Hi João, Robert and everyone,
First, thank you for your responses.
It was easy to predict that the question about discarding duplicates would get
responses faster as it is the one that you can address quickly and accurately
with common sense.
Briefly, I fully agree, we need to remove the PCR bias whenever possible. I was
actually wondering about the false negative error introduced by this filter.
Now that I think about it a little better, the benefit of the the decrease in
false positives must comfortably outweigh the increase of false negative unless
the ChIP peaks are very sharp. Good.
Question one still remains:
I read in the data with ShortRead. Now, how do I filter it and export it to a
fomat that will allow me to follow along the example workflow? Class matters,
doesn't it?
> load("alignedLocs.rda")
> ls()
[1] "alignedLocs"
> class(alignedLocs)
[1] "AlignedList"
attr(,"package")
[1] "chipseq"
Thank you,
Ivan
----- Original Message ----
From: João Fadista <[email protected]>
To: [email protected]; [email protected]
Sent: Thursday, 19 March, 2009 10:31:24
Subject: RE: [Bioc-sig-seq] Reducing Solexa's export.txt in preparation for
aChIP-seq analysis.
Hi,
Removing duplicates is a step that you can do in order to minimize the possible
bias due to the amplification in sample preparation.
Best,
João
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of
[email protected]
Sent: Thursday, March 19, 2009 3:24 PM
To: [email protected]
Subject: [Bioc-sig-seq] Reducing Solexa's export.txt in preparation for
aChIP-seq analysis.
Hello,
In preparation to analyse my own ChIP-seq data, I am trying to follow the steps
described in this sample workflow:
http://www.bioconductor.org/workshops/2008/SeattleNov08/ChIP-seq/workflow.pdf
The document starts by loading data that has been "reduced to a set of
alignment start positions (including orientation)".
Can somebody elaborate on that a little bit or, ideally, show it with one
example?
Also, as part of the reduction, the procedure "removed all duplicate reads and
applied a quality score cutoff". The score cutoff is fine but how is removing
duplicates justified?
Thank you,
Ivan
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