Re: Interspecies differential expression of orthologs with Edger
Gordon K Smyth <[email protected]> Tue, 9 Sep 2014 09:47:29 +1000 (AUS Eastern Standard Time)
| Newsgroups | gmane.science.biology.informatics.conductor |
|---|---|
| Message-ID | <[email protected]> |
Dear Assaf, Please type library(edgeR) ?roast.DGEList to see the roast gene set test that Steve was referring to. It tests whether a set of genes is differentially expressed as a group. Gordon On Mon, 8 Sep 2014, assaf www wrote: > Hi Steve > > I will look into limma::voom (was not aware of this approach). > > Do you mean GO enrichment (e.g., David/Go-seq/etc), is so then no, its not > what I mean. > > I specifically would like to ask if Edger (or similar tools) could give > reasonable DE estimation by comparing the sum of counts of groups of genes > (instead single genes). > This is a completely different thing - it may possibly allow working-around > the issue of paralogy-orthology when performing cross-species DE analysis, > and may have multiple other advantages I believe (regardless of > cross-species things). > (Of course, in case it doesn't violate the basic assumptions of these DE > analyzes, and can keep the data properly normalized - this is my question) > > thanks a lots for the suggestions, i will look into, > Assaf > > On Mon, Sep 8, 2014 at 6:33 PM, Steve Lianoglou <lianoglou.steve-RuTDbSqP/[email protected]> > wrote: > >> Hi, >> >> On Mon, Sep 8, 2014 at 1:17 AM, assaf www <[email protected]> wrote: >>> Hi sean >>> >>> I guess I'm not clear, sorry. >>> >>> I mean that in principle it is possible to aggregate genes based on their >>> membership in gene families (or any other criteria), and to compare the >> sum >>> of read counts per sample per groups of genes (usually it would be counts >>> per sample per genes). What I would be interested to learn is if such >>> comparison can be done in Edger. >>> >>> About FDR : In the above case, after grouping there are less multiple >>> comparisons, and lower FDR. >> Instead of grouping different genes into one "count feature," it's >> sounds like keeping genes separate, but doing a gene set enrichment >> analysis might be more like what you are looking for? >> >> edgeR and limma::voom have these out of the box -- look at the camera >> and roast functions for further info on that. >> >> HTH, >> -steve >> >> -- >> Steve Lianoglou >> Computational Biologist >> Genentech >> > ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}} _______________________________________________ Bioconductor mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor