Efficient and Accurate Multiple-Phenotype Regression Method for High Dimensional Data Considering Population Structure.

ABSTRACT: A typical genome-wide association study tests correlation between a single phenotype and each genotype one at a time. However, single-phenotype analysis might miss unmeasured aspects of complex biological networks. Analyzing many phenotypes simultaneously may increase the power to capture these unmeasured aspects and detect more variants. Several multivariate approaches aim to detect variants related to more than one phenotype, but these current approaches do not consider the effects of population structure. As a result, these approaches may result in a significant amount of false positive identifications. Here, we introduce a new methodology, referred to as GAMMA for generalized analysis of molecular variance for mixed-model analysis, which is capable of simultaneously analyzing many phen

SUBMITTER: Joo JW 

PROVIDER: S-EPMC5161272 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature