VEP (Variant Effect Predictor) determines the effect of your variants (SNPs, insertions, deletions, CNVs or structural variants) on genes, transcripts, and protein sequence, as well as regulatory regions.

References:

• McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F. The Ensembl Variant Effect Predictor. Genome Biol. 2016 Jun 6;17(1):122.

• VEP Main Page
• VEP Tutorial
• ensembl-vep Git Page
• • Old VEP versions
    • VEP Main Page (version 111)
    • VEP Main Page (version 110)
    • VEP Main Page (version 109)
    • VEP Main Page (version 108)
    • VEP Main Page (version 107)
    • VEP Main Page (version 106)
    • VEP Main Page (version 105)
    • VEP Main Page (version 104)
    • VEP Main Page (version 103)
    • VEP Main Page (version 102)
    • VEP Main Page (version 101)
    • VEP Main Page (version 100)

• Module Name: VEP (see the modules page for more information)
• Singlethreaded
• Environment variables set
  • VEP_HOME
  • VEP_EXAMPLES
  • VEP_CACHEDIR -- reference data and plugins
  • GS -- location of the GeneSplicer application
  • PERL5LIB
• Example files in $VEP_EXAMPLES
• Reference data in $VEP_CACHEDIR

By default VEP requires internet connectivity to the Ensembl databases. THIS IS NOT POSSIBLE ON THE BIOWULF CLUSTER! Instead, the databases have been locally cached into a version-specific directory $VEP_CACHEDIR, as set by the VEP module, allowing for offline analysis.

Without supplying --dir $VEP_CACHEDIR, VEP will attempt to create a cache directory in your home directory as ~/.vep. This may cause your /home directory to fill up, causing unexpected failures to your jobs. Make sure to include --cache --dir $VEP_CACHEDIR with all VEP commands (including haplo and variant_recoder).

Older versions of VEP used --dir_cache $VEP_CACHEDIR rather than --dir $VEP_CACHEDIR. Both are valid.

Commands

• convert_cache.pl
• filter_vep: filter the output of VEP
• vep: predict effect of variants
• haplo: Ensembl transcript haplotypes view
• variant_recoder: translating between different variant encodings

Reference Files

--assembly is needed for human sequences because there are two available (GRCh37 and GRCh38). For cat, dog, and mouse, no assembly required.

• --fasta $VEP_CACHEDIR/cat.fa --species cat
• --fasta $VEP_CACHEDIR/dog.fa --species dog
• --fasta $VEP_CACHEDIR/mouse.fa --species mouse
• --fasta $VEP_CACHEDIR/zebrafish.fa --species zebrafish
• --fasta $VEP_CACHEDIR/GRCh38.fa --species human --assembly GRCh38
• --fasta $VEP_CACHEDIR/GRCh37.fa --species human --assembly GRCh37

Plugins

There are a large number of plugins available for use with VEP. Some of these plugins require third-party reference data. Most of this data is available within $VEP_CACHEDIR, but some are available in the /fdb tree. Here is an example for using plugins:

module load VEP/111
vep \
 -i ${VEP_EXAMPLES}/homo_sapiens_GRCh38.vcf \
 -o example.out \
 --offline \
 --cache \
 --force_overwrite \
 --dir ${VEP_CACHEDIR} \
 --species human \
 --assembly GRCh38 \
 --fasta ${VEP_CACHEDIR}/GRCh38.fa \
 --everything \
 --plugin CSN \
 --plugin Blosum62 \
 --plugin Carol \
 --plugin Condel,$VEP_CACHEDIR/Plugins/config/Condel/config,b \
 --plugin Phenotypes,file=${VEP_CACHEDIR}/Plugins/Phenotypes.pm_human_111_GRCh38.gvf.gz \
 --plugin ExAC,$VEP_CACHEDIR/ExAC.r0.3.sites.vep.vcf.gz \
 --plugin GeneSplicer,$GS/bin/genesplicer,$GS/human,context=200 \
 --plugin CADD,${VEP_CACHEDIR}/CADD_1.4_GRCh38_whole_genome_SNVs.tsv.gz,${VEP_CACHEDIR}/CADD_1.4_GRCh38_InDels.tsv.gz \
 --plugin Downstream \
 --plugin LoFtool \
 --plugin FATHMM,"python ${VEP_CACHEDIR}/fathmm.py"

Here is a synopsis of --plugin examples using GRCh38:

• AlphaMissense:
  

  --plugin AlphaMissense,file=${VEP_CACHEDIR}/AlphaMissense_hg38.tsv.gz,cols=all

• BayesDel:
  

  --plugin BayesDel,file=${VEP_CACHEDIR}//BayesDel_170824_addAF_all_scores_GRCh38.txt.gz

• Blosum62:
  

  --plugin Blosum62

• CADD:
  

  --plugin CADD,${VEP_CACHEDIR}/CADD_1.4_GRCh38_whole_genome_SNVs.tsv.gz,${VEP_CACHEDIR}/CADD_1.4_GRCh38_InDels.tsv.gz

• Carol:
  

  --plugin Carol

• Condel:
  

  --plugin Condel,${VEP_CACHEDIR}/Plugins/Condel/config,b

• CSN
  

  --plugin CSN

• dbNSFP:
  

  --plugin dbNSFP,${VEP_CACHEDIR}/dbNSFP4.2a_hg38.txt.gz,LRT_score,GERP++_RS

• dbscSNV:
  

  --plugin dbscSNV,${VEP_CACHEDIR}/dbscSNV1.1.txt.gz

• DisGeNET:
  

  --plugin DisGeNET,file=${VEP_CACHEDIR}/all_variant_disease_pmid_associations_sorted.tsv.gz,disease=1,filter_source=GWASDB&GWASCAT

• DosageSensitivity:
  

  --plugin DosageSensitivity,file=${VEP_CACHEDIR}//Collins_rCNV_2022.dosage_sensitivity_scores.tsv.gz

• Downstream:
  

  --plugin Downstream

• Enformer:
  

  --plugin Enformer,file=$VEP_CACHEDIR/enformer_grch38.vcf.gz

• ExAC:
  

  --plugin ExAC,${VEP_CACHEDIR}/ExAC.r0.3.1.sites.vep.vcf.gz

• FATHMM:
  

  --plugin FATHMM,"python ${VEP_CACHEDIR}/fathmm.py"

• G2P:
  

  --plugin G2P,file=${VEP_CACHEDIR}/SkinG2P.csv

• GeneSplicer:
  

  --plugin GeneSplicer,$GS/bin/genesplicer,$GS/human,context=200

• gnomad:
  

  --custom file=${VEP_CACHEDIR}/gnomad.genomes.v4.0.sites.noVEP.vcf.gz,\
  short_name=gnomADg,format=vcf,type=exact,coords=0,\
  fields=AF_afr%AF_amr%AF_asj%AF_eas%AF_fin%AF_nfe%AF_oth
  

• HGVSReferenceBase:
  

  --hgvs --plugin HGVSReferenceBase

• Lof:
  

  --plugin LoF,loftee_path:${VEP_CACHEDIR}/Plugins/loftee_GRCh38, \
  human_ancestor_fa:${VEP_CACHEDIR}/Plugins/loftee_GRCh38/human_ancestor.fa.gz, \
  conservation_file:${VEP_CACHEDIR}/Plugins/loftee_GRCh38/loftee.sql, \
  gerp_bigwig:${VEP_CACHEDIR}/Plugins/loftee_GRCh38/gerp_conservation_scores.homo_sapiens.GRCh38.bw

• LoFtool:
  

  --plugin LoFtool

• MaxEntScan:
  

  --plugin MaxEntScan,${VEP_CACHEDIR}/MaxEntScan

• MTR:
  

  --plugin MTR,${VEP_CACHEDIR}/mtrflatfile_2.0.txt.gz

• OpenTargets:
  

  --plugin OpenTargets,file=${VEP_CACHEDIR}//OTGenetics.tsv.gz

• Phenotypes:
  

  --plugin Phenotypes,file=${VEP_CACHEDIR}/Plugins/Phenotypes.pm_human_111_GRCh38.gvf.gz

• REVEL:
  

  --plugin REVEL,${VEP_CACHEDIR}/revel_GRCh38_1.3.tsv.gz

• SpliceAI:
  

  --plugin SpliceAI,snv=${VEP_CACHEDIR}/spliceai_scores.masked.snv.hg38.vcf.gz,indel=${VEP_CACHEDIR}/spliceai_scores.masked.indel.hg38.vcf.gz

• SpliceVault:
  

  --plugin SpliceVault,file=${VEP_CACHEDIR}//SpliceVault_data_GRCh38.tsv.gz

• StructuralVariantOverlap:
  

  --plugin StructuralVariantOverlap,file=${VEP_CACHEDIR}/gnomad_v2_sv.sites.vcf.gz

• VARITY:
  

  --plugin VARITY,file=${VEP_CACHEDIR}//varity_all_predictions_GRCh38.tsv.gz

Some of the plugins have multiple versions of reference files.

