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Bioinformatics Advance Access published online on June 15, 2006
Bioinformatics, 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
Received April 3, 2006
Revised May 17, 2006
Accepted June 9, 2006

Article

Robust estimation of the false discovery rate

Stan Pounds 1 * and Cheng Cheng 1

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

* To whom correspondence should be addressed.
Stan Pounds, E-mail: stanley.pounds{at}stjude.org


  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. Additionally, 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.

Associate Editor: Martin Bishop
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