Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing.

ABSTRACT:

Background

Epigenome-wide association studies (EWAS), which seek the association between epigenetic marks and an outcome or exposure, involve multiple hypothesis testing. False discovery rate (FDR) control has been widely used for multiple testing correction. However, traditional FDR control methods do not use auxiliary covariates, and they could be less powerful if the covariates could inform the likelihood of the null hypothesis. Recently, many covariate-adaptive FDR control methods have been developed, but application of these methods to EWAS data has not yet been explored. It is not clear whether these methods can significantly improve detection power, and if so, which covariates are more relevant for EWAS data.

Results

In this study, we evaluate the performance of five

SUBMITTER: Huang J 

PROVIDER: S-EPMC7132874 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature