Tim Triche, Jr.
tim.triche at gmail.com
Tue Nov 19 01:45:27 CET 2013
Doesn't tileGenome or whatever it's called help with the binning? It's not too hard to bolt multiple tracks into a SummarizedExperiment at that point.
> On Nov 18, 2013, at 4:33 PM, Kasper Daniel Hansen <kasperdanielhansen at gmail.com> wrote:
> (Michael Love and I had some discussion on this Friday)
> I also think it would be a very convenient class/method. A lot of data
> these days are naturally represented (and are available from say GEO) as
> bigWig files (essentially coverage tracks), for example ChIP-seq. This
> would be much more efficient than converting BAM to coverage on the fly.
> It seems to me that bigWig ought to be efficient for this, but I am not
> very familiar with its performance. What we want is really to be able to
> chunk multiple coverage profiles over the genome, and do computations on
> each of the chunks. Any idea on efficiency? I am happy to contribute a
> bit, at least with design.
> On Mon, Nov 18, 2013 at 6:11 PM, Michael Lawrence <lawrence.michael at gene.com
>> Aggregating coverage over multiple samples is a popular request recently.
>> I'm happy to support this effort, but I thinks someone in Seattle is going
>> to have to take the lead on it.
>> On Mon, Nov 18, 2013 at 2:36 PM, Michael Love
>> <michaelisaiahlove at gmail.com>wrote:
>>> a discussion came up on devel last year about looking at a genomic range
>>> over multiple samples and multiple experiments (
>>> stepping aside the multiple experiment part, I'm interested in
>>> BigWigViews() with fixed ranges across samples. Has there been any more
>>> thoughts in this direction?
>>> BigWigViews would be incredibly useful for genomics applications where we
>>> want to scan along the genome looking at lots of samples. BigWig offers a
>>> concise representation of the information compared to BAM files.
>>> What I am trying now is using import(BigWigFile, which=gr) on files one
>>> one, and then binding the coverage together.
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