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Inferring population structure in biobank-scale genomic data

Authors :
Alec M. Chiu
Erin K. Molloy
Zilong Tan
Ameet Talwalkar
Sriram Sankararaman
Source :
American journal of human genetics, vol 109, iss 4
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

Inferring the structure of human populations from genetic variation data is a key task in population and medical genomic studies. Although a number of methods for population structure inference have been proposed, current methods are impractical to run on biobank-scale genomic datasets containing millions of individuals and genetic variants. We introduce SCOPE, a method for population structure inference that is orders of magnitude faster than existing methods while achieving comparable accuracy. SCOPE infers population structure in about a day on a dataset containing one million individuals and variants as well as on the UK Biobank dataset containing 488,363 individuals and 569,346 variants. Furthermore, SCOPE can leverage allele frequencies from previous studies to improve the interpretability of population structure estimates.

Details

ISSN :
00029297
Volume :
109
Database :
OpenAIRE
Journal :
The American Journal of Human Genetics
Accession number :
edsair.doi.dedup.....be976f26b962410b65b0f7ea54d1592e