Hello R and edgeR users/developers, I had a question regarding the use of edgeR and graphing results. I'm trying to do some comparisons between including and excluding different features in edgeR. One variation I'm trying is the following: x <- read.delim("fileofcounts.txt",row.names="Symbol") group <- factor(c(1,1,2,2)) y <- DGEList(counts=x,group=group) et <- exactTest(y, dispersion = 0) I believe this setup assumes the dispersion in my data is Poisson, and calculates the gene-wise exactTest as so. I've also removed the calcNormFactors() function in this situation. So am I correct in suggesting the only normalization that would be occurring in this case is with respect to the library size? And my other question is how would I be able to make a qq-plot for this procedure (goodness of fit statistics as the y-axis and Chi- square quantiles as the x-axis)? The current gof() function appears to only be capable of using GLM data as an input. Does anyone know how to do the same with Poisson data that did not use the GLM functions? Furthermore, if I were to have included the tag-wise dispersion it would also be good to know how to make the same graph with a negative binomial distribution. So if anyone knows how to make that graph I would be interested too. Thanks -- output of sessionInfo(): R version 3.0.2 (2013-09-25) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods [7] base other attached packages: [1] LSD_2.5 ellipse_0.3-8 schoolmath_0.4 [4] colorRamps_2.3 RColorBrewer_1.0-5 gtools_3.2.1 [7] MASS_7.3-29 edgeR_3.4.2 limma_3.18.12 loaded via a namespace (and not attached): [1] tools_3.0.2 -- Sent via the guest posting facility at bioconductor.org.