Efficient Bayesian mixed-model analysis increases association power in large cohorts View Full Text


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Article Info

DATE

2015-02-02

AUTHORS

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

ABSTRACT

Alkes Price, Po-Ru Loh and colleagues report the BOLT-LMM method for mixed-model association. They apply their method to 9 quantitative traits in 23,294 samples and demonstrate that it provides improvements in computational efficiency as well as gains in power that increase with the size of the cohort, making it useful for the analysis of large cohorts. More... »

PAGES

284-290

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    http://scigraph.springernature.com/pub.10.1038/ng.3190

    DOI

    http://dx.doi.org/10.1038/ng.3190

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25642633


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