Meta-MultiSKAT: Multiple phenotype meta-analysis for region-based association test.

ABSTRACT: The power of genetic association analyses can be increased by jointly meta-analyzing multiple correlated phenotypes. Here, we develop a meta-analysis framework, Meta-MultiSKAT, that uses summary statistics to test for association between multiple continuous phenotypes and variants in a region of interest. Our approach models the heterogeneity of effects between studies through a kernel matrix and performs a variance component test for association. Using a genotype kernel, our approach can test for rare-variants and the combined effects of both common and rare-variants. To achieve robust power, within Meta-MultiSKAT, we developed fast and accurate omnibus tests combining different models of genetic effects, functional genomic annotations, multiple correlated phenotypes, and heterogeneity ac

SUBMITTER: Dutta D 

PROVIDER: S-EPMC7006736 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature