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Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution.

Abstract:

Trans-ethnic meta-analysis of genome-wide association studies (GWAS) across diverse populations can increase power to detect complex trait loci when the underlying causal variants are shared between ancestry groups. However, heterogeneity in allelic effects between GWAS at these loci can occur that is correlated with ancestry. Here, a novel approach is presented to detect SNP association and quantify the extent of heterogeneity in allelic effects that is correlated with ancestry. We employ tr...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/hmg/ddx280

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
More from this funder
Name:
National Institutes of Health
Grant:
U01-DK105535
More from this funder
Name:
Horizon 2020
Grant:
654248
More from this funder
Name:
Wellcome Trust
Grant:
WT098017
More from this funder
Name:
National Heart Lung and Blood Institute
Publisher:
Oxford University Press
Journal:
Human Molecular Genetics More from this journal
Volume:
26
Issue:
18
Pages:
3639-3650
Publication date:
2017-07-01
Acceptance date:
2017-07-13
DOI:
EISSN:
1460-2083
ISSN:
0964-6906
Pmid:
28911207
Language:
English
Keywords:
Pubs id:
pubs:728763
UUID:
uuid:67506a0c-7deb-48b7-8980-efe5425b0dd5
Local pid:
pubs:728763
Source identifiers:
728763
Deposit date:
2017-09-26

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