Metadata-Version: 2.1
Name: domaincaller
Version: 0.1.0
Summary: A python implementation of original DI-based domain caller proposed by Dixon et al. (2012)
Home-page: https://github.com/XiaoTaoWang/domaincaller/
Author: XiaoTao Wang
Author-email: wangxiaotao686@gmail.com
License: UNKNOWN
Description: Introduction
        ============
        Domaincaller is an implementation of the original Directionality Index (DI) based
        TAD caller proposed by Dixon et al. [1]_ Instead of original separate scripts for
        each stage of the caller, this module provides a convenient command line interface
        integrating the whole pipeline, including calculating the DI track, performing HMM
        and post-processing. It supports the `.cool <https://github.com/mirnylab/cooler>`_
        matrix format, so has low memory requirements when dealing with high resolution data.
        
        Installation
        ============
        First install dependencies using `conda <https://conda.io/miniconda.html>`_::
        
            conda config --add channels defaults
            conda config --add channels bioconda
            conda config --add channels conda-forge
            conda create -n domaincaller python=3.7.1 cooler=0.8.6 numpy=1.17.2 scipy=1.3.1 pomegranate=0.10.0 networkx=1.11
            conda activate nholoop
        
        Then install the domaincaller using pip::
        
            pip install domaincaller-0.1.0-py3-none-any.whl
        
        Usage
        =====
        Check the command-line help by ``domaincaller [-h]``.
        
        
        Citation
        ========
        .. [1] Dixon JR, Selvaraj S, Yue F, Kim A, Li Y, Shen Y, Hu M, Liu JS, Ren B. Topological domains
           in mammalian genomes identified by analysis of chromatin interactions. Nature, 2012,
           doi: 10.1038/nature11082
Keywords: TAD Hi-C cooler DI
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: POSIX
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/x-rst
