Identifying high resolution reference points using ChIP-exo ================

The pipeline proposed here can be used to find high resolution reference coordinates.The pipeline also gives the following: 1) Genomic regions containing over represented combination of factors. 2) Over-represented motifs in these enriched regions. 3) Assessment of each candidate reference as a potential organizing center. 4) Distance of reference features from each other.

• Python 2.7 or higher.
• Python modules: pysam, pybedtools, numpy, scipt, matplotlib.

• A directory containing peak calls in gff format for all the factors.
• A directory containing indexed BAM files for the same factors.
• Both peak filenames and BAM filenames should start with factorname followed by "_".

To run the pipeline type the following:

$ python Run_pipeline.py -h

$ example usages:
$ python Run_pipeline.py [OPTIONS]
$ **** Remember that your BAM file and your peak file should start with "factorname_"

Options:

-h, --help show this help message and exit -p PEAKDIR The directory containing the peaks call files in gff format. [REQUIRED] -i BAMDIR The directory containing the BAM files. [REQUIRED] -w WINDOW Window size, default = 20 [OPTIONAL] -g GFILE File containing the chromosome number and length. -s GSIZE Mappable genome size: sg11 = 11,332,237 (default), hg19=248,988,565, mm9=2,178,433,024 for read length = 36. Refer PMID:22276185 [OPTIONAL] -v PVAL P-value cutoff for significant enrichment over background, default = 0.05 [OPTIONAL] -l ILEN Length of chromHMM segmentation interval, default = 200 [OPTIONAL] -n STATE Number of states, default = 12 [REQUIRED] -r FASTA Reference FASTA file. [REQUIRED] -t TSS File containing TSS coordinates. [REQUIRED] -u UP Upstream distance from candidate reference point, default = 500 [OPTIONAL] -d DOWN Downstream distance from candidate reference point, default = 500 [OPTIONAL]

The output of the pipeline contains:

• ChromHMM defined states enriched with combination of factors.
• High resolution reference points for each state.
• Assessment of each reference point to define the regulatory architecture.
• Plots around the reference points.