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Bioinformatics Advance Access published online on December 20, 2005
Bioinformatics, doi:10.1093/bioinformatics/btk013
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received August 29, 2005
Revised December 14, 2005
Accepted December 15, 2005

Article

Multidimensional local false discovery rate for microarray studies

Alexander Ploner 1 *, Stefano Calza 2, Arief Gusnanto 3, and Yudi Pawitan 1

1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden
2 Dip. di Scienze Biomediche e Biotecnologie, Università degli Studi di Brescia, 11 25123 Brescia, Italy
3 MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 2SR, United Kingdom

* To whom correspondence should be addressed.
Alexander Ploner, E-mail: alexander.ploner{at}meb.ki.se


  Abstract

Motivation: The false discovery rate (fdr) is a key tool for statistical assessment of differential expression (DE) in microarray studies. Overall control of the fdr alone, however, is not sufficient to address the problem of genes with small variance, which generally suffer from a disproportional high rate of false positives. It is desirable to have an fdr-controlling procedure that automatically accounts for gene variability.

Methods: We generalize the local fdr as a function of multiple statistics, combining a common test statistic for assessing differential expression with its standard error information. We use a nonparametric mixture model for DE and nonDE genes to describe the observed multi-dimensional statistics, and estimate the distribution for nonDE genes via the permutation method. We demonstrate this fdr2d approach for simulated and real microarray data.

Results: The fdr2d allows objective assessment of differential expression as a function of gene variability. We also show that the fdr2d performs better than commonly-used modified test statistics.

Availability: An R-package OCplus containing functions for computing fdr2d() and other operating characteristics of microarray data is available at http://www.meb.ki.se/~yudpaw.


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