USAT: A Unified Score-Based Association Test for Multiple Phenotype-Genotype Analysis.

ABSTRACT: Genome-wide association studies (GWASs) for complex diseases often collect data on multiple correlated endo-phenotypes. Multivariate analysis of these correlated phenotypes can improve the power to detect genetic variants. Multivariate analysis of variance (MANOVA) can perform such association analysis at a GWAS level, but the behavior of MANOVA under different trait models has not been carefully investigated. In this paper, we show that MANOVA is generally very powerful for detecting association but there are situations, such as when a genetic variant is associated with all the traits, where MANOVA may not have any detection power. In these situations, marginal model based methods, however, perform much better than multivariate methods. We investigate the behavior of MANOVA, both theoreti

SUBMITTER: Ray D 

PROVIDER: S-EPMC4785800 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature