Inference on phenotype-specific effects of genes using multivariate kernel machine regression.

ABSTRACT: We consider the problem of assessing the joint effect of a set of genetic markers on multiple, possibly correlated phenotypes of interest. We develop a kernel machine based multivariate regression framework, where the joint effect of the marker set on each of the phenotypes is modeled using prespecified kernel functions with unknown variance components. Unlike most existing methods that mainly focus on the global association between the marker set and the phenotype set, we develop estimation and testing procedures to study phenotype-specific associations. Specifically, we develop an estimation method based on the penalized likelihood approach to estimate phenotype-specific effects and their corresponding standard errors while accounting for possible correlation among the phenotypes. We dev

SUBMITTER: Maity A 

PROVIDER: S-EPMC5768462 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature