Detecting Genetic Variants in the Presence of Covariates Based on a Random-effects Model

Abstract

There is an emerging interest in sequencing-based association studies of multiple rare variants. Recently, we proposed a new method based on testing whether the fraction of causal variants in a region is zero. The test (TREM) is derived from a random-effects model, and the choice of weighting function is not required when the common and rare variants are analyzed simultaneously. Further, the test does not require complete genotype for each subject at each variant. Here, we extend this method to account for covariates. We also discuss how to adjust for the effect of population stratification by using a method of principle components. Finally, we show some simulation results to compare the performance of several competing tests. ?