[BioC] limma eBayes: how to determine goodness of fit?
Mark Robinson
mrobinson at wehi.EDU.AU
Wed Jun 6 12:22:28 CEST 2007
Hi Paul.
Thanks for the explanation, I see what you are doing. I would call
what you are doing 'model selection' and its true, limma doesn't do
that. But, you can probably fit a 'full' model and just look for the
differences that you describe, all within limma.
For example, you could fit a model:
~ -1 + M1 + M2 + M3
where M1-M3 are binary indicators of the signal samples. So this
fits a model with no intercept and a different mean for each 'signal'
sample. If I understand your problem correctly, you are looking for
genes that are non-zero in each of coefficients for M1-M3 (like you
gene1 and gene2). But, you are also interested in genes which have
non-zero in M1,M2 and maybe not so in M3 (your gene3). These are
just contrasts. So, you should be able to look for everything you
are interested in, by constructing contrasts on M1-M3.
Alternatively, you could fit all the possible models you are
interested in and filter all the topTables. There are not that many.
Just one other note ....
> I was happy to see that I found small residuals, and a high R-
> squared when I modeled gene3
> like this:
I think you'll find that small residuals (or at least small relative
to the signal) and high R-squares correspond to large (in magnitude)
t-statistic or large Fs. So, everything you need is in limma.
Hope that helps.
Cheers,
Mark
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