Metadata-Version: 1.1
Name: xlmhg
Version: 2.2.12
Summary: XL-mHG: A Semiparametric Test for Enrichment
Home-page: https://github.com/flo-compbio/xlmhg
Author: Florian Wagner
Author-email: florian.wagner@duke.edu
License: GPLv3
Description: XL-mHG
        ======
        
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        **develop**  |codecov-develop| |travis-develop| |appveyor-develop|
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        This is an efficient Python/Cython implementation of the semiparametric
        `XL-mHG test`__ for enrichment in ranked lists. The XL-mHG test is an extension
        of the nonparametric `mHG test`__, which was developed by `Dr. Zohar
        Yakhini`__ and colleagues.
        
        __ xlmhg_paper_
        __ mhg_paper_
        __ zohar_
        
        If you use the XL-mHG test in your research, please cite `Eden et al. (PLoS
        Comput Biol, 2007)`__ and `Wagner (PLoS One, 2015)`__.
        
        __ mhg_paper_
        __ go_pca_paper_
        
        Installation
        ------------
        
        .. code-block:: bash
        
            $ pip install xlmhg
        
        Usage
        -----
        
        .. code-block:: python
        
            import xlmhg
            stat, cutoff, pval = xlmhg.xlmhg_test(v, X, L)
        
        Where: ``v`` is the ranked list of 0's and 1's, represented by a NumPy array of
        type \"np.uint8\", `X`` and ``L`` are parameters, and the return values have
        the following meanings:
        
        - ``stat``: The XL-mHG test statistic
        - ``cutoff``: The cutoff at which the XL-mHG test statistic was attained
        - ``pval``: The XL-mHG p-value
        
        What do the ``X`` and ``L`` parameters mean?
        --------------------------------------------
        
        - ``X`` refers to the minimum number of "1's" that have to be seen before
          anything can be called "enrichment".
        - ``L`` is the lowest cutoff (i.e., the largest ``n``) that is being tested
          for enrichment.
        
        A more direct way to understand ``X`` and ``L`` is through the definition of
        the XL-mHG test statistic. It is defined as the minimum hypergeometric p-value
        over all cutoffs at which at least ``X`` "1's" have already been seen, and
        excluding any cutoffs larger than ``L``. For `X=1` and `L=N`, the XL-mHG test
        reduces to the mHG test.
        
        Background
        ----------
        
        For a discussion of the statistical background and implementation of this test,
        please see the `Technical Report on arXiv <http://arxiv.org/abs/1507.07905>`_,
        as well as the `XL-mHG PeerJ Preprint article`__.
        
        __ xlmhg_paper_
        
        Copyright and License
        ---------------------
        
        Copyright (c) 2015, 2016 Florian Wagner
        
        ::
        
          XL-mHG is free software: you can redistribute it and/or modify
          it under the terms of the GNU General Public License, Version 3,
          as published by the Free Software Foundation.
          
          This program is distributed in the hope that it will be useful,
          but WITHOUT ANY WARRANTY; without even the implied warranty of
          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
          GNU General Public License for more details.
          
          You should have received a copy of the GNU General Public License
          along with this program. If not, see <http://www.gnu.org/licenses/>.
        
        
        .. _xlmhg_paper: https://doi.org/10.7287/peerj.preprints.1962v1
        
        .. _zohar: http://bioinfo.cs.technion.ac.il/people/zohar
        
        .. _mhg_paper: https://dx.doi.org/10.1371/journal.pcbi.0030039
        
        .. _go_pca_paper: https://dx.doi.org/10.1371/journal.pone.0143196
        
        .. |pypi| image:: https://img.shields.io/pypi/v/xlmhg.svg
            :target: https://pypi.python.org/pypi/xlmhg
            :alt: PyPI version
        
        .. |versions| image:: https://img.shields.io/pypi/pyversions/xlmhg.svg
            :target: https://pypi.python.org/pypi/xlmhg
            :alt: Python versions supported
        
        .. |license| image:: https://img.shields.io/pypi/l/xlmhg.svg
            :target: https://pypi.python.org/pypi/xlmhg
            :alt: License
        
        .. |travis-master| image:: https://travis-ci.org/flo-compbio/xlmhg.svg?branch=master
            :alt: Travis-CI build Status (master branch)
            :scale: 100%
            :target: https://travis-ci.org/flo-compbio/xlmhg.svg?branch=master
        
        .. |travis-develop| image:: https://travis-ci.org/flo-compbio/xlmhg.svg?branch=develop
            :alt: Travis-CI build Status (develop branch)
            :scale: 100%
            :target: https://travis-ci.org/flo-compbio/xlmhg.svg?branch=develop
        
        .. |appveyor-master| image:: https://ci.appveyor.com/api/projects/status/wpon7qkwpxx3fe6q/branch/master?svg=true
            :alt: Appveyor build Status (master branch)
            :scale: 100%
            :target: https://ci.appveyor.com/project/flo-compbio/xlmhg/branch/master
        
        .. |appveyor-develop| image:: https://ci.appveyor.com/api/projects/status/wpon7qkwpxx3fe6q/branch/develop?svg=true
            :alt: Appveyor build Status (develop branch)
            :scale: 100%
            :target: https://ci.appveyor.com/project/flo-compbio/xlmhg/branch/develop
        
        .. |codecov-master| image:: https://codecov.io/gh/flo-compbio/xlmhg/branch/master/graph/badge.svg
            :alt: Coverage (master branch)
            :target: https://codecov.io/gh/flo-compbio/xlmhg/branch/master
        
        .. |codecov-develop| image:: https://codecov.io/gh/flo-compbio/xlmhg/branch/develop/graph/badge.svg
            :alt: Coverage (develop branch)
            :target: https://codecov.io/gh/flo-compbio/xlmhg/branch/develop
        
Keywords: statistics nonparametric semiparametric enrichment test ranked lists
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Cython
