A method for identifying genetic heterogeneity within phenotypically defined disease subgroups.

ABSTRACT: Many common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic architectures, in which disease-associated variants have different effect sizes in two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximizing power in comparison to standard variant-by-variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post hoc identification of the contributing genetic variants. We demonstrate the method on a range of simulated and test data sets, for which expected res

SUBMITTER: Liley J 

PROVIDER: S-EPMC5357574 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature