hi Gilgi,


On Mon, Dec 23, 2013 at 10:15 AM, Gilgi Friedlander <
gilgi.friedlander@weizmann.ac.il> wrote:

>  Hi Mike,
>
>
>
> Thanks a lot.
>
>
>
> I tried doing so, and I am getting an error. I tried to find what the
> problem is without success. Sorry if it is something trivial I am missing.
>
>
>
> I have 2 duplicates for each sample
>
> Here is what I did:
>
> design = data.frame(row.names=colnames( countsTable ),condition =
> sampleTable$condition,type=sampleTable$type)
>
>
>
> > design
>
>            condition  type
>
> mut_Tot       mut total
>
> mut_Tot       mut total
>
> mut_poly      mut  poly
>
> mut_poly      mut  poly
>
> wt_Tot           wt total
>
> wt_Tot           wt total
>
> wt_poly          wt  poly
>
> wt_poly          wt  poly
>
>
>
>
>
>
>
> cds <- newCountDataSet( countsTable, design )
>
> cds <- estimateSizeFactors( cds )
>
> estimateDispersions( cds )
>


​it looks like this line above is the problem. You should have:

cds <- estimateDispersions(cds)

best,

Mike​




>
>
> fit1 = fitNbinomGLMs( cds, count ~ type + condition + type:condition  )
>
> Error in fitNbinomGLMs(cds, count ~ type + condition + type:condition) :
>
>   Call 'estimateDispersions' with 'method="pooled"' (or 'blind') first.
>
>
>
> I have duplicates, so why am I getting that error?
>
>
>
> Thanks a lot,
>
> Gilgi
>
>
>
> *From:* Michael Love [mailto:michaelisaiahlove@gmail.com]
> *Sent:* Monday, December 23, 2013 4:36 PM
> *To:* Gilgi [guest]
> *Cc:* bioconductor@r-project.org; Gilgi Friedlander; DESeq Maintainer
> *Subject:* Re: [BioC] DESeq / DESeq2 for translation efficiency in
> polysome profiling or ribsome profiling experiments
>
>
>
> hi Gilgi,
>
>
>
> Yes if you are interested in whether treatment affects the ratio of one
> assay to another you can investigate this using an interaction term, so:
>
>
>
> design(dds) <- ~ assay + treatment + assay:treatment
>
>
>
> Then you can either use a likelihood ratio test (reduced formula = ~ assay
> + treatment), or a Wald test on the interaction term.
>
>
>
> This was recently included as a recommendation in the vignette of the
> devel branch (v1.3), but Wolfgang has a slide on this from a recent Bioc
> talk, testing if the ratio of CLIP-Seq to RNA-Seq is affected by treatment.
>
>
>
> slide 25 here:
> http://bioconductor.org/help/course-materials/2013/EMBOBGI/131119-bgi-huber-de.pdf
>
>
>
> best,
>
>
>
> Mike
>
>
>
> On Mon, Dec 23, 2013 at 2:37 AM, Gilgi [guest] <guest@bioconductor.org>
> wrote:
>
>
> Hello,
> I wanted to ask whether it is possible to use DESeq for the analysis of
> translation efficiency in polysome profiling or ribsome profiling.
> In polysome profiling - polysomes are isolated (e.g. by sucrose
> gradients), and mRNA that were associated with the polysomes are then
> isolated and sequenced.
> In ribosome profiling, mRNA fragments that are protected by the ribosome
> are sequenced.
> When such experiments are conducted in parallel to total RNA-seq, one can
> ask questions regarding the translation efficiency.
> For example: if we have 4 samples: ribosome sequencing (without
> treatment), total sequencing (without treatment), sequencing (with
> treatment), total sequencing (with treatment), one can ask how does the
> treatment affects the protein synthesis rate (which is the ratio
> ribosome/total).
> I wanted to ask whether it is possible to define such a model in DESeq for
> such analysis, in order to answer how is this ratio affected by the
> treatment.
> Thanks a lot
>
>
>  -- output of sessionInfo():
>
> none
>
> --
> 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]]

