Robust estimation of the false discovery rate

126Citations
Citations of this article
146Readers
Mendeley users who have this article in their library.

This article is free to access.

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. © 2006 Oxford University Press.

Cite

CITATION STYLE

APA

Pounds, S., & Cheng, C. (2006). Robust estimation of the false discovery rate. Bioinformatics, 22(16), 1979–1987. https://doi.org/10.1093/bioinformatics/btl328

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free