[BioC] edgeR/DESeq for ChIP-seq analysis

[Mark Robinson]

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

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.

Hope that helps.

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
> */
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

----------
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