False discovery rate estimation for large-scale homogeneous discrete p-values

Kun Liang

Biometrics, 2016, vol. 72, issue 2, 639-648

Abstract: type="main" xml:lang="en">

Large-scale homogeneous discrete p-values are encountered frequently in high-throughput genomics studies, and the related multiple testing problems become challenging because most existing methods for the false discovery rate (FDR) assume continuous p-values. In this article, we study the estimation of the null proportion and FDR for discrete p-values with common support. In the finite sample setting, we propose a novel class of conservative FDR estimators. Furthermore, we show that a broad class of FDR estimators is simultaneously conservative over all support points under some weak dependence condition in the asymptotic setting. We further demonstrate the significant improvement of a newly proposed method over existing methods through simulation studies and a case study.

Date: 2016
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