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

Fangxin Hong, Rainer Breitling, Connor W. McEntee, Ben S. Wittner, Jennifer L. Nemhauser, Joanne Chory

    Research output: Contribution to journalArticlepeer-review

    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. © 2006 Oxford University Press.
    Original languageEnglish
    Pages (from-to)2825-2827
    Number of pages2
    JournalBioinformatics
    Volume22
    Issue number22
    DOIs
    Publication statusPublished - 15 Nov 2006

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