An optimal kernel ‐based U‐statistic method for quantitative gene‐set association analysis

In this study, we proposed an efficient testing procedure that cannot only control Type 1 error rate but also have power close to the one obtained under the optimal kernel in the candidate kernel set, for quantitative trait association studies. Our method, a maximum kernel‐basedU‐statistic method, is built upon the KBT framework and is based on asymptotic results under a high‐dimensional setting. Hence it can efficiently deal with the case where the number of variants in a set is much larger than the sample size. Both simulation and real data analysis demonstrate the ad vantages of the method compared with its counterparts.

Source: Genetic Epidemiology - November 19, 2018 Category: Epidemiology Authors: Tao He, Shaoyu Li, Ping ‐Shou Zhong, Yuehua Cui Tags: RESEARCH ARTICLE Source Type: research