Scalable probabilistic PCA for large-scale genetic variation data.

Principal component analysis (PCA) is a key tool for understanding population structure and controlling for population stratification in genome-wide association studies (GWAS). With the advent of large-scale datasets of genetic variation, there is a need for methods that can compute principal compon...

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Bibliographic Details
Published in:	PLoS Genetics
Main Authors:	Aman Agrawal, Alec M Chiu, Minh Le, Eran Halperin, Sriram Sankararaman
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2020-05-01
Online Access:	https://doi.org/10.1371/journal.pgen.1008773

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