Hi Kasper,
You are correct, this sounds like a perfect Genominator use case.
However, while working on my package, I realized that you can achieve
the same with straight out of the box IRanges and Rsamtools/ShortRead
functions, without having to format the data back and forth. This was
important for me as I use many IRanges functionalities in my
downstream analyses.
Cheers,
Nico
---------------------------------------------------------------
Nicolas Delhomme
High Throughput Functional Genomics Center
European Molecular Biology Laboratory
Tel: +49 6221 387 8310
Email: [email protected]
Meyerhofstrasse 1 - Postfach 10.2209
69102 Heidelberg, Germany
---------------------------------------------------------------
On 15 Apr 2010, at 17:43, Kasper Daniel Hansen wrote:
If you are mainly interested in counting, you should check out
Genominator which has been capable of doing this for a large number of
samples for a long time. It should be fairly easy to use, with the
biggest huddle usually being reading in the data at first.
Kasper
On Thu, Apr 15, 2010 at 11:23 AM, Nicolas Delhomme
<[email protected]> wrote:
Hi Kunbin,
I'm currently developing an R package that does something close to
what you
describe. Maybe we can discuss more in details what you need, off
list, to
see if I can help you out? If it turns out to be the case, then
we'll post
back the result to the list.
Cheers,
---------------------------------------------------------------
Nicolas Delhomme
High Throughput Functional Genomics Center
European Molecular Biology Laboratory
Tel: +49 6221 387 8310
Email: [email protected]
Meyerhofstrasse 1 - Postfach 10.2209
69102 Heidelberg, Germany
---------------------------------------------------------------
On 3 Apr 2010, at 05:48, Kunbin Qu wrote:
Hi,
I have run RNA-seq on 4 human samples, and I'd like to look at the
count
number from each sample at regions where any of the sample has
some read
coverage (say, threshold of 5 reads). What is the best way to do
this? It is
basically to examine the differentially expression regions across
the
transcriptome, not just limited to known annotated regions. I
having been
trying to use IRanges and related packages, but things start to
get hairy
when come to cluster the reads, condense them (within certain bp
range),
back-track the identities. I also looked at Cufflink, but it does
not seem
to be for this purpose, isn't it? Any advice is highly appreciated.
-Kunbin
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