[BioC] Questions about limma
sdavis2 at mail.nih.gov
Wed Apr 6 21:24:46 CEST 2005
On Apr 6, 2005, at 1:44 PM, He, Yiwen (NIH/CIT) wrote:
> Hi Sean,
> Thanks for your help!
> lmFit didn't work on my log ratio data because the data was not
> numeric, so I got all NAs for the result. It's now working after I
> converted it to numeric.
Glad to hear it.
> I did read the User's guide and saw those case studies. However, I was
> not able to find any test data that I can load into R to run the test.
> Can you point me to the right place?
You are right. I spoke too quickly--it doesn't look like the example
files are included--sorry about that! It looks like they are available
> I have a general question: How is limma compared with other
> statistical analysis like SAM? I ran both procedures on the same
> dataset (one class) and got similar results (28 out of the 30 top
> genes overlap, orders differ slightly). But the significant levels
> (p/B for limma and q for SAM) differ. For small sample size, SAM's q
> is bigger than limma's p values, on the other hand, when sample size
> is large, q is much smaller. I understand limma uses empirical bayes
> mothods so that it works on small number of replicates. What are the
> other advantages of limma?
As for p/q values, they will be different--are you using fdr multiple
comparisons correction? I don't generally use siggenes much, though,
so I don't know how they compare in practice. As for other advantages
of limma, it does linear modeling of experiments, so many complex
experimental designs can be handled in the same framework.
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