Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

ABSTRACT: Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used

SUBMITTER: Cook JP 

PROVIDER: S-EPMC5237383 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature