The interpretation of non-coding variants is more challenging than that of coding variants as less prediction methods and reference data are available. On top of the annotation provided for human and mouse in the Ensembl Regulatory Build, the Ensembl Variant Effect Predictor (VEP) also integrates two other human-specific datasets providing information about how variants can affect gene expression. The plugins, satMutMPRA and FunMotifs, are available for use with command-line VEP. One provides detailed information on the impact on expression of variants in the regulatory regions of disease-associated genes; the other an alternative set of genome-wide transcription factor binding motifs.

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If you’re really delving into the role of a particular genetic variant, you might want to know about that base position in other species. VEP can get you ancestral alleles in human and conservation scores in many species for a variant position allowing you to assess if a position is evolutionarily important, or if an allele matches our primate ancestors.

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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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