NOTE: The name of the variation file for the Phenotypes plugin depends on the version of VEP being used. In the above example, VEP/111 is being used, and the variation file is ${VEP_CACHEDIR}/Plugins/Phenotypes.pm_homo_sapiens_111_GRCh38.gvf.gz. Please run the command ls -l ${VEP_CACHEDIR} to see all the reference files available.

For more information about plugins, type

perldoc $VEP_CACHEDIR/Plugins/[name].pm

where [name] is the name of the plugin.

LOFTEE Plugin

The LOFTEE (Loss-Of-Function Transcript Effect Estimator) plugin is a bit trickier than others, and is not well documented. It is available for VEP versions >= 101. Here are examples for annotating GRCh37 and GRCh38 aligned VCF files:

ml VEP/101

export PERL5LIB=$PERL5LIB:${VEP_CACHEDIR}/Plugins/loftee_GRCh37
vep \
  --offline --cache --dir ${VEP_CACHEDIR} \
  --input_file ${VEP_EXAMPLES}/homo_sapiens_GRCh37.vcf \
  --species human --assembly GRCh37 --fasta ${VEP_CACHEDIR}/GRCh37.fa \
  --output_file GRCh37.txt --stats_file GRCh37_summary.txt \
  --plugin LoF,loftee_path:${VEP_CACHEDIR}/Plugins/loftee_GRCh37,\
conservation_file:${VEP_CACHEDIR}/Plugins/loftee_GRCh37/phylocsf_gerp.sql,\
human_ancestor_fa:${VEP_CACHEDIR}/Plugins/loftee_GRCh37/human_ancestor.fa.gz >& GRCh37.out

export PERL5LIB=$PERL5LIB:${VEP_CACHEDIR}/Plugins/loftee_GRCh38
vep \
  --offline --cache --dir ${VEP_CACHEDIR} \
  --input_file ${VEP_EXAMPLES}/homo_sapiens_GRCh38.vcf \
  --species human --assembly GRCh38 --fasta ${VEP_CACHEDIR}/GRCh38.fa \
  --output_file GRCh38.txt --stats_file GRCh38_summary.txt \
  --plugin LoF,loftee_path:${VEP_CACHEDIR}/Plugins/loftee_GRCh38,\
human_ancestor_fa:${VEP_CACHEDIR}/Plugins/loftee_GRCh38/human_ancestor.fa.gz,\
conservation_file:${VEP_CACHEDIR}/Plugins/loftee_GRCh38/loftee.sql,\
gerp_bigwig:${VEP_CACHEDIR}/Plugins/loftee_GRCh38/gerp_conservation_scores.homo_sapiens.GRCh38.bw >& GRCh38.out

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ~]$ module load VEP
[user@cn3144 ~]$ ln -s $VEP_EXAMPLES/homo_sapiens_GRCh38.vcf .
[user@cn3144 ~]$ vep -i homo_sapiens_GRCh38.vcf -o test.out --offline --cache --dir $VEP_CACHEDIR --species human --assembly GRCh38 --fasta $VEP_CACHEDIR/GRCh38.fa 

[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

Create a batch input file (e.g. VEP.sh). For example:

#!/bin/bash
module load VEP
vep -i trial1.vcf --offline --cache --dir $VEP_CACHEDIR --fasta $VEP_CACHEDIR/GRCh38.fa --output trial1.out

Submit this job using the Slurm sbatch command.

sbatch [--cpus-per-task=#] [--mem=#] VEP.sh

Create a swarmfile (e.g. VEP.swarm). For example:

vep -i trial1.vcf --offline --cache --dir $VEP_CACHEDIR --fasta $VEP_CACHEDIR/GRCh38.fa --output trial1.out
vep -i trial2.vcf --offline --cache --dir $VEP_CACHEDIR --fasta $VEP_CACHEDIR/GRCh38.fa --output trial2.out
vep -i trial3.vcf --offline --cache --dir $VEP_CACHEDIR --fasta $VEP_CACHEDIR/GRCh38.fa --output trial3.out
vep -i trial4.vcf --offline --cache --dir $VEP_CACHEDIR --fasta $VEP_CACHEDIR/GRCh38.fa --output trial4.out

By default, vep will write to the same output file ("variant_effect_output.txt") unless directed to do otherwise using the --output option. For swarms of multiple runs, be sure to include this option.

Submit this job using the swarm command.

swarm -f VEP.swarm [-g #] [-t #] --module VEP