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Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data

Genetics (Austin), 2018-10, Vol.210 (2), p.719-731 [Peer Reviewed Journal]

Copyright © 2018 by the Genetics Society of America. ;Copyright Genetics Society of America Oct 2018 ;Copyright © 2018 by the Genetics Society of America 2018 ;ISSN: 1943-2631 ;ISSN: 0016-6731 ;EISSN: 1943-2631 ;DOI: 10.1534/genetics.118.301336 ;PMID: 30131346

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Title:
Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data
Author: Meisner, Jonas ; Albrechtsen, Anders
Subjects: Admixtures ; Alleles ; Animals ; Clustering ; Computer simulation ; Gene Frequency ; Gene sequencing ; Genetics ; Genetics, Population - methods ; Genotype ; Genotypes ; Heuristic methods ; Investigations ; Iterative methods ; Next-generation sequencing ; Population ; Population (statistical) ; Population genetics ; Population structure ; Population studies ; Principal Component Analysis ; Principal components analysis ; Sequence Analysis, DNA - methods ; Statistical analysis ; Statistical methods ; Uncertainty
Is Part Of: Genetics (Austin), 2018-10, Vol.210 (2), p.719-731
Description: We here present two methods for inferring population structure and admixture proportions in low-depth next-generation sequencing (NGS) data. Inference of population structure is essential in both population genetics and association studies, and is often performed using principal component analysis (PCA) or clustering-based approaches. NGS methods provide large amounts of genetic data but are associated with statistical uncertainty, especially for low-depth sequencing data. Models can account for this uncertainty by working directly on genotype likelihoods of the unobserved genotypes. We propose a method for inferring population structure through PCA in an iterative heuristic approach of estimating individual allele frequencies, where we demonstrate improved accuracy in samples with low and variable sequencing depth for both simulated and real datasets. We also use the estimated individual allele frequencies in a fast non-negative matrix factorization method to estimate admixture proportions. Both methods have been implemented in the PCAngsd framework available at http://www.popgen.dk/software/.
Publisher: United States: Genetics Society of America
Language: English
Identifier: ISSN: 1943-2631
ISSN: 0016-6731
EISSN: 1943-2631
DOI: 10.1534/genetics.118.301336
PMID: 30131346
Source: MEDLINE
Alma/SFX Local Collection
ProQuest Central

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Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data

Copyright © 2018 by the Genetics Society of America. ;Copyright Genetics Society of America Oct 2018 ;Copyright © 2018 by the Genetics Society of America 2018 ;ISSN: 1943-2631 ;ISSN: 0016-6731 ;EISSN: 1943-2631 ;DOI: 10.1534/genetics.118.301336 ;PMID: 30131346

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