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The phenotype-genotype reference map: Improving biobank data science through replication

delete2023-09-01
delete5
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OA
AI
L
Lisa Bastarache *
S
Sarah Delozier
A
Anita Pandit
J
Jing He
A
Adam Lewis
A
Aubrey Annis
J
Jonathon LeFaive
J
Joshua C. Denny
R
Robert J. Carroll
R
Russ B. Altman
J
Jacob Hughey
M
Matthew Zawistowski
J
Josh F. Peterson
DOI:10.1016/j.ajhg.2023.07.012delete
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Abstract

Abstract

En 中文
Population-scale biobanks linked to electronic health record data provide vast opportunities to extend our knowledge of human genetics and discover new phenotype-genotype associations. Given their dense phenotype data, biobanks can also facilitate replication studies on a phenome-wide scale. Here, we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments. PGRM phenotypes are standardized as phecodes, ensuring interoperability between biobanks. We applied the PGRM to five ancestry-specific cohorts from four independent biobanks and found evidence of robust replications across a wide array of phenotypes. We show how the PGRM can be used to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we use the PGRM to explore factors associated with replicability of GWAS results.
Keywords:
GENOME-WIDE ASSOCIATION
BIG DATA PARADOX
UK BIOBANK
DIVERSITY
HEALTH
RECORD
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Journal

American Journal of Human Genetics cover
American Journal of Human Genetics
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vanderbilt university
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University of Michigan
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