Looking for a resource to help you identify causal associations between genetic variants, genes, and diseases in humans? Would you like this information to be open source, open access, and available in an easy-to-use web interface?
- Prioritise genes using an integrated functional score
- Generate a list of genes for which a variant is functionally implicated
- Identify variants tagging a trait-associated lead variant through fine mapping or LD
- Identify traits associated with a gene or variant
- Find shared susceptibility loci
- Visualise associations between traits, variants, and genes
- Connect genes with known drugs in the Open Targets Platform
This new resource will complement the Open Targets Platform and assist with the identification and prioritisation of potential new drug targets by highlighting candidate causal variants and their implicated genes.
Check our short animation to whiz through UK Biobank data, GWAS, GTEx, FANTOM5, PCHi-C data and plenty more.
What are the entry points into Open Targets Genetics?
- Variant (either as a rsID or GRCh38 genomic coordinates e.g. 1_154453788_C_T)
- Gene (HGNC official symbol or Ensembl gene ID e.g. PCSK9)
- Trait or study, including GWAS Catalog and UK Biobank traits e.g. LDL cholesterol (Willer CJ (2013) Nat Genet)
Where does the data come from?
We integrate publicly available functional genomics datasets including eQTL, pQTL, enhancer-TSS, DHS-promoter, and promoter capture Hi-C data, as well as functional consequences predicted by Ensembl VEP and distance to TSS (transcript start site). More details can be found on our data sources documentation. The variant-phenotype associations are derived from UK Biobank disease-trait summary statistics and GWAS curated studies. We use the GWAS (lead) disease-associated variants and expand this set into causal tag variants through linkage disequilibrium (LD) expansion or fine-mapping.
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