We’re fortunate to be part of the EMBL European Bioinformatics Institute (EBI), which puts us alongside stellar bioinformaticians and resources in every discipline. From this, great collaborations can grow. We’ve already worked with our colleagues at Gene Expression Atlas and Reactome to embed widgets in Ensembl for viewing baseline gene expression and biochemical pathways respectively, but our latest collaboration is with the Protein Data Bank in Europe (PDBe) to show genetic variation on protein structures.

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The VEP can work as an offline or a web tool and it’s also available as REST service. Perfect for integrating into pipelines or displaying data on the web, the REST API VEP endpoints can take input as HGVS, genomic loci or variant identifiers and can interpret common forms of non-standard HGVS. They are all available using both GET and POST protocols, supporting queries on single or multiple variants respectively.

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Identifying the causal variants from a GWAS generally involves identifying the haplotype blocks that contain your variant of interest, rather than the variant and the gene it is affecting itself. To find the actual genes involved, you need to consider all variants in LD with your identified associations. Ensembl Post-GWAS analysis pipeline (PostGAP) can provide automatic fine-tuning of your GWAS variants, incorporating regulatory information and population-wide LD calculations, along with your VEP results.

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A common use case for the VEP is as a first step towards identifying the causal genetic variant of a rare phenotype from whole genome/exome sequencing. The VEP tells you which genes are hit, what effects they have on them, and you have to begin the long laborious process of filtering those down. Things you might consider include allele frequency, association with genes known to be involved in rare disease and whether both genes in a diploid organism are affected. Rather than faffing about doing this manually, you can use the G2P (genotype to phenotype) plugin instead, which was recently published as a preprint.

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