Metadata-Version: 2.1
Name: MAGINE
Version: 0.0.10
Summary: Package to analyze biological data.
Home-page: https://github.com/LoLab-VU/Magine
Author: James Pino
Author-email: james.ch.pino@gmail.com
License: UNKNOWN
Keywords: biological networks,biological pathways,enrichment analysis,network analysis,visualization,multi-omics,rnaseq,proteomics,metabolomics
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Science/Research
Description-Content-Type: text/x-rst
Requires-Dist: scipy
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: statsmodels
Requires-Dist: jinja2
Requires-Dist: requests
Requires-Dist: sortedcontainers
Requires-Dist: defusedxml
Requires-Dist: xlrd
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: matplotlib-venn
Requires-Dist: plotly (==2.7)
Requires-Dist: wordcloud
Requires-Dist: bioservices
Requires-Dist: pathos
Requires-Dist: jupyter
Requires-Dist: ipywidgets
Requires-Dist: py2cytoscape
Requires-Dist: pydot
Requires-Dist: pydotplus
Requires-Dist: networkx (>=2.1)
Provides-Extra: test
Requires-Dist: coverage ; extra == 'test'

=================================================================
MAGINE : Mechanism of Action Generator involving Network Analysis
=================================================================

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.. image:: https://readthedocs.org/projects/magine/badge/?version=latest
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MAGINE is a framework for the analysis of quantitative multi-omics data.
It was designed to handle multi-sample (time points) and multi-omics
(rnaseq, label-free proteomics, etc). Users are provided access to tools driven
around their experimental data. Provides access to enrichment analysis, biological
network construction and various visualization methods.


Documentation
=============

The manual is available online at http://magine.readthedocs.io.

.. _Anaconda: https://www.anaconda.com/distribution/#download-section

Installation
============

1. Install Anaconda

   Our recommended approach is to use Anaconda_, which is a
   distribution of Python containing most of the numeric and scientific
   software needed to get started. If you are a Mac or Linux user, have
   used Python before and are comfortable using ``pip`` to install
   software, you may want to skip this step and use your existing Python
   installation.

   Anaconda has a simple graphical installer which can be downloaded
   from https://www.anaconda.com/distribution/#download-section - select
   your operating system and download the **Python 3.7 version**. The
   default installer options are usually appropriate.

2. Open a terminal

   We will install most packages with conda::

      $ conda create -n magine_env python=3.7
      $ conda activate magine_env
      $ conda config --add channels conda-forge
      $ conda install jinja2 statsmodels networkx graphviz
      $ conda install -c marufr python-igraph

   **Windows users:** Please download and install igraph and pycairo
   using the wheel files provided by Christoph Gohlke, found at
   https://www.lfd.uci.edu/~gohlke/ . Download and install via pip.

3. Install MAGINE

   The installation is very straightforward with ``pip`` - type the following in a terminal::

      $ pip install magine

4. Start Python and MAGINE

   From the terminal or command prompt type ::

      $ jupyter notebook

   You will then be at the Python prompt. Type ``import magine`` to try
   loading magine. If no error messages appear and the next Python
   prompt appears, you have succeeded in installing magine!





