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DiffBind question: How to extract read counts?

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k.panov • 0

@kpanov-15226

Last seen 6.0 years ago

Hi Rory,

I wonder, if it is possible to extract counting data (after performing dba.count) from a resulting DBA object in csv format where consensus peak names are in the first column, peak positions are in the second/third/forth colums (chromosome, start, end) and normalized number of reads for each sample are in subsequent columns.

Regards

Konstantin

diffbind read counts extract data • 2.3k views

ADD COMMENT • link updated 6.0 years ago by Rory Stark ★ 5.2k • written 6.0 years ago by k.panov • 0

score 0 · Answer 1 · 2018-04-12

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Rory Stark ★ 5.2k

@rory-stark-5741

Last seen 14 days ago

Cambridge, UK

I'm not sure what you mean by consensus peak names? The peak intervals are specified only by their positions, the closest they have t oa name is a number (1:numpeaks).

Here's one way of getting the columns you want in a csv (with the peak number as the peak name):

> normCounts <- dba.peakset(myDBA, bRetrieve=TRUE, DataType=DBA_DATA_FRAME)
> write.csv(normCounts, file="normalized_counts.csv")

ADD COMMENT • link 6.0 years ago Rory Stark ★ 5.2k

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Thank you very much Rory, that what I need . Regarding peak names, I just was not sure if any peak names (e.g. Peak 1, Peak 2 and so for) were given in addition to coordinates.

Regards

Konstantin

ADD REPLY • link 6.0 years ago k.panov • 0

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Hi Rory,

Just to clarify, the counts extracted by dba.peakset function, aren't normalized to the library size, aren't they?

Regards

Konstantin

ADD REPLY • link 6.0 years ago k.panov • 0

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The values to be returned are controlled by the score parameter passed to dba.count(). The default values are TMM normalized, which takes library size into account. (You can tell they're normalized because they are not integers).

You can change the score without having to re-count the reads by calling dba.count() with peaks=NULL and score=DBA_SCORE_READS (or any of the other scores detailed on the dba.count() man page).

ADD REPLY • link 6.0 years ago Rory Stark ★ 5.2k