Finding common genes in multiple cancer types through meta-analysis of microarray experiments: a rank aggregation approach.
Discovering genes involved in multiple types of cancers is of significant therapeutic importance. We show that collective evidence for such genes can be obtained via a form of meta-analysis that aggregates the results (rankings and p values) from various cancer-specific microarray experiments. This method is illustrated by a combined analysis of 20 microarray experiments. In the aggregated list of top-50 genes, 36 of them have been implicated in cancer (often multiple cancers) genesis in past studies, which also suggests that this list may contain some novel cancer genes that may deserve further scrutiny in the future.
Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA.
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D014408:Biomarkers, Tumor / Q000235:genetics*; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D015972:Gene Expression Regulation, Neoplastic; D052138:Genes, Neoplasm; D006801:Humans; D015201:Meta-Analysis as Topic; D009369:Neoplasms / Q000235:genetics*
D014408:Biomarkers, Tumor