Hi, It depends entirely on the biology of the experiment and you have said nothing about that. For most experiments, the experimentor knows, a priori, that only a small number of genes are likely to change (in the low hundreds). If you did an experiment where you anticipate lots of genes changing expression values, then as has already been pointed out, the assumptions of most normalization methods are not met. What to do in that case is up to you and would require consultation with a local expert, IMHO. best wishes Robert E Motakis, Mathematics wrote: > Dear all, > > I am working on two colours microarray experiments and, from a set of 42000 > genes, I would like to identify the differentially expressed ones. I have > read several articles on this issue and most of them imply that the number > of differential expressed genes in such experiments should be a small > number (compared to the whole set). > > Could anyone tell me why this is correct? What if I find half of the genes > to be differentially expressed according to the t-test p-value? > > I am not discussing the issue of p-values and q-values yet. I am asking > only about why most of the papers imply a low number of differentially > expressed genes. > > Thank you, > Makis > > > ---------------------- > E Motakis, Mathematics > E.Motakis at bristol.ac.uk > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Robert Gentleman, PhD Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 PO Box 19024 Seattle, Washington 98109-1024 206-667-7700 rgentlem at fhcrc.org

Dear Makis, I think the idea is that the normalization methods must assume that the expression is basically the same between the types of cells in order to work. This might not always be in fact the case, but if it isn't, then the use of methods like quantile normalization to reduce technical variation leaving only biological normalization become suspect. Anyway, that's my take. I would love to hear from people more knowledgeable than myself on this issue. Best wishes, Rich On May 26, 2006, at 11:06 AM, E Motakis, Mathematics wrote: > Dear all, > > I am working on two colours microarray experiments and, from a set of > 42000 > genes, I would like to identify the differentially expressed ones. I > have > read several articles on this issue and most of them imply that the > number > of differential expressed genes in such experiments should be a small > number (compared to the whole set). > > Could anyone tell me why this is correct? What if I find half of the > genes > to be differentially expressed according to the t-test p-value? > > I am not discussing the issue of p-values and q-values yet. I am asking > only about why most of the papers imply a low number of differentially > expressed genes. > > Thank you, > Makis > > > ---------------------- > E Motakis, Mathematics > E.Motakis at bristol.ac.uk > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > ------------------------------------------------------------ Richard A. Friedman, PhD Associate Research Scientist Herbert Irving Comprehensive Cancer Center Oncoinformatics Core Lecturer Department of Biomedical Informatics Box 95, Room 130BB or P&S 1-420C Columbia University Medical Center 630 W. 168th St. New York, NY 10032 (212)305-6901 (5-6901) (voice) friedman at cancercenter.columbia.edu http://cancercenter.columbia.edu/~friedman/ "Cartesian duelism is when somebody told Decartes that he didn't think therefore he was, and Descartes challenged him to a duel". -Isaac Friedman, age 16