[BioC] Limma then Annaffy?

James W. MacDonald jmacdon at med.umich.edu
Fri Dec 30 14:55:58 CET 2005

davidl at unr.nevada.edu wrote:
> Hello all,
>      Ive been searching the mail archives for about 2 hours without any luck on
> finding an answer to this problem.  I was just wondering if there was a way to
> take the results that I obtained from limma and plug them into some sort of
> annotation package (such as annaffy).  I am using affymetrix moe4302 gene chips
> and would like to learn more about the genes limma found to be differentially
> expressed between my two groups.  I was able to use multtest and annaffy to
> create the html table, but I would really like to use the differentially
> expressed genes from limma (the ones you see in topTable, etc.)

You could use limma2annaffy() in the affycoretools package. This package 
is in the 1.8 devel repository, so unless you have R-2.3.0, you will not 
be able to use biocLite() to install. However, it will work with all 
existing versions of limma, annaffy, R, etc, so just download and 
install by hand.



>      Also, in searching the mail archives, I saw a few emails indicating that
> the adjusted p-values and B values found with limma should not be considered
> absolutely correct because of assumptions limma makes about normality (or
> something along those lines).  Does this mean that it would be wise to use
> another package (or another program?) to find p-values for differential
> expression?  I would like to find p-values at some point that are meaningful,
> to a certain extent, on their own, as opposed to p-values which indicate just
> the relative order of differential expression among genes (and aren't
> associated with an actual probability of the absence of differential
> expression)(that was worded weird, sorry).  If the assumptions about normality
> are the problem, is there a wilcoxon type test that would come reccomended as
> part of a bioconductor package? I'm interested in using a fdr type adjustment
> for deciding my p-value cut-offs.  Is there any concensus as to the best way to
> do this right now?
>       Basically, Im just really overwhelmed by the variety of analysis methods
> that exist right now for microarrays.  I'm sorry if the answer to my first
> question is located in a conspicuous place that I happened to miss and I'm very
> appreciative of any any help that anyone would like to offer.
> Thank you very much,
> Dave
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James W. MacDonald
University of Michigan
Affymetrix and cDNA Microarray Core
1500 E Medical Center Drive
Ann Arbor MI 48109

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