Re: DEXSeq update results change
António Miguel de Jesus Domingues <[email protected]>
| Newsgroups | gmane.science.biology.informatics.conductor |
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| Message-ID | <CAPaCvoC3or_H=zWHO1ept=0tRhZY34+8FSWpaG6aTaAxiGqB2Q@mail.gmail.com> |
Hi Alejandro, thanks again for looking into this. > I had a look at your data, apparently the difference in dispersion > estimates between the old and the new versions of DEXSeq can make a > difference in the coefficients of the GLM, therefore the exon fold > changes. But this changes seem to be specifically affecting only those > exons with very low counts. This is very re-assuring and makes sense. The new version is teh way to go then :) Best regards, António > For example, with the objects that you send me: > > select <- rowSums( dxr$countData ) > 10 > plot( dxr_new$`log2fold_3_c_GFP_c`[select], dxr_old$`log2fold.3_c_c.GFP_c_c.`[select] > ) > > These numbers/plots give a much more reasonable picture. These differences > are from those exons where noise is predominant. I will dig more into this, > but I would not worry so much about it, the signs for the significant exons > are anyway consistent: > > select2 <- which(dxr_old$padjust < 0.1) > table( dxr_new$`log2fold_3_c_GFP_c`[select2] > 0 , > dxr_old$`log2fold.3_c_c.GFP_c_c.`[select2] > 0) > > FALSE TRUE > FALSE 1630 0 > TRUE 0 614 > > Best regards, > Alejandro > > > > > Dear Wolfgang and Alejandro, >> >> First of all, thank you for looking into this. >> >> can you send one ore more specific examples, i.e. >> - the count table for the affected gene(s), for all its exons, >> and/or the plotDEXSeq output >> - the size factorss >> >> >> I have prepared a data set+script for testing that will follow in a >> separate private email, so that you can look into this in detail. While >> preparing it I think I spotted where the difference in results might >> originate *(1)*. >> >> >> Let me clarify that my concern is not with a particular exon, but rather >> with the general trend (ratio of up-regulated / down-regulated exons) that >> is changed, particularly in the experimental set-up I am sending you. >> >> That also leads to the second point - with only two replicates per >> condition, expectations about reproducibility of the result should >> be modest. No amount of statistical software can undo that. >> >> >> I am well aware of that :) In defence of data, I should say that the >> experimental validation of the DGE results (for this same data) was nearly >> 100%. So yes, few replicates can be an issue, but we have some experimental >> validation to give us assurance that not all is bad. >> >> @ Alejandro >> >> Just an additional question, do you see the shift in fold changes >> for all your exons or only for a subset of them? >> In older versions there was a bug that was causing some label >> swaps in the result columns, but this should be fixed in the most >> recent versions (I just want to make sure it is fixed!). As >> Wolfgang mentions, this would become evident by looking at the >> plotDEXSeq output (by looking at the normalized counts and exon >> usage). >> >> >> >> The scatter plot of fold change of new vs old version is a bit funky I >> must say: >> https://www.dropbox.com/s/l3snr4epgwbkty8/foldchange_comparison.png >> >> >> *(1) * >> >> while playing with the example data to send you, I noticed what could be >> an explanation while counting significantly changed exons: >> >> https://www.dropbox.com/s/7zc4n352ftjzqqe/nHits_comparison.pdf >> >> In the old version of DEXseq without a fold-change cut-off, there are >> more exons with decreased inclusion than with increased inclusion >> (~2500/1500 exons). With increasingly higher fold-change cut-offs this is >> inverted. For instance with fc 10% is 2000/1500, and with fc of 50% is >> 80/400. So a completely different trend. Using the new DEXSeq version, >> changing the FC cut-off makes no difference: the trend is always more exons >> with increased inclusion, which is sort of what I would expect. >> >> Could it be that the old version is less efficient in estimating the >> fold-changes when the differences are minor. Well, not estimating >> fold-changes but rather the dispersions. That would explain the differences >> I observed. And we only have 2 replicates so we cannot expect miracles from >> DEXSeq. >> >> Best regards, >> António >> >> >> On 16 August 2014 12:24, Wolfgang Huber <[email protected] <mailto: >> [email protected]>> wrote: >> >> Dear Antonio >> >> can you send one ore more specific examples, i.e. >> - the count table for the affected gene(s), for all its exons, >> and/or the plotDEXSeq output >> - the size factorss >> >> This should help all of us understand better, and perhaps fix, >> what you’re unhappy about. >> What DEXSeq does is not a black box, it is in fact very simple, so >> we should be able to get to the bottom of this. >> >> Regarding the question in the second paragraph: if you have reason >> to assume that the biological variability is the same in all your >> conditions (knockdowns), then the joint dispersion estimation will >> be more precise. But it is not biologically implausible that the >> assumption may be wrong (e.g. because of the different efficiency >> of RNAi), leading to underestimating of the true biological >> variability (and there over-calling of results) in some conditions. >> >> That also leads to the second point - with only two replicates per >> condition, expectations about reproducibility of the result should >> be modest. No amount of statistical software can undo that. >> >> Best wishes >> Wolfgang >> >> >> >> -- >> -- >> António Miguel de Jesus Domingues, PhD >> Postdoctoral researcher >> Deep Sequencing Group - SFB655 >> Biotechnology Center (Biotec) >> Technische Universität Dresden >> Fetscherstraße 105 >> 01307 Dresden >> >> Phone:+49 (351) 458 82362 <tel:%2B49%20%28351%29%20458%2082362> >> Email: antonio.domingues(at)biotec.tu-dresden.de < >> http://biotec.tu-dresden.de> >> >> -- >> The Unbearable Lightness of Molecular Biology >> > > -- -- António Miguel de Jesus Domingues, PhD Postdoctoral researcher Deep Sequencing Group - SFB655 Biotechnology Center (Biotec) Technische Universität Dresden Fetscherstraße 105 01307 Dresden Phone: +49 (351) 458 82362 Email: antonio.domingues(at)biotec.tu-dresden.de -- The Unbearable Lightness of Molecular Biology [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor