[BioC] Limma then Annaffy? solved

[davidl@unr.nevada.edu]

Thank you everyone,

    Its amazing how fast I got several really helpful responses to my
question...you guys are awesome. The getText function Eric Kort suggested
worked well and I'll definately try out limma2annaffy, since that is pretty
much exactly what I asked for.

Very appreciative,

Dave

Quoting "James W. MacDonald" <jmacdon at med.umich.edu>:

> 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.
>
>
> Best,
>
> Jim
>
>
> >
> >      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
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor at stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/bioconductor
>
>
> --
> James W. MacDonald
> University of Michigan
> Affymetrix and cDNA Microarray Core
> 1500 E Medical Center Drive
> Ann Arbor MI 48109
> 734-647-5623
>
>
>
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