[BioC] Multiple class gene finding
sdavis2 at mail.nih.gov
Thu Jun 17 12:41:01 CEST 2004
I have a dataset with many classes and would like to find the genes
associated (differentially expressed) with each class. The experimental
design is two-color with a common reference. I am not interested in
differential expression between the reference and the sample, but only the
differences between samples. One approach would be to do T-tests between
ratios for each group and all others. Another would be to use F-statistics
to determine those genes that are differentially expressed in a more general
sense. What I really want, I think, is a combination of the two so that I
can label each gene with class(es) and know that it is differentially
expressed across samples. What functions exist for doing something like
this? I think the limma package provides ClassifyTestsF which looks useful.
Are there others? Have others used other approaches?
Sean Davis, M.D., Ph.D.
National Institutes of Health
Postdoctoral Research Fellow
National Human Genome Research Institute
National Cancer Institute
Johns Hopkins University
Department of Pediatric Oncology
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