Metadata-Version: 1.1
Name: phyde
Version: 0.3.3
Summary: Hybridization detection using phylogenetic invariants
Home-page: https://github.com/pblischak/HyDe
Author: Paul Blischak & Laura Kubatko
Author-email: blischak.4@osu.edu
License: GPLv3
Description: 
        |Build Status| |Documentation|  |PyPI Badge|
        
        HyDe: hybridization detection using phylogenetic invariants
        -----------------------------------------------------------
        
        **HyDe Preprint:**
        
        Blischak, P. D., J. Chifman, A. D. Wolfe, and L. S. Kubatko. 2017.
        HyDe: a Python package for genome-scale hybridization detection.
        bioRxiv doi: `10.1101/188037 <https://doi.org/10.1101/188037>`__.
        
        `Read the Docs <http://hybridization-detection.rtfd.io/>`__
        -----------------------------------------------------------
        
        HyDe is a software package that detects hybridization in phylogenomic
        data sets using phylogenetic invariants. The primary interface for HyDe is a Python
        module called ``phyde`` (**P**\ ythonic **Hy**\ bridization **De**\ tection).
        ``phyde`` provides a suite of tools for performing hypothesis tests on triples of taxa
        to detect hybridization. It also has built in functions to wrap calls to the pure C++ version
        of HyDe, ``hyde_cpp``. We have provided a ``Makefile`` that
        will compile the ``hyde_cpp`` C++ executable and will then install the
        ``phyde`` Python package using the ``setup.py`` file. To ensure that the necessary
        dependencies are available, we suggest using a Python distribution such
        as `Miniconda <https://conda.io/miniconda.html>`__.
        
        To facilitate analyses using the Python module, three scripts are provided to
        conduct hybridization detection analyses directly from the command line:
        
        - ``run_hyde.py``: runs a standard hybridization detection analysis on all triples
          in all directions. Results are also filtered based on whether there is significant
          evidence for hybridization.
        - ``individual_hyde.py``: tests each individual within a putative hybrid population
          using a list of specified triples specified.
        - ``bootstrap_hyde.py``: conducts bootstrap resampling of the individuals within
          the putative hybrid lineages for each specified triple.
        
        These last two scripts need to be given a three column table of triples
        (P1, Hybrid, P2) that you wish to test:
        
        .. code::
        
          sp1 sp2 sp3
          sp1 sp3 sp4
          sp3 sp4 sp5
          .
          .
          .
        
        You can also use a results file from a previous analysis as a triples file.
        For example, you can use the filtered results from the ``run_hyde.py`` script so that
        you only run analyses on triples that have significant levels of hybridization.
        If you only have a few hypotheses that you want to test, then you can also pass
        a triples file to ``run_hyde.py`` and it will only test those hypotheses rather than
        testing everything.
        
        Multithreaded versions of these scripts are also available (``run_hyde_mp.py``,
        ``individual_hyde_mp.py``, and ``bootstrap_hyde_mp.py``).
        Make sure you have the ``multiprocess`` module installed before you use them:
        ``pip install multiprocess``.
        
        Getting help
        ------------
        
        If you have questions about running HyDe, please feel free to use the
        **gitter chatroom** to get help:
        
        |Gitter|
        
        If you have a problem while running HyDe and you think it may be a bug,
        please consider filing an issue:
        
        |HyDe Issues|
        
        Installation
        ------------
        
        Requirements:
        ~~~~~~~~~~~~~
        
        -  Python 2.7
        -  Python Modules:
        
           -  Cython
           -  Numpy
           -  Scipy
           -  Pandas
           -  Matplotlib
           -  Seaborn
        
        -  C++ compiler (g++ >= v4.8)
        
        .. code:: bash
        
            # To install dependencies
            pip install cython numpy scipy pandas matplotlib seaborn
        
            # Clone HyDe repository from GitHub
            git clone https://github.com/pblischak/HyDe.git
            cd HyDe
        
            # Compile hyde_cpp using `make`
            make
        
            # Now install phyde module
            python setup.py install
        
            # Test the installation
            make test
        
        The ``phyde`` module is also hosted on the Python Package Index (PyPI), and can be installed directly using
        ``pip``.
        
        .. code:: bash
        
          # Install from PyPI with pip
          pip install phyde
        
        Documentation for analyzing data using HyDe can be found `here <http://hybridization-detection.readthedocs.io/en/latest/analyze.html>`_.
        
        .. |Build Status| image:: https://travis-ci.org/pblischak/HyDe.svg?branch=master
           :target: https://travis-ci.org/pblischak/HyDe
        
        .. |Documentation| image:: https://readthedocs.org/projects/hybridization-detection/badge/?version=latest
           :target: http://hybridization-detection.readthedocs.io/en/latest/?badge=latest
        
        .. |PyPI Badge| image:: https://badge.fury.io/py/phyde.svg
           :target: https://pypi.python.org/pypi/phyde
        
        .. |Gitter| image:: https://badges.gitter.im/Join%20Chat.svg
           :target: https://gitter.im/pblischak-HyDe/Lobby
        
        .. |HyDe Issues| image:: https://img.shields.io/badge/HyDe-Issues-blue.svg
           :target: https://github.com/pblischak/HyDe/issues
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Cython
Classifier: Programming Language :: C++
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
