Multi-SKAT: General framework to test for rare-variant association with multiple phenotypes.

ABSTRACT: In genetic association analysis, a joint test of multiple distinct phenotypes can increase power to identify sets of trait-associated variants within genes or regions of interest. Existing multiphenotype tests for rare variants make specific assumptions about the patterns of association with underlying causal variants, and the violation of these assumptions can reduce power to detect association. Here, we develop a general framework for testing pleiotropic effects of rare variants on multiple continuous phenotypes using multivariate kernel regression (Multi-SKAT). Multi-SKAT models affect sizes of variants on the phenotypes through a kernel matrix and perform a variance component test of association. We show that many existing tests are equivalent to specific choices of kernel matrices wit

SUBMITTER: Dutta D 

PROVIDER: S-EPMC6330125 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature