Comparison of F-tests for Univariate and Multivariate Mixed-Effect Models in Genome-Wide Association Mapping.

ABSTRACT: Genome-wide association mapping (GWA) has been widely applied to a variety of species to identify genomic regions responsible for quantitative traits. The use of multivariate information could enhance the detection power of GWA. Although mixed-effect models are frequently used for GWA, the utility of F-tests for multivariate mixed-effect models is not well-recognized. Thus, we compared the F-tests for univariate and multivariate mixed-effect models with simulations. The superiority of the multivariate F-test over the univariate test varied depending on three parameters: phenotypic correlation between variates (r), relative size of quantitative trait locus effects between variates (a _d), and missing proportion of phenotypic records (m

SUBMITTER: Onogi A 

PROVIDER: S-EPMC6369166 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature