BGWAS: Bayesian variable selection in linear mixed models with nonlocal priors for genome-wide association studies.

Abstract excerpt

BACKGROUND: Genome-wide association studies (GWAS) seek to identify single nucleotide polymorphisms (SNPs) that cause observed phenotypes. However, with highly correlated SNPs, correlated observations, and the number of SNPs being two orders of magnitude larger than the number of observations, GWAS procedures often suffer from high false positive rates. RESULTS: We propose BGWAS, a novel Bayesian variable...

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