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Convert a VCF into a MAF, where each variant is annotated to only one of all possible gene isoforms
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README.md

vcfmaf

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.

Build Status

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
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