Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics. Issue Volume 49:Issue D1(2021) (12th October 2020)

• Record Type: Journal Article
• Authors: Ghoussaini, Maya; Mountjoy, Edward; Carmona, Miguel; Peat, Gareth; Schmidt, Ellen M; Hercules, Andrew; Fumis, Luca; Miranda, Alfredo; Carvalho-Silva, Denise; Buniello, Annalisa; Burdett, Tony; Hayhurst, James; Baker, Jarrod; Ferrer, Javier; Gonzalez-Uriarte, Asier; Jupp, Simon; Karim, Mohd Anisul; Koscielny, Gautier; Machlitt-Northen, Sandra; Malangone, Cinzia; Pendlington, Zoe May; Roncaglia, Paola; Suveges, Daniel; Wright, Daniel; Vrousgou, Olga; Papa, Eliseo; Parkinson, Helen; MacArthur, Jacqueline A L; Todd, John A; Barrett, Jeffrey C; Schwartzentruber, Jeremy; Hulcoop, David G; Ochoa, David; McDonagh, Ellen M; Dunham, Ian;
• Is Part Of: Nucleic acids research. Volume 49:Issue D1(2021)
• Page Start: D1311
• Page End: D1320
• Publication Date: 2020-10-12
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkaa840
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Open Targets Genetics (https://genetics.opentargets.org ) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.