like formats we've seen out in the wild.

⁠Quick start

Find the latest stable release⁠, download it, and view the detailed usage manuals for vcf2maf and maf2maf:

export VCF2MAF_URL=`curl -sL https://api.github.com/repos/mskcc/vcf2maf/releases | grep -m1 tarball_url | cut -d\" -f4`
curl -L -o mskcc-vcf2maf.tar.gz $VCF2MAF_URL; tar -zxf mskcc-vcf2maf.tar.gz; cd mskcc-vcf2maf-*
perl vcf2maf.pl --man
perl maf2maf.pl --man

If you don't have VEP⁠ installed, then follow this gist⁠. Of the many annotators out there, VEP is preferred for its large team of active coders, and its CLIA-compliant HGVS formats⁠. After installing VEP, you can test the script like so:

perl vcf2maf.pl --input-vcf tests/test.vcf --output-maf tests/test.vep.maf

To fill columns 16 and 17 of the output MAF with tumor/normal sample IDs, and to parse out genotypes and allele counts from matched genotype columns in the VCF, use options --tumor-id and --normal-id. Skip option --normal-id if you didn't have a matched normal:

perl vcf2maf.pl --input-vcf tests/test.vcf --output-maf tests/test.vep.maf --tumor-id WD1309 --normal-id NB1308

VCFs from variant callers like VarScan⁠ use hardcoded sample IDs TUMOR/NORMAL in the genotype columns of the VCF. To have this script correctly parse the correct genotype columns, while still printing the proper IDs in the output MAF:

perl vcf2maf.pl --input-vcf tests/test_varscan.vcf --output-maf tests/test_varscan.vep.maf --tumor-id WD1309 --normal-id NB1308 --vcf-tumor-id TUMOR --vcf-normal-id NORMAL

If you have the VEP script in a different folder like /opt/vep, and its cache in /srv/vep, there are options available to use those instead:

perl vcf2maf.pl --input-vcf tests/test.vcf --output-maf tests/test.vep.maf --vep-path /opt/vep --vep-data /srv/vep

⁠maf2maf

If you have a MAF or a MAF-like file that you want to reannotate, then use maf2maf, which simply runs maf2vcf followed by vcf2maf:

perl maf2maf.pl --input-maf tests/test.maf --output-maf tests/test.vep.maf

After tests on variant lists from many sources, maf2vcf and maf2maf are quite good at dealing with formatting errors or "MAF-like" files. It even supports VCF-style alleles, as long as Start_Position == POS. But it's OK if the input format is imperfect. Any variants with a reference allele mismatch are kept aside in a separate file for debugging. The bare minimum columns that maf2maf expects as input are:

Chromosome	Start_Position	Reference_Allele	Tumor_Seq_Allele2	Tumor_Sample_Barcode
1	3599659	C	T	TCGA-A1-A0SF-01
1	6676836	A	AGC	TCGA-A1-A0SF-01
1	7886690	G	A	TCGA-A1-A0SI-01

See data/minimalist_test_maf.tsv for a sampler. Addition of Tumor_Seq_Allele1 will be used to determine zygosity. Otherwise, it will try to determine zygosity from variant allele fractions, assuming that arguments --tum-vad-col and --tum-depth-col are set correctly to the names of columns containing those read counts. Specifying the Matched_Norm_Sample_Barcode with its respective columns containing read-counts, is also strongly recommended. Columns containing normal allele read counts can be specified using argument --nrm-vad-col and --nrm-depth-col.

⁠License

Apache-2.0 | Apache License, Version 2.0 | https://www.apache.org/licenses/LICENSE-2.0