Dear All, I have problems in understanding what is the interpretation of default output of interaction contrast and how can I change the default settings (resultsNames(results)) and explore other interactions? For example, here are the 3 factors I am interested in: 1. treatment; levels: disease and control 2. localization; levels: A and B. 3. sex; levels: male and female If the design1 is: ~sex + treatment*localization, by default, the reported contrast in the results is: Wald test p-value: treatmentdisease.localizationA. Q1: Can I interpret the output as a list of genes that are diff.expressed (DE) between localization A and localization B in a disease? Q2: How could I get the DE genes between localization A and localization B in a control? Or DE genes between disease and control for localization A? If I change the order of factors in a design: design2= ~sex + treatment*localization, then by default in the results I get Wald test p-value: localizationA.treatmentdisease. Can I interpret this as a list of DE genes between disease and control in localization A? I tried it, but the results were the same as ones got from design1. Thank you in advance for your help. Best, Mike [[alternative HTML version deleted]]

hi Mike, On Sun, Jul 20, 2014 at 10:11 AM, Mike Miller <mike.bioc32 at="" gmail.com=""> wrote: > Dear All, > > I have problems in understanding what is the interpretation of default > output of interaction contrast and how can I change the default settings > (resultsNames(results)) and explore other interactions? > For example, here are the 3 factors I am interested in: > 1. treatment; levels: disease and control > 2. localization; levels: A and B. > 3. sex; levels: male and female > > If the design1 is: ~sex + treatment*localization, by default, the reported > contrast in the results is: > Wald test p-value: treatmentdisease.localizationA. > Q1: Can I interpret the output as a list of genes that are diff.expressed > (DE) between localization A and localization B in a disease? > Q2: How could I get the DE genes between localization A and localization B > in a control? Or DE genes between disease and control for localization A? > For the contrasts you are interested in performing, I would recommend setting up the analysis as follows (I am planning to include such an example in the vignette for the next release): # create a new variable which combines treatment and localization: dds$condition = factor(paste0(dds$treatment, ".", dds$localization)) design(dds) = ~ sex + condition dds = DESeq(dds) # then for example, DE genes between localization A # and localization B in a control res = results(dds, contrast=c("condition","control.B","control.A")) # or DE genes between disease and control for localization A res = results(dds, contrast=c("condition","disease.A","control.A")) Mike > If I change the order of factors in a design: > design2= ~sex + treatment*localization, then by default in the results I > get > Wald test p-value: localizationA.treatmentdisease. Can I interpret this as > a list of DE genes between disease and control in localization A? I tried > it, but the results were the same as ones got from design1. > > Thank you in advance for your help. > Best, > Mike > > [[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