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Article

Efficient Bayesian mixed-model analysis increases association power in large cohorts.

Nature genetics - 1 Mar 2015

Loh Po-Ru, Tucker George, Bulik-Sullivan Brendan K, Vilhjálmsson Bjarni J, Finucane Hilary K, Salem Rany M, Chasman Daniel I, Ridker Paul M, Neale Benjamin M, Berger Bonnie, Patterson Nick, Price Alkes L

Abstract excerpt

Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts and may not optimize power. All existing methods require time cost O(MN(2)) (where N is the number of samples and M is the number of SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 25642633
DOI: 10.1038/ng.3190
PMCID: PMC4342297

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