Efficient variance components analysis across millions of genomes

Variance components analysis may be used for a variety of applications including heritability estimation and association mapping. Here, the authors present a computationally efficient method, scalable to extremely large GWAS datasets, and use it for heritabilty analysis of 22 traits from UK Biobank

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Autores principales:	Ali Pazokitoroudi, Yue Wu, Kathryn S. Burch, Kangcheng Hou, Aaron Zhou, Bogdan Pasaniuc, Sriram Sankararaman
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/044c5503786540658095e58fca2853be
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spelling	oai:doaj.org-article:044c5503786540658095e58fca2853be2021-12-02T16:27:51ZEfficient variance components analysis across millions of genomes10.1038/s41467-020-17576-92041-1723https://doaj.org/article/044c5503786540658095e58fca2853be2020-08-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-17576-9https://doaj.org/toc/2041-1723Variance components analysis may be used for a variety of applications including heritability estimation and association mapping. Here, the authors present a computationally efficient method, scalable to extremely large GWAS datasets, and use it for heritabilty analysis of 22 traits from UK BiobankAli PazokitoroudiYue WuKathryn S. BurchKangcheng HouAaron ZhouBogdan PasaniucSriram SankararamanNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Ali Pazokitoroudi Yue Wu Kathryn S. Burch Kangcheng Hou Aaron Zhou Bogdan Pasaniuc Sriram Sankararaman Efficient variance components analysis across millions of genomes
description	Variance components analysis may be used for a variety of applications including heritability estimation and association mapping. Here, the authors present a computationally efficient method, scalable to extremely large GWAS datasets, and use it for heritabilty analysis of 22 traits from UK Biobank
format	article
author	Ali Pazokitoroudi Yue Wu Kathryn S. Burch Kangcheng Hou Aaron Zhou Bogdan Pasaniuc Sriram Sankararaman
author_facet	Ali Pazokitoroudi Yue Wu Kathryn S. Burch Kangcheng Hou Aaron Zhou Bogdan Pasaniuc Sriram Sankararaman
author_sort	Ali Pazokitoroudi
title	Efficient variance components analysis across millions of genomes
title_short	Efficient variance components analysis across millions of genomes
title_full	Efficient variance components analysis across millions of genomes
title_fullStr	Efficient variance components analysis across millions of genomes
title_full_unstemmed	Efficient variance components analysis across millions of genomes
title_sort	efficient variance components analysis across millions of genomes
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/044c5503786540658095e58fca2853be
work_keys_str_mv	AT alipazokitoroudi efficientvariancecomponentsanalysisacrossmillionsofgenomes AT yuewu efficientvariancecomponentsanalysisacrossmillionsofgenomes AT kathrynsburch efficientvariancecomponentsanalysisacrossmillionsofgenomes AT kangchenghou efficientvariancecomponentsanalysisacrossmillionsofgenomes AT aaronzhou efficientvariancecomponentsanalysisacrossmillionsofgenomes AT bogdanpasaniuc efficientvariancecomponentsanalysisacrossmillionsofgenomes AT sriramsankararaman efficientvariancecomponentsanalysisacrossmillionsofgenomes
_version_	1718383972906434560

Efficient variance components analysis across millions of genomes

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