[BioC] Affy: probeset to gene expression with expresso

[Helen Smith]

Hi, 

Thank you Jim. 

Can I ask, I have always averaged the expressions and they completed pathway analysis for the genes rather than the probes. Do you consider it better to leave it as individual probes and assess individual expression at the pathway level?
I'm torn as to which is the best approach, 

Thanks, 
Helen

-----Original Message-----
From: bioconductor-bounces at r-project.org [mailto:bioconductor-bounces at r-project.org] On Behalf Of James W. MacDonald
Sent: 13 August 2013 16:28
To: Martin Preusse
Cc: bioconductor at r-project.org
Subject: Re: [BioC] Affy: probeset to gene expression with expresso

Hi Martin,

I just answered a very closely related question. See if this helps:

https://stat.ethz.ch/pipermail/bioconductor/2013-August/054353.html

Best,

Jim



On 8/13/2013 9:47 AM, Martin Preusse wrote:
> I am trying to get the gene level expression values from an Affy micro array, i.e. merge the values for probe sets representing the same gene.
>
> I tried to use the 'expresso' function from the affy package, but I always end up with an ExpressionSet containing probe sets, not genes.
>
> What is an easy way to summarize/merge probe sets to (entrez) genes?
>
>
> library(affydata)
> library(affy)
>
> # get the 'Dilution' affy batch
> data(Dilution)
>
> eset<- expresso(Dilution, bgcorrect.method='rma', 
> normalize.method='constant', pmcorrect.method='pmonly',
> summary.method='avgdiff')
>
>
> write.exprs(eset,'testfile.txt')
>
>
> P.S.: I know it might not be the best idea to average probe sets, but 
> I would like to try ;)
>
> Cheers
> Martin
>
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--
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
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Seattle WA 98105-6099

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