Hi, I am using EdgeR to find DE genes in an experiment with two factors (Tissue (2 levels) and Treatment (3 levels). Currently the design matrix output by model.matrix() looks like this: Int Tissue Treat1 Treat2 Treat3 S1 1 0 0 0 1 S2 1 0 0 0 1 S3 1 0 0 1 0 S4 1 0 0 1 0 S5 1 0 1 0 0 S6 1 0 1 0 0 S7 1 1 0 0 1 S8 1 1 0 0 1 S9 1 1 0 1 0 S10 1 1 0 1 0 S11 1 1 1 0 0 S12 1 1 1 0 0 attr(,"assign") [1] 0 1 2 2 2 attr(,"contrasts") attr(,"contrasts")$Tissue [1] "contr.treatment" attr(,"contrasts")$Treat [1] "contr.treatment" and the model is a comparison of this design and the model without the last column. I would like to specify a design matrix where a) I drop each of the Treat levels (in separate runs of EdgeR) to find the DE lists corresponding to each level of the Treatment and to b) specify a model where level1 of the Treatment is the reference against which the other levels are compared. I am stuck on how to specify the alternate design matrix and how to pass this to the model.matrix() command (or even if I have to do this). I am aware this is a general R command and have read the manual page and the manual pages for the contrasts() function. My inability to make logical sense of these is no doubt testament to my lack of R expertise and some help would be appreciated. In reading the limma documentation it indicates that a reference can be specified by the option ref=" ". Would this also work for me e.g. model.matrix(targets, ref="Treat1")? For specifying the alternate contrasts would this also be achieved in a similar way to that shown in the limma manual by setting up a contrasts matrix e.g. contrast.matrix <- makeContrasts(Treat2,levels=design) to achieve also the contrast of Treat2 (still using Treat1 as a reference)? My next question is then the obvious, how is this then used in the testing. Do I specify it in the glmFit() or using the glmLRT() function on the original output from the glmFit but specifying the contrasts matrix as the option? e.g glm1 <- glmFit(DGEList.object, design, dispersion = common.dispersion) # fits the model lrt1 <- glmLRT(DGEList.object, glm1) ## fits the original design contrast lrt2 <- glmLRT(DGEList.object, glm1, contrast.matrix) ## fits the second contrast or, am I way off track...... looking forward to being set straight. Josquin ========================================= Dr Josquin Tibbits Senior Research Scientist Victorian AgriBiosciences Centre La Trobe University R&D Park 1 Park Drive Bundoora VIC 3083 Phone: +61 3 9032 7055 Email: Josquin.Tibbits@dpi.vic.gov.au Notice: This email and any attachments may contain information t...{{dropped:14}}