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Developing a Parametric Method for Testing the Significance of Gene Sets in Microarray Data Analysis
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 Title & Authors
Developing a Parametric Method for Testing the Significance of Gene Sets in Microarray Data Analysis
Lee, Sun-Ho; Lee, Seung-Kyu; Lee, Kwang-Hyun;
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The development of microarray technology makes possible to analyse many thousands of genes simultaneously. While it is important to test each gene whether it shows changes in expression associated with a phenotype, human diseases are thought to occur through the interactions of multiple genes within a same functional cafe-gory. Recent research interests aims to directly test the behavior of sets of functionally related genes, instead of focusing on single genes. Gene set enrichment analysis(GSEA), significance analysis of microarray to gene-set analysis(SAM-GS) and parametric analysis of gene set enrichment(PAGE) have been applied widely as a tool for gene-set analyses. We describe their problems and propose an alternative method using a parametric analysis by adopting normal score transformation of gene expression values. Performance of the newly derived method is compared with previous methods on three real microarray datasets.
Microarray experiment;single gene analysis;gene set analysis;normal score;
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