Hi Alexander,

Thanks for your rapid response!

DEXSeq is designed to test for differences in exon usage, not differential
> expression.


I guess I should clarify--I have already used edgeR to look for overall
differential expression but was also wanting to see if I could pin down
functional components where the DE is occurring, i.e. which exon(s).

Anyway, in both DESeq and DEXSeq you can assign normalization factors using:
>
> sizeFactors(yourobject) <- your normalization factors
>
> or why dont you use the normalization factors from DESeq/DEXSeq?


Thanks a bunch! I should have read the sizeFactors documentation more
carefully. The reason I really wanted to be able to supply my own
normalization factors is because we have some large sample-specific GC
effects on expression that most normalization techniques will be unable to
take into account. Using conditional quantile normalization (cqn from
bioconductor) has shown a large improvement in our count distributions.

Also, there are no issues with a single core. I was just hoping to
parallelize the process since it takes several hours with our dataset to
run.

Thanks again,

Alicia

On Tue, Oct 9, 2012 at 1:37 AM, Alejandro Reyes <alejandro.reyes@embl.de>wrote:

> Dear Alicia,
>
> Thanks for your input!
>
>
>  Hi all,
>>
>> I am interested in using DEXSeq to look for differential expression
>> across seven conditions, each with ~7 biological replicates. I have created
>> an ExonCountSet object and am trying to estimate the dispersions from my
>> model. I have two questions: 1) Is it possible to supply an offset term to
>> the glm? This would be very helpful when trying to incorporate
>> normalization info, since the count data is restricted to integers. I
>> noticed that the glmnb.fit object called by DEXSeq contains a mf$offset
>> variable. Additionally, 2) Has anyone seen and/or corrected the following
>> error when trying to use multiple cores to estimate dispersions?
>>
>
> DEXSeq is designed to test for differences in exon usage, not differential
> expression.  To test for differential expression you can use other packages
> like DESeq or edgeR. Anyway, in both DESeq and DEXSeq you can assign
> normalization factors using:
>
> sizeFactors(yourobject) <- your normalization factors
>
> or why dont you use the normalization factors from DESeq/DEXSeq?
>
>
>  ecs <- estimateDispersions(ecs, nCores=3)
>> Estimating Cox-Reid exon dispersion estimates using 3 cores. (Progress
>> report: one dot per 100 genes)
>> The process has forked and you cannot use this CoreFoundation
>> functionality safely. You MUST exec().
>> Break on __THE_PROCESS_HAS_FORKED_AND_**YOU_CANNOT_USE_THIS_**
>> COREFOUNDATION_FUNCTIONALITY__**_YOU_MUST_EXEC__() to debug.
>> This message repeats several times and also contains the following:
>> Tcl_ServiceModeHook: Notifier not initialized.
>>
>
> If you are testing for differential exon usage, do you get the error
> message using only a single core? I believe that it is a problem with your
> multicore + apple... some "googling" took me to this:
>
> https://stat.ethz.ch/**pipermail/r-sig-mac/2009-**August/006426.html<https://stat.ethz.ch/pipermail/r-sig-mac/2009-August/006426.html>
>
> Best wishes,
> Alejandro
>
>
>  Thanks a bunch for any potential insight!
>>
>>   -- output of sessionInfo():
>>
>>  sessionInfo()
>>>
>> R version 2.15.1 (2012-06-22)
>> Platform: x86_64-apple-darwin12.0.0 (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] splines   stats     graphics  grDevices utils     datasets  methods
>> [8] base
>>
>> other attached packages:
>>   [1] DEXSeq_1.2.1          Biobase_2.16.0        BiocGenerics_0.2.0
>>   [4] RColorBrewer_1.0-5    scales_0.2.2          cqn_1.2.0
>>   [7] quantreg_4.91         SparseM_0.96          preprocessCore_1.18.0
>> [10] nor1mix_1.1-3         mclust_4.0            plyr_1.7.1
>> [13] multicore_0.1-7
>>
>> loaded via a namespace (and not attached):
>>   [1] biomaRt_2.12.0   colorspace_1.1-1 dichromat_1.2-4  hwriter_1.3
>>   [5] labeling_0.1     munsell_0.4      RCurl_1.95-0     statmod_1.4.16
>>   [9] stringr_0.6.1    tcltk_2.15.1     tools_2.15.1     XML_3.95-0
>>
>> --
>> Sent via the guest posting facility at bioconductor.org.
>>
>>
>

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