Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

ABSTRACT: To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied

SUBMITTER: Chiu CY 

PROVIDER: S-EPMC5315507 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature