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  FaST linear mixed models for genome-wide association studies

Lippert, C., Listgarten J, Liu Y, Kadie CM, Davidson, R., & Heckerman, D. (2011). FaST linear mixed models for genome-wide association studies. Nature Methods, 8(10), 833–835. doi:10.1038/nmeth.1681.

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Lippert, C1, Author           
Listgarten J, Liu Y, Kadie CM, Davidson, RI, Author
Heckerman, D, Author
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1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 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/).

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 Dates: 2011-10
 Publication Status: Issued
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 Identifiers: URI: http://www.nature.com/nmeth/journal/vaop/ncurrent/pdf/nmeth.1681.pdf
DOI: 10.1038/nmeth.1681
BibTex Citekey: LippertLLKDH2011
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Title: Nature Methods
Source Genre: Journal
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Pages: - Volume / Issue: 8 (10) Sequence Number: - Start / End Page: 833–835 Identifier: -