Ensembl Variant Effect Predictor (VEP)¶
Resource Location
/labs/SysMedBio/Q/Resources/Genomics/VEP
/Volumes/lab/SysMedBio/Resources/Genomics/VEP
Q:\SysMedBio\Resources\Genomics\VEP
The Ensembl Variant Effect Predictor (VEP) is a standard bioinformatics toolset used to determine the functional consequences of genomic variants on genes, transcripts, proteins, and regulatory elements.
Scientific Context¶
When researchers identify mutations through next-generation sequencing (NGS), VEP predicts how these sequence alterations affect: - Coding Sequences: Determining if a variant is synonymous, missense (altering an amino acid), nonsense (introducing a stop codon), or causes a frameshift. - Non-Coding Regions: Analyzing impacts on splice sites, promoters, enhancers, transcription factor binding sites (TFBS), and untranslated regions (UTRs). - Downstream Consequences: Integrating pathogenicity predictors (e.g., SIFT, PolyPhen) and clinical significance classifications (e.g., ClinVar) to help prioritize disease-causing candidates.
The Role of VEP Cache Files¶
VEP cache files are pre-built, highly compressed local datasets containing gene models, transcript definitions, regulatory annotations, and known variation frequencies (e.g., from gnomAD or 1000 Genomes). They are critical because: 1. High Throughput & Speed: Accessing remote Ensembl databases for millions of variants is extremely slow and causes severe network bottlenecks. Local cache files enable coordinate-based, offline queries that process variants orders of magnitude faster. 2. Privacy and Security: By running VEP in "offline" mode using local cache files and reference FASTA sequences, researchers can annotate patient genomes locally without transmitting sensitive clinical genomic data over the public internet. 3. Reproducibility: A versioned cache file (such as Ensembl release 112) ensures that transcript structures and genomic features remain frozen and reproducible for a given study or analysis pipeline.
Main Publication¶
- Title: The Ensembl Variant Effect Predictor
- Authors: William McLaren, Laurent Gil, Sarah E. Hunt, Harpreet Singh Riat, Graham R. S. Ritchie, Anja Thormann, Paul Flicek, and Fiona Cunningham
- Journal: Genome Biology (2016, Volume 17, Article number: 122)
- DOI: 10.1186/s13059-016-0974-4
Available Files¶
The following files are available in the VEP resource directory:
homo_sapiens_vep_112_GRCh37.tar.gz: Compressed archive containing Ensembl VEP release 112 cache data for human assembly GRCh37.homo_sapiens_vep_112_GRCh38.tar.gz: Compressed archive containing Ensembl VEP release 112 cache data for human assembly GRCh38.homo_sapiens/: Unpacked directory containing local structured cache files for:112_GRCh37/: GRCh37 cache database.112_GRCh38/: GRCh38 cache database.
gwas-catalog-download-associations-sorted-alt-full-clean-sorted.tsv.gz: Tab-separated file containing sorted, clean GWAS catalog association data.gwas-catalog-download-associations-sorted-alt-full-clean-sorted.tsv.gz.tbi: Tabix index for the GWAS Catalog associations.