Architecture of the human regulatory network derived from

Q:

Re: Architecture of the human regulatory network derived from ENCODE data
10.1038/nature11245

Hi Dr. Gerstein: This is a very nice paper and is very important in my
current study. Do you have tools/software for TF Co-association (figure 1
and supplemental section B and C) mentioned in this paper. Can I get it?

A:
Anshul did the co-association analysis for this Networks paper. I
think he knows that part the best.

As for the co-association analysis in the ENCODE main paper, it can
be repeated using the GSC package available at the ENCODE statistics web
site (http://www.encodestatistics.org/). The first thing you need to do
is to determine (manually or by other means) a segmentation of the
genome, where TF binding is assumed segment-wise stationary. If you have
no specific preference on how the segmentation should be done, you can
use the GSC Python segmentation tool to do that, which will try to
perform an automatic segmentation (the results of which would be better
if you have more data). Then you can run the GSC Python program to
perform segmented block sampling to compute pairwise p-vlaues of your
binding data.

ENCODE data
MIME-Version: 1.0
Content-Type: text/plain; charset="utf-8"
Content-Transfer-Encoding: 7bit

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