Metadata-Version: 1.2
Name: RGT
Version: 0.13.2
Summary: Toolkit to perform regulatory genomics data analysis
Home-page: http://www.regulatory-genomics.org
Author: Eduardo G. Gusmao, Manuel Allhoff, Joseph Chao-Chung Kuo, Fabio Ticconi, Ivan G. Costa
Author-email: software@costalab.org
License: GPL
Download-URL: https://github.com/CostaLab/reg-gen/archive/0.13.2.zip
Description: RGT - Regulatory Genomics Toolbox
        =================================
        
        .. class:: no-web no-pdf
        
        |pypi| |dev_build| |coverage|
        
        RGT is an open source Python 3.6+ library for analysis of regulatory
        genomics. RGT is programmed in an oriented object fashion and its core
        classes provide functionality for handling regulatory genomics data.
        
        The toolbox is made of a `core library <http://www.regulatory-genomics.org/rgt/>`__ and several tools:
        
        * `THOR <http://www.regulatory-genomics.org/thor-2/>`__: ChIP-Seq differential peak caller, replaces
          `ODIN <http://www.regulatory-genomics.org/odin-2/>`__
        
        * `Motif Analysis <http://www.regulatory-genomics.org/motif-analysis/>`__: TBFS match and enrichment
        
        * `HINT <http://www.regulatory-genomics.org/hint/>`__: DNase-Seq footprinting method
        
        * `RGT-Viz <http://www.regulatory-genomics.org/rgt-viz/>`__: Visualization tool
        
        * `TDF <http://www.regulatory-genomics.org/tdf/>`__: DNA/RNA triplex domain finder
        
        Installation
        ============
        
        **Python 2 is no longer supported.**
        
        The quickest and easiest way to get RGT is to to use pip. First some dependencies:
        
        ::
        
            pip3 install --user cython numpy scipy
        
        Then install the full RGT suite with all other dependencies:
        
        ::
        
            pip3 install --user RGT
        
        
        Alternatively (but not recommended), you can clone this repository:
        
        ::
        
            git clone https://github.com/CostaLab/reg-gen.git
        
        or download a specific
        `release <https://github.com/CostaLab/reg-gen/releases>`__, then proceed
        to manual installation:
        
        ::
        
            cd reg-gen
            python3 setup.py install --user
        
        Detailed installation instructions and basic problem solving can be
        found `on our website <http://www.regulatory-genomics.org/rgt/download-installation>`__.
        
        For any issues, please write to our `support mailing list <https://groups.google.com/forum/#!forum/rgtusers>`__.
        
        .. |pypi| image:: https://img.shields.io/pypi/v/rgt.svg?label=latest%20release
            :target: https://pypi.python.org/pypi/rgt
            :alt: Latest version released on PyPi
        
        .. |mast_build| image:: https://img.shields.io/travis/CostaLab/reg-gen.svg?branch=master&label=master
            :target: https://travis-ci.org/CostaLab/reg-gen
            :alt: Build status of the master branch
        
        .. |dev_build| image:: https://img.shields.io/travis/CostaLab/reg-gen.svg?branch=develop&label=develop
            :target: https://travis-ci.org/CostaLab/reg-gen
            :alt: Build status of the develop branch
        
        .. |coverage| image:: https://img.shields.io/coveralls/CostaLab/reg-gen/develop.svg?label=coverage
            :target: https://coveralls.io/r/CostaLab/reg-gen?branch=develop
            :alt: Test coverage
        
Keywords: ChIP-seq,DNase-seq,Peak Calling,Motif Discovery,Motif Enrichment,HMM
Platform: linux
Platform: linux2
Platform: darwin
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.6
