Metadata-Version: 1.1
Name: RGT
Version: 0.9.5
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/0.9.5.zip
Description: RGT - Regulatory Genomics Toolbox
        =================================
        
        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.
        
        This library has been used for implementation of several tools as
        ChIP-Seq differential peak callers
        (`ODIN <http://www.regulatory-genomics.org/odin-2/>`__ and
        `THOR <http://www.regulatory-genomics.org/thor-2/>`__), DNase-Seq
        footprinting method
        (`HINT <http://www.regulatory-genomics.org/hint/>`__) and the
        visualization tool
        `RGT-Viz <http://www.regulatory-genomics.org/rgt-viz/>`__.
        
        Quick installation
        ==================
        
        The quickest and easiest way to get RGT is to to use pip:
        
        ::
        
            pip install RGT
        
        This will install the full RGT suite with all dependencies.
        
        Alternatively, 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
            sudo python setup.py install
        
        Detailed installation instructions and basic problem solving can be
        found at:
        
        http://www.regulatory-genomics.org/rgt/download-installation
        nn
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
