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

Authors:
Fangxin Hong;Rainer Breitling;Connor W. Mcentee;Ben S. Wittner;Jennifer L. Nemhauser;Joanne Chory
Affiliations:
Plant Biology Laboratory La Jolla, CA, USA;Groningen Bioinformatics Centre, University of Groningen Haren, The Netherlands;Plant Biology Laboratory La Jolla, CA, USA;Center for Cancer Research, Massachusetts General Hospital Boston, MA, USA;Department of Biology, University of Washington Seattle, WA, USA;Plant Biology Laboratory La Jolla, CA, USA
Venue:
Bioinformatics
Year:
2006

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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) FEBS Lett., 573, 83--92] 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@salk.edu Supplementary information: Supplementary data are available at Bioinformatics online.