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Bayesian meta‐analysis across genome‐wide association studies of diverse phenotypes

Abstract:

Genome‐wide association studies (GWAS) are a powerful tool for understanding the genetic basis of diseases and traits, but most studies have been conducted in isolation, with a focus on either a single or a set of closely related phenotypes. We describe MetABF, a simple Bayesian framework for performing integrative meta‐analysis across multiple GWAS using summary statistics. The approach is applicable across a wide range of study designs and can increase the power by 50% compared with standar...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1002/gepi.22202

Authors


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Institution:
University of Oxford
Department:
NDM
Role:
Author
ORCID:
0000-0003-3665-3575
More by this author
Institution:
University of Oxford
Department:
NDM
Role:
Author
More by this author
Institution:
University of Oxford
Department:
NDM
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Oxford college:
Linacre College
Role:
Author
ORCID:
0000-0002-5012-4162
More from this funder
Name:
Wellcome Trust and the Royal Society
Grant:
208750/Z/17/Z
More from this funder
Name:
Wellcome Trust
Grant:
100956/Z/13/Z
More from this funder
Name:
Academy of Finland
Grant:
294050
More from this funder
Name:
Wellcome Trust Career Development Fellowship
Grant:
097364/Z/11/Z
Publisher:
Wiley
Journal:
Genetic Epidemiology More from this journal
Volume:
43
Issue:
5
Pages:
532-547
Publication date:
2019-03-28
Acceptance date:
2019-03-05
DOI:
EISSN:
1098-2272
ISSN:
0741-0395
Pmid:
30920090
Language:
English
Keywords:
Pubs id:
pubs:991144
UUID:
uuid:219e0744-1655-4fe3-a309-b55ea49e762c
Local pid:
pubs:991144
Source identifiers:
991144
Deposit date:
2019-04-17

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