Latest updated on Feb/14/2021,
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.
This package requires only a standard computer with enough RAM to support the in-memory operations.
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
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
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
Please read (https:xx) for details on our code of conduct, and the process for submitting pull requests to us.
- *Xiang Li Initial work
#This project is licensed under the MIT License - see the LICENSE.md file for details