Separation of the largest eigenvalues in eigenanalysis of genotype data from discrete subpopulations

Katarzyna Bryc; Wlodek Bryc; Jack W. Silverstein

doi:10.1016/j.tpb.2013.08.004

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arXiv · 1301.4511

Separation of the largest eigenvalues in eigenanalysis of genotype data from discrete subpopulations

Katarzyna Bryc·Wlodek Bryc·Jack W. Silverstein

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Abstract

We present a mathematical model, and the corresponding mathematical analysis, that justifies and quantifies the use of principal component analysis of biallelic genetic marker data for a set of individuals to detect the number of subpopulations represented in the data. We indicate that the power of the technique relies more on the number of individuals genotyped than on the number of markers.

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Katarzyna Bryc, Wlodek Bryc, Jack W. Silverstein. 2017-10-18. Separation of the largest eigenvalues in eigenanalysis of genotype data from discrete subpopulations. https://doi.org/10.1016/j.tpb.2013.08.004

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