Hello, I have my results after running a microarray analysis. In general, the analysis is basically comparing gene expressions in 1 tumor group to another. Below are my relevant codes: mm2 <- model.matrix(~TumorType, pData(eset2)) fit2 <- lmFit(eset2, mm2) fit2 <- eBayes(fit2) Now I want to extract the top 50 up-regulated genes, but I am not sure how to do so. I know with toptable function, I can extract the top differentially expressed genes, but what if I only want the up- regulated ones? Thanks in advance! Sincerely, Casper [[alternative HTML version deleted]]

tops <- topTable(fit2, number=Inf) # get all genes tops[which(tops$logFC > 0), ] [1:50,] # up reg top 50 tops[which(top$logFC < 0), ] [1:50,] # down reg top 50 best i --- On Wed, 2/3/11, Casper Shyr <casshyr at="" hotmail.com=""> wrote: tops <- topTable(fit2, number=Inf) > From: Casper Shyr <casshyr at="" hotmail.com=""> > Subject: [BioC] Extracting top upregulated genes from Limma analysis > To: bioconductor at r-project.org > Date: Wednesday, 2 March, 2011, 5:41 > > Hello, > ? I have my results after running a microarray > analysis. In general, the analysis is basically comparing > gene expressions in 1 tumor group to another. > ? Below are my relevant codes: > > mm2 <- model.matrix(~TumorType, pData(eset2)) > fit2 <- lmFit(eset2, mm2) > fit2 <- eBayes(fit2) > > ? Now I want to extract the top 50 up-regulated genes, > but I am not sure how to do so. I know with toptable > function, I can extract the top differentially expressed > genes, but what if I only want the up-regulated ones? > > Thanks in advance! > Sincerely, > Casper > ??? > ???????? > ?????? ??? > ? > ??? [[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 >

On Wed, Mar 2, 2011 at 12:41 AM, Casper Shyr <casshyr@hotmail.com> wrote: > > Hello, > I have my results after running a microarray analysis. In general, the > analysis is basically comparing gene expressions in 1 tumor group to > another. > Below are my relevant codes: > > mm2 <- model.matrix(~TumorType, pData(eset2)) > fit2 <- lmFit(eset2, mm2) > fit2 <- eBayes(fit2) > > Now I want to extract the top 50 up-regulated genes, but I am not sure how > to do so. I know with toptable function, I can extract the top > differentially expressed genes, but what if I only want the up- regulated > ones? > > Hi, Casper. Take a look at the sort.by argument to topTable. Sean [[alternative HTML version deleted]]

Hello Casper, This is from memory so double check it but the following should work: results <- decideTests(fit2, method="global") up <- which(results[,1] == 1) upGenes <- fit2[up, ] upTable <- topTable(upGenes[,4], number = 50, adjust.method= "BH", sort.by="p") The decideTests function assigns "upregulated" (actually DE genes in a positive direction) genes as "1" and "-1" for "downregulated" genes. HTH, noah On Mar 1, 2011, at 9:41 PM, Casper Shyr wrote: > > Hello, > I have my results after running a microarray analysis. In general, the analysis is basically comparing gene expressions in 1 tumor group to another. > Below are my relevant codes: > > mm2 <- model.matrix(~TumorType, pData(eset2)) > fit2 <- lmFit(eset2, mm2) > fit2 <- eBayes(fit2) > > Now I want to extract the top 50 up-regulated genes, but I am not sure how to do so. I know with toptable function, I can extract the top differentially expressed genes, but what if I only want the up- regulated ones? > > Thanks in advance! > Sincerely, > Casper > > [[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