Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD.

ABSTRACT: Our specific aims were to evaluate the power of bivariate analysis and to compare its performance with traditional univariate analysis in samples of unrelated subjects under varying sampling selection designs. Bivariate association analysis was based on the seemingly unrelated regression (SUR) model that allows different genetic models for different traits. We conducted extensive simulations for the case of two correlated quantitative phenotypes, with the quantitative trait locus making equal or unequal contributions to each phenotype. Our simulation results confirmed that the power of bivariate analysis is affected by the size, direction and source of the phenotypic correlations between traits. They also showed that the optimal sampling scheme depends on the size and direction of the indu

SUBMITTER: Saint-Pierre A 

PROVIDER: S-EPMC3110051 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature