Ying, This is getting close to the top of the to-do list. I'll probably get to it in the next month. In the meantime, you can always make your own vectors using the frmaTools package. Best, Matt On Tue, Apr 22, 2014 at 2:07 PM, ying chen <ying_chen at="" live.com=""> wrote: > Hi Matt, > > I just wonder is it possible for you to update the hgu133plus2frmavecs > packages to use the most recent customCDF v18? > > Thanks a lot, > > Ying > >> Date: Tue, 22 Apr 2014 10:40:33 -0400 >> From: mccallm at gmail.com >> To: sbrohee at ulb.ac.be >> CC: basvgestel at hotmail.com; bioconductor at r-project.org >> Subject: Re: [BioC] Comparison of murine and human microarray data > >> >> Bas, >> >> My (biased) recommendation would be fRMA + barcode. Comparing human >> and mouse microarray data is Figure 2 of the barcode paper: >> http://nar.oxfordjournals.org/content/39/suppl_1/D1011.full >> >> You still need to be careful with the orthologous gene mapping. >> >> Best, >> Matt >> >> >> On Tue, Apr 22, 2014 at 10:22 AM, Sylvain Broh?e <sbrohee at="" ulb.ac.be=""> >> wrote: >> > Hi Bas, >> > >> > First of all, I would say that I would not recommend to to this kind of >> > stuff as it seems kind of dirty to me. >> > >> > However, recently, I was 'kindly' asked to perform this type of analyze >> > and >> > I used the good old ComBat function from the sva package to remove the >> > batch >> > effect between human and mouse. In order to have a reliable matrix from >> > the >> > beginning, I used only those genes that had the same gene names (in >> > capital >> > letters for mouse). >> > >> > This is the code I used : >> > >> > Let's eset be the mouse dataset and human.exp.names.agg be the human >> > dataset. Genes are in rows and experiments in columns. >> > >> > row.names(eset) <- toupper(row.names(eset)) >> > human.mouse.complete <- merge(human.exp.names.agg, eset, by = >> > 'row.names') >> > row.names(human.mouse.complete) <- human.mouse.complete[,1] >> > human.mouse.complete <- human.mouse.complete[,-1] >> > pheno.mod0 <- data.frame(row.names = names(human.mouse.complete), fact.1 >> > = >> > rep(1, ncol(human.mouse.complete)), fact.2 = rep(2, >> > ncol(human.mouse.complete))) >> > mod0 <- model.matrix(~1, data = pheno.mod0) >> > human.mouse.complete.combat <- ComBat(human.mouse.complete, c(rep(1, >> > human.exp.nb), c(rep(2,22))), mod = mod0) >> > >> > It seemed to give satisfactory results. >> > >> > If there are more "clever" ways, I would be happy to hear about them! >> > >> > Cheers, >> > >> > Sylvain >> > >> > >> > >> > On 04/22/2014 04:04 PM, Bas van Gestel wrote: >> >> >> >> Dear all, >> >> For a project I would like to compare the gene expression of different >> >> immune cells in both mouse and human. For the immune cells of interest, >> >> microarray data is available. The microarray data for the human immune >> >> cells >> >> have been generated with the same platform. The microarray data for the >> >> murine immune cells have been generated with the same platform, >> >> although >> >> with a different platform than used for the human immune cells. I >> >> performed >> >> RMA normalization using the rma function in the affy package separately >> >> for >> >> the human and the murine datasets. However, I would like to compare the >> >> gene >> >> expression levels of mouse and human immune cells. I therefore would >> >> like to >> >> ask you the following questions:What is the recommended way to >> >> normalize the >> >> RMA normalized datasets of human and mouse, so that I can >> >> compare/combine >> >> both datasets? >> >> Thanks a lot for your help. >> >> Kind regards, Bas >> >> [[alternative HTML version deleted]] >> >> >> >> _______________________________________________ >> >> Bioconductor mailing list >> >> Bioconductor at r-project.org >> >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> >> Search the archives: >> >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > >> > >> > _______________________________________________ >> > Bioconductor mailing list >> > Bioconductor at r-project.org >> > https://stat.ethz.ch/mailman/listinfo/bioconductor >> > Search the archives: >> > http://news.gmane.org/gmane.science.biology.informatics.conductor >> >> >> >> -- >> Matthew N McCall, PhD >> 112 Arvine Heights >> Rochester, NY 14611 >> Cell: 202-222-5880 >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880