A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants.

ABSTRACT: Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous pheno

SUBMITTER: Broadaway KA 

PROVIDER: S-EPMC4800053 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature