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NOTE: For Paper Review, please follow the instruction below:

Latest updated on Feb/14/2021,

Comprehensive Network Analysis for HiC





Overview

This module is a Python package containing tool for network analysis of HiC data. It starts from HiC Interaction pairs, then generating network and clustering. Finally ranking all clusters by their interaction change.

System Requirements

Hardware Requirements

This package requires only a standard computer with enough RAM to support the in-memory operations.

Software Requirements

HicHub mainly depends on the Python scientific stack.

python <=3.3
pandas
numpy
pybedtools
python-igraph
scipy

If you want to convert .hic to input file faster, please install strawC. Detail: https://github.com/aidenlab/straw

Installation Guide

Recommend to use bioconda for installing. Create the environment from the environment_hichub.yml(Can be found in this repository) file:

conda env create -f environment_hichub.yml
python3 -m pip install hichub --user
python3 -m pip install numpy pandas pybedtools python-igraph scipy
https://bioconda.github.io/user/install.html

Or

Example of Running (Demo)

Input Format: HiC Interaction in txt format. Example of test data can be found in ~/test_data %% Convert .hic to required input format python3 convert_hic_to_pair.py -i ~/ -n NONE -f test.hic -r 10000

#chr	bin1	bin2	Cond1	Cond2
10	3000000	3010000	100	200

EXAMPLE:

%% Find hub by shrinked algorithm
callhub.py -i chr10_test.bed -f WT_na -b DKO_na -r 10000 -d 0.5
or (if callhub.py was not found in your path, please download this git and ./bin/callhub.py )
python3 ./bin/callhub.py -i chr10_test.bed -f WT_na -b DKO_na -r 10000 -d 0.5

Options:

  -h, --help            show this help message and exit
  -i <file>, --in=<file>
                        Path to Input HiC file in txt format
  -f <str>, --foreground_name=<str>
                        Name of condition as foreground.
  -b <str>, --background_name=<str>
                        Name of condition as background.
  -r <int>, --resolution=<int>
                        Resolution of HiC txt
  -d <float>, --filtered_density=<float>
                        Density cutoff for hub shriking.

Output can be found at working directory: (Demo output is: /HiC_Hubs/python_package/tests/2704_DKO_na_Diff_hub.txt or 3106_WT_na_Diff_hub.txt)

3106_WT_na_Diff_hub.txt
0	1	2	hub_name	Num_vertices	pvalue
chr10	20930000	21060000	chr10:20930000-21060000	11	7.88966007260005e-09
chr10	19590000	19720000	chr10:19590000-19720000	11	7.809766623341443e-05
chr10	80210000	80340000	chr10:80210000-80340000	11	9.520611432439225e-05
chr10	95890000	96030000	chr10:95890000-96030000	14	0.00015075762147303865

Built With

Contributing

Please read (https:xx) for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

Authors

  • *Xiang Li Initial work

License

#This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments