[BioC] DESeq on CCAT identified chipseq peaks

Rory Stark Rory.Stark at cruk.cam.ac.uk
Fri May 16 17:50:13 CEST 2014


The current released version of DiffBind is 1.10, Bioconductor is at 2.14,
and it all requires the most recent release of R, 3.1.0 (Spring Dance).

-Rory

On 16/05/2014 16:34, "QAMRA Aditi (GIS)" <qamraa99 at gis.a-star.edu.sg>
wrote:

>Thank you so much for explaining all of it so well.
>I read an answer you just gave about using the summits option in
>dba.counts - What version of diffbind is that ? I am using version 1.8.5
>in Rversion 3.0.2 and I can't use the summits option.
>
>Aditi
>
>-----Original Message-----
>From: Rory Stark [mailto:Rory.Stark at cruk.cam.ac.uk]
>Sent: Friday, May 16, 2014 10:17 PM
>To: QAMRA Aditi (GIS)
>Cc: bioconductor at r-project.org
>Subject: Re: [BioC] DESeq on CCAT identified chipseq peaks
>
>Hello Aditi-
>
>What you want is to use a "matched" design. There is a good explanation
>of this design (in a differential expression context) in the edgeR
>vignette.
>Basically, the matched tumour-normal pairs are going to have certain
>similarities to each other as they each come from the same patient. A
>matched design will model this to detect consistent differences in
>enrichment between tumor and normal that is independent of individual
>patients.
>
>You can analyze a matched design by setting up the contrast with
>block=DBA_REPLICATE:
>
>> h3k4me3_counts = dba.contrast(h3k4me3_counts,
>>categories=DBA_CONDITION,
>>block=DBA_REPLICATE)
>> h3k4me3_counts = dba.analyze(h3k4me3_counts, method=DBA_DESEQ2)
>
>You'll see that two analyses are run (unmatched and matched):
>
>> h3k4me3_counts
>
>Is is useful to look at the MA plot:
>
>> dba.plotMA(h3k4me3_counts, method=DBA_DESEQ2_BLOCK)
>
>You can get the list of all the sites with statistics relating to how
>confidently they can be identified as being differentially enriched:
>
>> matchedReport = dba.report(h3k4me3_counts, method=DBA_DESEQ2_BLOCK,
>> th=1)
>
>Cheers-
>Rory
>
>
>On 16/05/2014 06:54, "QAMRA Aditi (GIS)" <qamraa99 at gis.a-star.edu.sg>
>wrote:
>
>>Hi Dr. Rory,
>>
>>I understand now. Thank you !
>>
>>A last question (hopefully) - Can you explain a little more on how the
>>use of a blocking factor works in the case of matched normal tumor
>>pairs ? Does it mean that using the DBA_REPLICATE condition as a
>>blocking factor in such a case adjusts (?) and removes any sort of
>>batch effects between replicates ?
>>
>>Thanks !
>>Aditi
>>________________________________________
>
>
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