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?

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?  If trying to crudely estimate
the parameter from the data, what would you recommend?

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)

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