Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
15 07 2019
Historique:
received: 01 05 2018
revised: 06 09 2018
accepted: 04 12 2018
pubmed: 7 12 2018
medline: 12 6 2020
entrez: 7 12 2018
Statut: ppublish

Résumé

Large biobanks linking phenotype to genotype have led to an explosion of genetic association studies across a wide range of phenotypes. Sharing the knowledge generated by these resources with the scientific community remains a challenge due to patient privacy and the vast amount of data. Here, we present Global Biobank Engine (GBE), a web-based tool that enables exploration of the relationship between genotype and phenotype in biobank cohorts, such as the UK Biobank. GBE supports browsing for results from genome-wide association studies, phenome-wide association studies, gene-based tests and genetic correlation between phenotypes. We envision GBE as a platform that facilitates the dissemination of summary statistics from biobanks to the scientific and clinical communities. GBE currently hosts data from the UK Biobank and can be found freely available at biobankengine.stanford.edu.

Identifiants

pubmed: 30520965
pii: 5231855
doi: 10.1093/bioinformatics/bty999
pmc: PMC6612820
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2495-2497

Subventions

Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Organisme : NHGRI NIH HHS
ID : U01 HG009080
Pays : United States
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : NLM NIH HHS
ID : T32 LM012409
Pays : United States
Organisme : NLM NIH HHS
ID : T15 LM007033
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG010140
Pays : United States

Informations de copyright

© The Author(s) 2018. Published by Oxford University Press.

Références

Am J Hum Genet. 2021 Dec 2;108(12):2354-2367
pubmed: 34822764
Nucleic Acids Res. 2017 Jan 4;45(D1):D840-D845
pubmed: 27899611
Nat Commun. 2018 Apr 24;9(1):1612
pubmed: 29691392
Nature. 2016 Aug 17;536(7616):285-91
pubmed: 27535533
Nat Rev Genet. 2014 Jun;15(6):409-21
pubmed: 24805122
PLoS Med. 2015 Mar 31;12(3):e1001779
pubmed: 25826379

Auteurs

Gregory McInnes (G)

Biomedical Informatics Training Program, Stanford University, CA, USA.

Yosuke Tanigawa (Y)

Biomedical Informatics Training Program, Stanford University, CA, USA.
Department of Biomedical Data Science, Stanford University, CA, USA.

Chris DeBoever (C)

Department of Biomedical Data Science, Stanford University, CA, USA.

Adam Lavertu (A)

Biomedical Informatics Training Program, Stanford University, CA, USA.

Julia Eve Olivieri (JE)

Institute for Computational and Mathematical Engineering, Stanford University, CA, USA.

Matthew Aguirre (M)

Department of Biomedical Data Science, Stanford University, CA, USA.

Manuel A Rivas (MA)

Department of Biomedical Data Science, Stanford University, CA, USA.

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Classifications MeSH