[BioC] DEseq for chip-seq data normalisation

Rory Stark Rory.Stark at cruk.cam.ac.uk
Tue Nov 5 19:18:34 CET 2013

Hi Guiseppe-

You can retrieve the complete matrix of read counts from DiffBind, either
normalized or not, using dba.peakset with bRetrieve=TRUE. To can set the
score to use via dba.count with peaks=NULL and score=DBA_SCORE_READS, or
any of the other possible score values. The default score is
DBA_SCORE_TMM_MINUS_FULL, which is normalized using edgeR's TMM method,
after subtracting the reads in the control, and using the full library
size (not just the reads in peaks) as a scalar.


On Mon, Nov 4, 2013 at 8:47 AM, Giuseppe Gallone <
giuseppe.gallone at dpag.ox.ac.uk> wrote:

>I would like to use DEseq or DEseq2 to normalise the peak signal for some
>Chip-seq data across 10 biological replicates.
>I started looking at the DEseq documentation - it seems the program
>requires a matrix arrangement of raw count data, where each row is a peak
>and each column is a replicate.
>What is the best way to obtain this? I have bam files for the reads,
>obtained with BWA, and bed files (or alternatively narrowPeak files) for
>the peak intervals, obtained using MACS.
>I gather it is possible to use a program called HTseq to compute these
>counts, however this program seems unable to deal with bed files, only
>gff files, and I'd prefer working directly with my beds if at all
>Thank you.
>Best regards
>Bioconductor mailing list
>Bioconductor at r-project.org
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