kfbargad at ehu.es wrote: > Dear list, > > I have three groups of samples (Tto, NoTto, C) and have made the three > possible pairwise contrasts as follows: > > design.tto <- model.matrix(~-1+factor(c > (1,1,2,2,2,3,2,1,3,1,2,2,3,1,1,2,1,1,3,1))) > colnames(design.tto) <- c("C","Tto", "NoTto") > > fit.tto <- lmFit(eset,design.tto) > contrast.matrix.tto <- makeContrasts(Tto-C,NoTto-C, Tto-NoTto, levels > = design.tto) > fit2.tto <- contrasts.fit(fit.tto, contrast.matrix.tto) > fit3.tto <-eBayes(fit2.tto) > > If I select all d.e (p<0.05) genes from each contrast of interest I > get the same number of genes, 463, although different Do you mean that you get the same number of genes, but they aren't necessarily the same genes? > > topTable(fit3.tto, coef = X(where X =1,2 or 3)#, adjust="none", > sort.by="P", number=5506); NoTto_vs_C_y <- NoTto_vs_C[x$P.Value < > 0.05,] I assume this is just a snippet of code intended to give the general idea of what you have done? If so, is it possible that your actual code did the same exact thing three times? > > dim(Tto_vs_C_y) > [1] 463 7 > >>dim(NoTto_vs_C_y) > > [1] 463 7 > >>dim(Tto_vs_NoTto_y) > > [1] 463 7 > > > Is this normal? I wouldn't say it is normal, but it certainly is possible. These days limma has code to do exactly what you have done that you can use to check your results. rslt <- decideTests(fit3.tto, adjust="n") vennDiagram(rslt) HTH, Jim > > Thanks in advance > > David > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald University of Michigan Affymetrix and cDNA Microarray Core 1500 E Medical Center Drive Ann Arbor MI 48109 734-647-5623 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues.