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

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ID: 306055
2006
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Abstract
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 . A web-based interface will soon be available at Contact: fhong@salk.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W2172215633 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Fangxin Hong, Rainer Breitling, Connor McEntee, Ben S. Wittner, Jennifer L. Nemhauser, Joanne Chory
Journal BMC Bioinformatics
Year 2006
DOI
10.1093/bioinformatics/btl476
URL
https://doi.org/10.1093/bioinformatics/btl476
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