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Bioinformatics Advance Access published online on June 23, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn310
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

On correcting the overestimation of the permutation based false discovery rate estimator

Shuo Jiao and Shunpu Zhang *

Department of Statistics, University of Nebraska Lincoln

*To whom correspondence should be addressed. Dr. Shunpu Zhang, E-mail: szhang3{at}unl.edu


  Abstract

Motivation: Recent attempts to account for multiple testing in the analysis of microarray data have focused on controlling the false discovery rate (FDR), which is defined as the expected percentage of the number of false positive genes among the claimed significant genes. As a consequence, the accuracy of the FDR estimators willbe important for correctly controlling FDR. Xie et al. (2005) found that the standard permutation method of estimating FDR is biased and proposed to delete the predicted differentially expressed (DE) genes in the estimation of FDR for one-sample comparison. However, we notice that the formula of the FDR used in their paper is incorrect. This makes the comparison results reported in their paper unconvincing. Other problems with their method include the biased estimation of FDR caused by over- or under- deletion of DE genes in the estimation of FDR and by the implicit use of an unreasonable estimator of the true proportion of equivalently expressed (EE) genes. Due to the great importance of accurate FDR estimation in microarray data analysis, it is necessary to point out such problems and propose improved methods.

Results: Our results confirm that the standard permutation method overestimates the FDR. With the correct FDR formula, we show the method of Xie et al. (2005) always gives biased estimation of FDR: it overestimates when the number of claimed significant genes is small, and underestimates when the number of claimed significant genes is large. To overcome these problems, we propose two modifications. The results show that our estimator gives more accurate estimation.

Contact: szhang3{at}unl.edu

Associate Editor: Dr. Alex Bateman

Received on February 14, 2008; revised on June 11, 2008; accepted on June 12, 2008

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Bioinformatics, October 15, 2008; 24(20): 2420 - 2420.
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