[BioC] Agi4x44PreProcess 1.4.0 question: use of genes.rpt.agi() and Gene Sets

[Tobias Straub]

Hi

key question regarding your problem is the confidence in the  
measurement of a single agilent feature. in affy 3' expression arrays  
a robust measurement is obtained by summarization of several features.  
for the modern affy gene st arrays the gene-based expression  
measurement is also obtained by feature summarization across exons (at  
least this is what the affy epxression console forces you to do).

hence, the most intuitive and biologically relevant procedure would be  
to apply feature summarization accordingly for agilent arrays before  
doing the statistics. the question how this summarization has to be  
done cannot easily be answered without analysis of reference samples.  
my personal experience: there is not a big difference between taking  
the median signal or just taking the feature with the highest  
variance. if you are particularly interested in categorizing  
responders, the variance method is probably more sensitive.

best
Tobias

On Oct 20, 2009, at 4:45 PM, Francois Pepin wrote:

> Hi Massimo,
>
> I don't know about Agi4x44PreProcess, but Limma can do it with  
> avereps.
>
> In the case of Agilent arrays, I would not recommend doing that from  
> the start. The probes mapping to the same genes often do not measure  
> the same thing, they can map different splice variants and some can  
> be pretty far from the 3' end.
>
> So for differential analysis, I would suggest keeping them  
> different. For other analyses that assume one probe per gene, such  
> as gene ontology analysis, I would recommend an unbiased method to  
> choose a representative probe per gene, for example the highest  
> variance probe or the one closest to 3' end.
>
> If you search in the archives, you can find more advice as this is a  
> common topic.
>
> Francois
>
> Massimo Pinto wrote:
>> Greetings all,
>> I realised that I was carrying forward, in my analysis, multiple
>> measurements for the same gene that had been carried out using
>> independent probes. This is a feature of Agilent arrays, as I
>> understand. However, while it is clear to me that Agi4x44PreProcess
>> offers a function to summarize replicated probes, called
>> summarize.probe(), I cannot see a readily available function that
>> performs a similar treatment to replicated genes, i.e. Gene Sets, as
>> these are called in the Agi4x44 Package.
>> The result of calling
>>> genes.rpt.agi(dd, "hgug4112a.db", raw.data = TRUE, WRITE.html =  
>>> TRUE, REPORT = TRUE)
>> is an html list of Gene Sets, but these are not summarized to a
>> 'virtual' measurement, like summarize.probe() does for replicated
>> probes.
>> Is there a reason why one would like to carry on multiple probes  
>> for a
>> given gene throughout his/her subsequent analysis, including linear
>> modeling and gene ontology? If not, is there a function that performs
>> the median of such repeats?
>> Thank you in advance,
>> Yours
>> Massimo Pinto
>>> sessionInfo()
>> R version 2.9.1 (2009-06-26)
>> i386-apple-darwin8.11.1
>> locale:
>> C
>> attached base packages:
>> [1] grid      stats     graphics  grDevices utils     datasets
>> methods   base
>> other attached packages:
>> [1] affy_1.22.0             gplots_2.7.0            caTools_1.9
>>      bitops_1.0-4.1          gdata_2.4.2             gtools_2.5.0-1
>> [7] hgug4112a.db_2.2.11     RSQLite_0.7-1           DBI_0.2-4
>>      Agi4x44PreProcess_1.4.0 genefilter_1.24.0       annotate_1.22.0
>> [13] AnnotationDbi_1.6.0     limma_2.18.0            Biobase_2.4.1
>> loaded via a namespace (and not attached):
>> [1] affyio_1.11.3        preprocessCore_1.5.3 splines_2.9.1
>> survival_2.35-4      xtable_1.5-5
>> Massimo Pinto
>> Post Doctoral Research Fellow
>> Enrico Fermi Centre and Italian Public Health Research Institute  
>> (ISS), Rome
>> http://claimid.com/massimopinto
>> _______________________________________________
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>
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----------------------------------------------------------------------
Tobias Straub   ++4989218075439   Adolf-Butenandt-Institute, München D