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Inferring population structure in biobank-scale genomic data
- 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.
- Subjects :
- Genetics & Heredity
ancestry
Population
Human Genome
population structure
Genomics
Biological Sciences
Medical and Health Sciences
biobank
Good Health and Well Being
Genetics, Population
Gene Frequency
genetic structure
Genetics
admixture
Humans
Generic health relevance
scalability
Genetics (clinical)
Biotechnology
Biological Specimen Banks
Subjects
Details
- ISSN :
- 00029297
- Volume :
- 109
- Database :
- OpenAIRE
- Journal :
- The American Journal of Human Genetics
- Accession number :
- edsair.doi.dedup.....be976f26b962410b65b0f7ea54d1592e