Metadata-Version: 2.1
Name: hichub
Version: 0.0.3
Summary: Comprehensive Network Analysis for HiC
Home-page: https://github.com/lux563624348/HiC_Hubs
Author: Xiang Li
Author-email: lux@gwu.edu
License: UNKNOWN
Project-URL: Bug Reports, https://github.com/lux563624348/HiC_Hubs
Project-URL: Funding, https://github.com/lux563624348/HiC_Hubs
Project-URL: Say Thanks!, https://github.com/lux563624348/HiC_Hubs
Project-URL: Source, https://github.com/lux563624348/HiC_Hubs
Description: # NOTE: This software is under development.
        Latest updated on Jan/14/2021, 
        
        # Comprehensive Network Analysis for HiC
        
        [![PyPI download](image/pypi.PNG)](https://pypi.org/project/hichub/)
        
        
        <br><br>
        <img src="image/Hub_Myb.PNG" width="800">
        <br><br>
        
        
        - [Overview](#overview)
        - [Documentation](#documentation)
        - [System Requirements](#system-requirements)
        - [Installation Guide](#installation-guide)
        - [Example of Running (Demo)](#Example_Running)
        - [License](#license)
        
        ## Overview
        HicHub is a Python package containing tools 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.
        
        ## Documentation
        The official documentation with usage is under development.
        
        ## 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
        ```
        
        ## Installation Guide
        Recommend to use bioconda for installing.
        ```
        python3 -m pip install hichub --user
        python3 -m pip install numpy optparse 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
        
        ```
        #chr	bin1	bin2	Cond1	Cond2
        10	3000000	3010000	100	200
        ```
        
        EXAMPLE: 
        ```
        python igraph_hub.py -i chr10_WT_na-DKO_na.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 of Hubs:
        ```
        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](LICENSE.md) file for details
        
        ## Acknowledgments
Keywords: HiC,graph,Hub
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Education
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Requires-Python: >=3.6, <4
Description-Content-Type: text/markdown
