FaST linear mixed models for genome-wide association studies

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Item Type:	Article
Title:	FaST linear mixed models for genome-wide association studies
Creators Name:	Lippert, C., Listgarten, J., Liu, Y., Kadie, C.M., Davidson, R.I. and Heckerman, .
Abstract:	We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/).
Keywords:	Algorithms, Computer Simulation, Genetic Models, Genome-Wide Association Study, Software
Source:	Nature Methods
ISSN:	1548-7091
Publisher:	Nature Publishing Group
Volume:	8
Number:	10
Page Range:	833-835
Date:	4 September 2011
Official Publication:	https://doi.org/10.1038/nmeth.1681
PubMed:	View item in PubMed

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