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Bioinformatics Advance Access published online on September 18, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl476
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received March 18, 2006
Revised August 22, 2006
Accepted September 3, 2006

Applications note

RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis

Fangxin Hong 1 *, Rainer Breitling 2, Connor W. McEntee 3, Ben S. Wittner 4, Jennifer L. Nemhauser 5, and Joanne Chory 1

1 Plant Biology Laboratory, The Salk Institute, La Jolla, CA, USA; Howard Hughes Medical Institute, The Salk Institute, La Jolla, CA, USA
2 Groningen Bioinformatics Centre, University of Groningen, Haren, The Netherlands
3 Plant Biology Laboratory, The Salk Institute, La Jolla, CA, USA
4 Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
5 Department of Biology, University of Washington, Seattle, WA, USA

* To whom correspondence should be addressed.
Fangxin Hong, E-mail: fhong{at}salk.edu


  Abstract

Summary: While meta-analysis provides a powerful tool for analyzing microarray experiments by combining data from multiple studies, it presents unique computational challenges. The Bioconductor package RankProd provides a new and intuitive tool for this purpose in detecting differentially expressed genes under two experimental conditions. The package modifies and extends the rank product method proposed by Breitling et al (2004) to integrate multiple microarray studies from different laboratories and/or platforms. It offers several advantages over t-test based methods and accepts pre-processed expression datasets produced from a wide variety of platforms. The significance of the detection is assessed by a non-parametric permutation test, and the associated p-value and false discovery rate (FDR) are included in the output alongside the genes that are detected by user-defined criteria. A visualization plot is provided to view actual expression levels for each gene with estimated significance measurements.

Availability: RankProd is available at Bioconductor http://www.bioconductor.org. A web-based interface will soon be available at http://cactus.salk.edu/RankProd.

Associate Editor: Satoru Miyano
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