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Bioinformatics Advance Access originally published online on June 15, 2006
Bioinformatics 2006 22(16):1979-1987; doi:10.1093/bioinformatics/btl328
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Robust estimation of the false discovery rate

Stan Pounds * and Cheng Cheng

Department of Biostatistics, St. Jude Children's Research Hospital 332 N. Lauderdale Street, Memphis, TN 38135 USA

*To whom correspondence should be addressed.


  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 www.stjuderesearch.org/depts/biostats

Contact: stanley.pounds{at}stjude.org

Supplementary information: Supplementary data are avilable at Bioinformatics online.

Associate Editor: Martin Bishop

Received on April 3, 2006; revised on May 17, 2006; accepted on June 9, 2006

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