Metadata-Version: 1.1
Name: pyaffy
Version: 0.3.2
Summary: pyAffy: Processing raw data from Affymetrix expression microarrays in Python.
Home-page: https://github.com/flo-compbio/pyaffy
Author: Florian Wagner
Author-email: florian.wagner@duke.edu
License: GPLv3
Description: ..
            Copyright (c) 2016 Florian Wagner
            
            This file is part of pyAffy.
            
            pyAffy 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/>.
        
        pyAffy
        ======
        
        .. "|docs-latest| |docs-develop|
        
        pyAffy is a Python/Cython implementation of the RMA algorithm for
        processing raw data from Affymetrix expression microarrays. For a detailed
        discussion of this implementation, see the `pyAffy PeerJ preprint`__. For
        a list of changes, see the `changelog <changelog.rst>`_.
        
        __ peerj_preprint_
        
        .. _peerj_preprint: https://peerj.com/preprints/1790/
        
        Installation
        ------------
        
        Option 1: Using `pip`
        ~~~~~~~~~~~~~~~~~~~~~
        
        .. code-block:: bash
        
            $ pip install pyaffy
        
        
        Option 2: Cloning the GitHub repository
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        .. code-block:: bash
        
            $ git clone https://github.com/flo-compbio/pyaffy.git
            $ cd pyaffy
            $ pip install -e .
        
        Usage
        -----
        
        The `rma` function expects two parameters: A custom CDF file (from the
        `Brainarray web site`__) and an ordered dictionary (`collections.OrderedDict`)
        with sample names as keys and corresponding CEL files as values.
        
        __ brainarray_
        
        The `rma` function returns a list of genes, a list of samples, and an
        expression matrix (of type `numpy.ndarray`), in that order.
        
        .. code-block:: python
        
            from pyaffy import rma
            # for documentation of the rma function, try:
            # help(rma)
            genes, samples, X = rma(cdf_file, sample_cel_files)
        
        A small `example with real code`__ is available in the `pyaffy-demos` repository.
        
        __ real_example_
        
        .. _brainarray: http://brainarray.mbni.med.umich.edu/Brainarray/Database/CustomCDF/genomic_curated_CDF.asp
        .. _real_example: https://github.com/flo-compbio/pyaffy-demos/tree/master/minimal
        
        Copyright and License
        ---------------------
        
        Copyright (c) 2016 Florian Wagner
        
        ::
        
          pyAffy 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/>.
        
Keywords: affymetrix microarray rma expression normalization
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
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
