Pan-ChIP-seq Analysis of Protein Colocalization Using Peak Sets
The current version of PanChIP supports the hg38 genome assembly.
Python 3, BEDTools
pip3 install panchip
PanChIP Analysis: a directory with only 6-column BED files
PanChIP Filter: a 6-column BED file
We recommend most PanChIP users to utilize BED files with constant non-zero fifth column values (e.g., 1, 500, 1000).
Commands:
init Initialization of the PanChIP library
analysis Analysis of a list peak sets
filter Filtering library for quality control
Run panchip <command> -h for help on a specific command.
PanChIP: Pan-ChIP-seq Analysis of Peak Sets
positional arguments:
command Subcommand to run
optional arguments:
-h, --help show this help message and exit
--version show program's version number and exit
Initialization of the PanChIP library
positional arguments:
library_directory Directory wherein PanChIP library will be stored. > 13.6
GB of storage required.
optional arguments:
-h, --help show this help message and exit
Analysis of a list peak sets
positional arguments:
library_directory Directory wherein PanChIP library was stored.
input_directory Input directory wherein peak sets in the format of .bed
files are located.
(.bed6 format with numeric scores in 5th column required)
output_directory Output directory wherein output files will be stored.
optional arguments:
-h, --help show this help message and exit
-t THREADS Number of threads to use. (default: 1)
-r REPEATS Number of repeats to perform. (default: 1)
Filtering library for quality control
positional arguments:
library_directory Directory wherein PanChIP library was stored.
input_file Path to the input .bed file.
(.bed6 format with numeric scores in 5th column required)
output_directory Output directory wherein output files will be stored.
optional arguments:
-h, --help show this help message and exit
-t THREADS Number of threads to use. (default: 1)
Please cite the original PanChIP paper for works that utilized the PanChIP software.
- Sanidas I, Lee H, Rumde PH, Boulay G, Morris R, Golczer G, Stanzione M, Hajizadeh S, Zhong J, Ryan MB, Corcoran RB, Drapkin BJ, Rivera MN, Dyson NJ, and Lawrence MS. Chromatin-bound RB targets promoters, enhancers, and CTCF-bound loci, and is redistributed by cell cycle progression. Molecular Cell 82.18 (2022).
The development of PanChIP was possible thanks to many groundbreaking works of fellow researchers. We highly recommend users to cite the Cistrome Data Browser as well.
- Zheng R, Wan C, Mei S, Qin Q, Wu Q, Sun H, Chen C-H, Brown M, Zhang X, Meyer CA, and Liu XS. Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis. Nucleic Acids Research 47.D1, D729–D735 (2019).
While the design of PanChIP is different from that of BART, we suggest users to also try out the BART software. PanChIP measures the overlap between peak sets, while BART assesses the predictability of profiles based on the library.
- Wang Z, Civelek M, Miller CL, Sheffield NC, Guertin MJ, and Zang C. BART: a transcription factor prediction tool with query gene sets or epigenomic profiles. Bioinformatics 34.16, 2867–2869 (2018).