Metadata-Version: 1.1
Name: RGT
Version: 0.12.0
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/0.12.0.zip
Description: RGT - Regulatory Genomics Toolbox
        =================================
        
        .. class:: no-web no-pdf
        
        |pypi| |dev_build| |coverage|
        
        RGT is an open source python 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
        ============
        
        The quickest and easiest way to get RGT is to to use pip. First some dependencies:
        
        ::
        
            pip install --user cython numpy scipy
        
        Then install the full RGT suite with all other dependencies:
        
        ::
        
            pip 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
            python 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
