The open targets post-GWAS analysis pipeline.

Autor:	Peat G; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.; Open Targets, EBI South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK., Jones W; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK., Nuhn M; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.; Open Targets, EBI South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK., Marugán JC; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.; Open Targets, EBI South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK., Newell W; Open Targets, EBI South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.; GSK, Medicines Research Center, Stevenage SG1 2NY, UK., Dunham I; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.; Open Targets, EBI South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK., Zerbino D; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.; Open Targets, EBI South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Jazyk:	angličtina
Zdroj:	Bioinformatics (Oxford, England) [Bioinformatics] 2020 May 01; Vol. 36 (9), pp. 2936-2937.
DOI:	10.1093/bioinformatics/btaa020
Abstrakt:	Motivation: Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. Results: We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. Availability and Implementation: The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io. (© The Author(s) 2020. Published by Oxford University Press.)
Databáze:	MEDLINE
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