[BioC] Analyzing single-channel genepix data from Genepix in Limma
smyth at wehi.EDU.AU
Sat May 12 12:40:23 CEST 2007
Without creating a new object, you could pass the weights to lmFit()
using the weights= argument, then pass the annotation to topTable()
using the genelist= argument.
If your annotation is just a single vector of gene IDs, you can add
this to RG$G as rownames (it may complain if not unique).
Alternatively, you could assemble an ExpressionSet object. Others can
better advise you how to do that than me.
>Date: Fri, 11 May 2007 10:02:27 -0400
>From: "Lance E. Palmer" <lance.palmer at stonybrook.edu>
>Subject: [BioC] Analyzing single-channel genepix data from Genepix in
>To: bioconductor at stat.math.ethz.ch
>Message-ID: <1178892147.26381.102.camel at informatics.bio.sunysb.edu>
>Hi I just wanted some advice on analyzing single channel data from
>Genepix in Limma.
>There are a number of slides that have bad cy5 signals and other chips
>where on cy3 was used, so I wanted to be able to just analyze the cy3
>After a search of the newsgroup, there was a post by Gordon that
>basically says use this:
>y2 <- normalizeBetweenArrays(RG$G, method="quantile")
>(or use vsn)
>and then run Limma normally.
>I was wondering if this is still the preferred method? If one just
>passes the cy3 channel values to lmFit, the weights don't seem to be
>passed along. Is there any way of combining the annotation, weights
>and expression values into an object that lmFit can recognize?
More information about the Bioconductor