Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function.

ABSTRACT:

Background

A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic.

Results

The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Gene

SUBMITTER: Yang JJ 

PROVIDER: S-EPMC5571642 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature