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README.md
analyze.R
clean.py
process.sh

README.md

README

This subdirectory contains the example scripts to accompany the manuscript. Read the section Version your code for the full explanation. The commands described below should be executed from within the subdirectory code.

process.sh

process.sh downloads the ENCODE CTCF ChIP-seq data from multiple types of kidney samples and calls peaks. The downloaded BAM files and MACS2 output are saved in tissue-specific subdirectories in ../data/. Run it as follows:

bash process.sh

You will need to have Python 2.7 installed because it is a prerequisite for the peak caller MACS2. To install MACS2, run:

pip install macs2

clean.py

clean.py filters peaks with a fold change cutoff and merges peaks from the different kidney samples. It creates the file ../data/sites-union.bed. Run it as follows:

python clean.py

It can be run with either Python2 or Python3. You will first need to install bedtools and pybedtools. See their documentation for instructions, but as an example, this can be accomplished on Ubuntu with the following:

apt-get install bedtools
pip install pybedtools

analyze.R

analyze.R creates diagnostic plots on the length of the peaks and their distribution across the genome. It creates the file ../data/sites-union.pdf. Run it as follows:

Rscript analyze.R