Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics.
Chromatin
/ chemistry
Databases, Genetic
Datasets as Topic
Drug Discovery
/ methods
Drug Repositioning
/ methods
Genome, Human
Genome-Wide Association Study
Genotype
Humans
Inflammatory Bowel Diseases
/ drug therapy
Internet
Molecular Targeted Therapy
/ methods
Phenotype
Quantitative Trait Loci
Quantitative Trait, Heritable
Software
Journal
Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011
Informations de publication
Date de publication:
08 01 2021
08 01 2021
Historique:
accepted:
17
09
2020
revised:
16
09
2020
received:
14
08
2020
pubmed:
13
10
2020
medline:
27
1
2021
entrez:
12
10
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 33045747
pii: 5921290
doi: 10.1093/nar/gkaa840
pmc: PMC7778936
doi:
Substances chimiques
Chromatin
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
D1311-D1320Informations de copyright
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.
Références
PLoS Genet. 2019 Dec 12;15(12):e1008489
pubmed: 31830040
Nature. 2020 May;581(7809):434-443
pubmed: 32461654
Nat Genet. 2012 Mar 18;44(4):369-75, S1-3
pubmed: 22426310
Nat Genet. 2018 Sep;50(9):1335-1341
pubmed: 30104761
Genet Epidemiol. 2009 Jan;33(1):79-86
pubmed: 18642345
Nature. 2012 Sep 6;489(7414):75-82
pubmed: 22955617
Nature. 2015 Feb 19;518(7539):337-43
pubmed: 25363779
Bioinformatics. 2010 Apr 15;26(8):1112-8
pubmed: 20200009
Nat Genet. 2019 Oct;51(10):1442-1449
pubmed: 31501517
Nature. 2018 Jun;558(7708):73-79
pubmed: 29875488
Nature. 2014 Mar 27;507(7493):455-461
pubmed: 24670763
Genome Biol. 2016 Jun 06;17(1):122
pubmed: 27268795
J Health Econ. 2016 May;47:20-33
pubmed: 26928437
Nucleic Acids Res. 2020 Jan 8;48(D1):D682-D688
pubmed: 31691826
Nucleic Acids Res. 2019 Jan 8;47(D1):D1056-D1065
pubmed: 30462303
Nucleic Acids Res. 2017 Jan 4;45(D1):D985-D994
pubmed: 27899665
Nat Biotechnol. 2014 Jan;32(1):40-51
pubmed: 24406927
Nucleic Acids Res. 2019 Jan 8;47(D1):D1005-D1012
pubmed: 30445434
Nat Genet. 2015 Aug;47(8):856-60
pubmed: 26121088
Nat Genet. 2017 Feb;49(2):256-261
pubmed: 28067908