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Dear David, At 03:16 AM 2/12/2005, Dr. D. P. Kreil wrote: >Dear Sir/Madam, > >I would be grateful for your comments regarding the interpretation of the >"proportion" parameter of limma's eBayes function. > >The documentation says: "assumed proportion of genes which are >differentially expressed". > >How does that relate to more complex linear models with multiple >coefficients/contrasts? In topTable, using the "coef" parameter, a linear >model coefficient or contrast can be specified. In that context, >differential expression directly makes sense. The eBayes routine, however, >does not take a "coef" parameter, so what is the meaning of >"differentially expressed" there for a linear model, in general? The meaning is that the same proportion is assumed to apply for every contrast. This may admitedly be unrealistic. >Is that 1 minus the proportion of genes that are non-differentially >expressed in all contrasts? In that case, the more complex the model, the >smaller "proportion" should be set, correct? No. I can't see any reason to think so. > If trying to crudely estimate the parameter from the data, what would > you recommend? I recommend not estimating it, for reasons that I explain in Section 6.4 of Smyth (2004) (http://www.statsci.org/smyth/pubs/ebayes.pdf). You're certainly free to vary the proportion based on your biological understanding of the process for each fit or contrast. Best wishes Gordon >I am very much looking forward to your comments / thoughts about >interpreting and/or setting the "proportion" parameter. (I know it doesn't >affect the ranking. We are nevertheless trying to get some meaning out of >the B statistic.) > >With many thanks for your help in adance, >yours sincerely, > >David. >(Boku University, Vienna)