Hi Massimo, the intention of the genes.rpt.agi function is to detect which genes are interrogated by different probes at different chromosomal location. I think it could be somewhat dangerous to summarize the expression values of those genes in the Agilent chips, sometimes you can find the same gene differentially expressed in different directions. So, that function is just to identify what genes are interrogated by different probes. As Francois says, for the differential analysis do not make any summary of those replicated genes, analyze them independenlty and then see what happens.. p.- On Tue, Oct 20, 2009 at 3:45 PM, Francois Pepin <fpepin@cs.mcgill.ca> 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 >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]