Efficient generalized least squares method for mixed population and family-based samples in genome-wide association studies.

ABSTRACT: Genome-wide association studies (GWAS) that draw samples from multiple studies with a mixture of relationship structures are becoming more common. Analytical methods exist for using mixed-sample data, but few methods have been proposed for the analysis of genotype-by-environment (G×E) interactions. Using GWAS data from a study of sarcoidosis susceptibility genes in related and unrelated African Americans, we explored the current analytic options for genotype association testing in studies using both unrelated and family-based designs. We propose a novel method-generalized least squares (GLX)-to estimate both SNP and G×E interaction effects for categorical environmental covariates and compared this method to generalized estimating equations (GEE), logistic regression, the Cochran-Armitage t

SUBMITTER: Li J 

PROVIDER: S-EPMC4112407 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature