Bioinformatics Advance Access originally published online on September 18, 2006
Bioinformatics 2006 22(22):2825-2827; doi:10.1093/bioinformatics/btl476
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RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis
1 Plant Biology Laboratory La Jolla, CA, USA
2 Howard Hughes Medical Institute, The Salk Institute La Jolla, CA, USA
3 Groningen Bioinformatics Centre, University of Groningen Haren, The Netherlands
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.
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) FEBS Lett., 573, 8392] 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
Contact: fhong{at}salk.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Received on March 18, 2006; revised on August 22, 2006; accepted on September 3, 2006
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