Hi Stephen,

one option is to simply average multiple probes matching to the same
transcript, using the avereps()-function (from the limma package). It takes
an ID-argument, where you specify the transcipt (or maybe even
"locus")-names, so that probes with the same IDs will be averaged.
If you have duplicate probes (technical replicates, that is the same probe
sequences etc), then avedups will do the job.

There might be other options too?

As far as I know, rma/gcrma for Affy arrays are wrappers for a combination
of functions, that includes background correction, quantile normalization
and median polish summarization of the 11 probes, and as you have done the
first two steps with your arrays, that is no longer necessary (plus I guess
you do often have only 1-2 probes per transcript anyway, so there would not
be a "median polish" option for that anyway).

Hope this helps, best Sam

On 11 January 2012 21:45, Stephen Turner <vustephen@gmail.com> wrote:

> Hello.
>
> I have 4 Agilent two-channel arrays that I read in using read.maimages().
> I've done normalization and background subtraction. How do I now summarize
> the probe information (62976 probes) to gene-level expression values (39430
> entrez RNAs, 16251 lincRNAs). I normally did this using rma() or gcrma()
> from the affy package when I have Affymetrix data.
>
> Thanks,
>
> Stephen
>
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-- 
-----------------------------------------------------
Samuel Wuest
Smurfit Institute of Genetics
Trinity College Dublin
Dublin 2, Ireland
Phone: +353-1-896 2444
Web: http://www.tcd.ie/Genetics/wellmer-2/index.html
Email: wuests@tcd.ie
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