[BioC] DEXSeq update results change

António domingues amjdomingues at gmail.com
Fri Aug 15 16:25:24 CEST 2014

Dear Alejandro,

I just wanted to follow up on this to say that I also see quite a big 
difference between the "new" and old "DEXseq". Not only are the numbers 
of differentially expressed exons much larger in the new version (in one 
experiment they nearly quadrupled), the direction of change is now 
shifted. That is, when upon knock-down there was about 50% more exon 
exclusion then inclusion, now is the other way around. It does not 
happen in all my knockdowns (and I have seven of them) but it is 
sufficient to me wary of previous conclusions based on the old version. 
As before, DEXSeq was run with the default options. Perhaps my 
experimental design is not the best to make a conclusion on how much 
different the results are between the 2 versions of DEXSeq (only 2 
biological replicates per condition), but other users should bare in 
mind that some changes in results might happen.

Regarding my experimental design, I am building the DEXSeqDataSet object 
with only 2 conditions (4 samples)  to do the pairwise comparisons. 
Since I have a control and 7 conditions, is it possible, similarly to 
DESeq2, to build the object, estimate the dispersion, and do the 
comparisons with all the samples  and then only extract the results of 
the comparisons of interest? And if so, does it offer an statistical 
advantage? My gut feeling says yes but it says many wrong things all 
time :) (I am attaching a dispersion plot from on comparison for DEXSeq 
1.10, sessionInfo is at the bottom of the email)

On a matter of packages changes, and I put this question to discussion 
on the list, where should the threshold be for a change in a package to 
warrant also a change in name? Changes in function wrappers, bug 
corrections are all fine, but when the results stop being reproducible 
(and not due to bug fixing), should it be time to think about it? We 
have seen it happening with DESeq which after major changes became 
DESeq2. This is not a dig at you, just genuine curiosity, and concern as 


> Dear Marco Marconi,
> I think that was the version where we changed from our original method,
> the one described on the paper to the recent apporach, you fill find
> this details in the section "Methodological changes since publication of
> the paper".  As you might have noticed, the dispersions are very
> correlated as well as the p-values.
> I don't think the change in the p-value, and therefore the p-adjusted
> value, since it is not changing dramatically.  The simplest thing would
> be to increase your FDR threshold a bit.
> Best regards,
> Alejandro
> >/  Hello, After performing a general Bioconductor update to the new version, I
> />/  noticed that now the DEXseq package 1.8.0 is giving me different results
> />/  from prrevious version 1.6.0. As a start, its function print dots "..." on
> />/  the stdout which was not done in the previous version. This is not a big
> />/  issue, the problem is that now I am obtaining different results. Generally,
> />/  the padjust values are bigger.
> />/
> />/  For example this exon:
> />/
> />/                       a1       a2      a3       b1      b2       b3
> />/  EXXXX        126     90      101     81      233     225
> />/
> />/  gets different results:
> />/
> />/  geneID,exonID,dispersion,pvalue,padjust,meanBase,log2fold(b/a)
> />/
> />/  old version:
> />/  EXXXX,0.0684906370633231,0.00256847378387803,0.0321347815544768,129.941383199307,-0.217272839643456
> />/
> />/  new version:
> />/  EXXXX,0.0928452378435829,0.00401881761350959,0.0587521235795571,129.941383199307,-0.213275654796358
> />/
> />/
> />/  as you can see the old one has a padjust below 0.05 and the other above
> />/  0.05, which is a big problem.
> />/
> />/
> />/  I had a look in the NEWS section of the DEXSeq package, but i couldn't find
> />/  any information about major changes.
> />/
> />/
> />/  thank you very much, regards,
> />

R version 3.1.1 (2014-07-10)
Platform: x86_64-pc-linux-gnu (64-bit)

  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C LC_TIME=en_US.UTF-8        
  [6] LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8 

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets methods   

other attached packages:
  [1] ggplot2_1.0.0           plyr_1.8.1 DEXSeq_1.10.8           
BiocParallel_0.6.1 DESeq2_1.4.5            RcppArmadillo_0.4.320.0
  [7] Rcpp_0.11.2             GenomicRanges_1.16.2 
GenomeInfoDb_1.0.2      IRanges_1.21.43 Biobase_2.24.0          

loaded via a namespace (and not attached):
  [1] annotate_1.42.1      AnnotationDbi_1.26.0 BatchJobs_1.3        
BBmisc_1.7           biomaRt_2.20.0 Biostrings_2.32.0
  [7] bitops_1.0-6         brew_1.0-6 checkmate_1.2        
codetools_0.2-8      colorspace_1.2-4 DBI_0.2-7
[13] digest_0.6.4         fail_1.2 foreach_1.4.2        
genefilter_1.46.1    geneplotter_1.42.0 grid_3.1.1
[19] gtable_0.1.2         hwriter_1.3 iterators_1.0.7      
lattice_0.20-29      locfit_1.5-9.1 MASS_7.3-33
[25] munsell_0.4.2        proto_0.3-10 RColorBrewer_1.0-5   
RCurl_1.95-4.1       reshape2_1.4 Rsamtools_1.16.0
[31] RSQLite_0.11.4       scales_0.2.4 sendmailR_1.1-2      
splines_3.1.1        statmod_1.4.20 stats4_3.1.1
[37] stringr_0.6.2        survival_2.37-7 tools_3.1.1          
XML_3.98-1.1         xtable_1.7-3 XVector_0.4.0
[43] zlibbioc_1.10.0

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

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