[BioC] edgeR/DESeq for ChIP-seq analysis

[Cittaro Davide]

On Nov 8, 2012, at 9:29 AM, sheng zhao <harryzs1981 at gmail.com> wrote:
> 
> Is it the case for histone modifications ChIP-seq (H3K4me1, H3K4me2 or
> H3k9me3)?
> 

AFAIK the NB model stands also for those.

d

> Regards,
> Sheng
> 
> 
> On Thu, Nov 8, 2012 at 8:59 AM, Cittaro Davide <cittaro.davide at hsr.it>wrote:
> 
>> Dear Mark
>> 
>> On Nov 8, 2012, at 8:53 AM, Mark Robinson <mark.robinson at imls.uzh.ch>
>> wrote:
>> 
>>> Dear Davide,
>>> 
>>> Indeed, edgeR and DESeq can be (and have been) used in this mode.  We
>> published something recently on this:
>>> 
>>> http://www.ncbi.nlm.nih.gov/pubmed/22879430
>>> http://imlspenticton.uzh.ch/robinson_lab/ABCD-DNA/ABCD-DNA.pdf
>>> 
>> 
>> I've missed that :-( Thanks for the paper
>> 
>>> You can apply that approach regardless of copy number being a factor ...
>> basically, we counted tiled bins of the genome, but yes, you could focus in
>> on regions of interest.  The function abcdDNA() is really just a wrapper
>> for the edgeR GLM.  As usual, "normalization" can be delicate, depending on
>> the type of data.
>>> 
>>> Also note that the DiffBind package already does something similar, but
>> has a lot more machinery to collect and organize the sets of enriched
>> regions.
>> 
>> I wonder why I've never used DiffBind before :-)
>> 
>>> 
>>> Hope that helps.
>> 
>> It does, thanks!
>> 
>> d
>> 
>>> 
>>> Best, Mark
>>> 
>>> 
>>> On 08.11.2012, at 08:37, Cittaro Davide wrote:
>>> 
>>>> Hi there, I'm writing to the list to have your comment about the
>> possibility of using edgeR or DESeq for the analysis of ChIP-seq samples.
>>>> Standard approaches to ChIP-seq analysis (relying on external software
>> such as MACS) do not make analysis of replicates easy. I've seen people
>> looking for peaks and then compare the common/differential intervals
>> between replicates in case/control design. I wonder if a more general
>> approach may work (and I'm going to test this anyway...).
>>>> Since the negative binomial model stands for ChIP-seq analysis, both
>> edgeR and DESeq should work well. One can use external software to identify
>> regions and compute the union of all regions as it was a "gene list". From
>> that point on, the pipeline should not differ from standard gene expression
>> analysis.
>>>> What do you think?
>>>> 
>>>> d
>>>> /*
>>>> Davide Cittaro, PhD
>>>> 
>>>> Coordinator of Bioinformatics Core
>>>> Center for Translational Genomics and Bioinformatics
>>>> Ospedale San Raffaele
>>>> Via Olgettina 58
>>>> 20132 Milano
>>>> Italy
>>>> 
>>>> Office: +39 02 26439140
>>>> Mail: cittaro.davide at hsr.it
>>>> Skype: daweonline
>>>> */
>>>> 
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>>> 
>>> ----------
>>> Prof. Dr. Mark Robinson
>>> Bioinformatics
>>> Institute of Molecular Life Sciences
>>> University of Zurich
>>> Winterthurerstrasse 190
>>> 8057 Zurich
>>> Switzerland
>>> 
>>> v: +41 44 635 4848
>>> f: +41 44 635 6898
>>> e: mark.robinson at imls.uzh.ch
>>> o: Y11-J-16
>>> w: http://tiny.cc/mrobin
>>> 
>>> ----------
>>> http://www.fgcz.ch/Bioconductor2012
>>> 
>>> 
>> 
>> /*
>> Davide Cittaro, PhD
>> 
>> Coordinator of Bioinformatics Core
>> Center for Translational Genomics and Bioinformatics
>> Ospedale San Raffaele
>> Via Olgettina 58
>> 20132 Milano
>> Italy
>> 
>> Office: +39 02 26439140
>> Mail: cittaro.davide at hsr.it
>> Skype: daweonline
>> */
>> 
>> _______________________________________________
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>> 
> 
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/*
Davide Cittaro, PhD

Coordinator of Bioinformatics Core
Center for Translational Genomics and Bioinformatics
Ospedale San Raffaele
Via Olgettina 58
20132 Milano
Italy

Office: +39 02 26439140
Mail: cittaro.davide at hsr.it
Skype: daweonline
*/