Efficient Bayesian mixed model analysis increases association power in large cohorts

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 = #samples and M = #SNPs...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4342297/
https://www.ncbi.nlm.nih.gov/pubmed/25642633
http://dx.doi.org/10.1038/ng.3190

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4342297/
https://www.ncbi.nlm.nih.gov/pubmed/25642633
http://dx.doi.org/10.1038/ng.3190

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