Hi Ryan, Thanks so much for the reply and link provided. I was looking to find the same genes which are DE in sample A vs sample B comparison as well as sample A vs sample C comparison so the latter option with two pairwise comparisons and taking the intersection will work for me. Best wishes, Maria W dniu czwartek, 10 kwietnia 2014 Ryan C. Thompson <rct@thompsonclan.org> napisa³(a): > Are you looking for genes that have any difference at all between any of the three populations, or are you looking specifically for genes that are different in *both* the A vs B and A vs C comparisons? For the former case, you can pass multiple coefficients or contrasts to the testing functions (glmLRT or glmQLFTest) to perform an ANOVA-like test. For the latter, you should probably adapt the approach recommended by Grodon Smyth in a recent thread on this list[1]. Specifically, perform each test separately and take the intersection of significant genes. > > -Ryan > > [1] https://stat.ethz.ch/pipermail/bioconductor/2014-April/058822.html > > On 04/10/2014 07:31 AM, Maria [guest] wrote: >> >> Hi all, >> I have read the entire edgeR user guide and some posts on here but I still do not understand if it possible to make non-pairwise contrasts in edgeR (or is it even an oxymoron)in the GLM mode. The only non-simple contrasts I could find are of the form (taken from the user guide): >> DrugvsPlacebo.2h = (Drug.2h-Drug.0h)-(Placebo.2h-Placebo.0h) >> but I have different setup. >> >> I have 3 different populations and I would like to see find genes that are significantly different between population A and B, and A and C simultaneously. >> Of course, I could make pairwise comparisons and look for intercept in DEG, but I am not sure it is the proper way? >> >> Regards, >> Maria >> >> -- output of sessionInfo(): >> >> R version 3.0.1 (2013-05-16) >> Platform: x86_64-w64-mingw32/x64 (64-bit) >> >> locale: >> [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 >> [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C >> [5] LC_TIME=English_United States.1252 >> >> attached base packages: >> [1] splines parallel stats graphics grDevices utils datasets methods base >> >> other attached packages: >> [1] edgeR_3.2.4 limma_3.16.8 DESeq2_1.0.19 RcppArmadillo_0.4.200.0 >> [5] Rcpp_0.11.1 GenomicRanges_1.12.5 IRanges_1.18.4 pasilla_0.2.16 >> [9] DESeq_1.12.1 lattice_0.20-29 locfit_1.5-9.1 DEXSeq_1.6.0 >> [13] Biobase_2.20.1 BiocGenerics_0.6.0 BiocInstaller_1.10.4 >> >> loaded via a namespace (and not attached): >> [1] annotate_1.38.0 AnnotationDbi_1.22.6 biomaRt_2.16.0 Biostrings_2.28.0 bitops_1.0-6 >> [6] DBI_0.2-7 genefilter_1.42.0 geneplotter_1.38.0 grid_3.0.1 hwriter_1.3 >> [11] RColorBrewer_1.0-5 RCurl_1.95-4.1 Rsamtools_1.12.4 RSQLite_0.11.4 statmod_1.4.18 >> [16] stats4_3.0.1 stringr_0.6.2 survival_2.37-7 tools_3.0.1 XML_3.98-1.1 >> [21] xtable_1.7-3 zlibbioc_1.6.0 >> >> -- >> Sent via the guest posting facility at bioconductor.org. >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > > [[alternative HTML version deleted]]