[BioC] GSEA with methylation data
dwu at fas.harvard.edu
Sun May 20 23:24:30 CEST 2012
Th function wilcoxGST in limma package, which is a synonym for geneSetTest with ranks.only=TRUE, will do gene set test for ranks of statistics.
In your case, you can put the ranks of t statistics as "statistics".
Comparing to Hypergeometric tests, Wilcoxon mean rank tests of gene set take care the detail of statistics and require no t statistic cutoff. Both Hypergeometric tests and Wilcoxon mean rank tests assumes genes are independent.
Of course, if there are correlations among the genes in the methylation data (I am not sure ...), other functions dealing with correlations, e.g., "roast", "camera", or "romer" in limma may be helpful. This may depend on the distribution of your normalized methylation data.
Hope this help.
Harvard University, Statistics Department
Harvard Medical School
Science Center, 1 Oxford Street, Cambridge, MA 02138-2901 USA
From: bioconductor-bounces at r-project.org [bioconductor-bounces at r-project.org] On Behalf Of Tim Smith [tim_smith_666 at yahoo.com]
Sent: Sunday, May 20, 2012 11:57 AM
Subject: [BioC] GSEA with methylation data
I wanted to conduct GSEA analysis on methylation data (illumina 27k). After conducting a differential analysis, I have a list of genes along with their pvalues and t-statistics. Is there a way that I can conduct a GSEA analysis with this data? Which packages should I be looking at?
I have looked at a few of the GSEA packages, but they all seem to be based on gene expression data (and chips/annotation packages etc.).
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