Robust estimation of the false discovery rate

Abstract

Motivation: Presently available methods that use p-values to estimate or control the false discovery rate (FDR) implicitly assume that p-values are continuously distributed and based on two-sided tests. Therefore, it is difficult to reliably estimate the FDR when p-values are discrete or based on one-sided tests. Results: A simple and robust method to estimate the FDR is proposed. The proposed method does not rely on implicit assumptions that tests are two-sided or yield continuously distributed p-values. The proposed method is proven to be conservative and have desirable large-sample properties. In addition, the proposed method was among the best performers across a series of ‘real data simulations’ comparing the performance of five currently available methods. Availability: Libraries of S-plus and R routines to implement the method are freely available from Contact:stanley.pounds@stjude.org Supplementary information: Supplementary data are avilable at Bioinformatics online.