Metadata-Version: 2.0
Name: pyteomics
Version: 3.3
Summary: A framework for proteomics data analysis.
Home-page: http://hg.theorchromo.ru/pyteomics
Author: Anton Goloborodko & Lev Levitsky
Author-email: pyteomics@googlegroups.com
License: License :: OSI Approved :: Apache Software License
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Education
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries
Provides-Extra: DF
Requires-Dist: pandas; extra == 'DF'
Provides-Extra: FDR
Requires-Dist: numpy; extra == 'FDR'
Provides-Extra: Unimod
Requires-Dist: lxml; extra == 'Unimod'
Requires-Dist: sqlalchemy; extra == 'Unimod'
Provides-Extra: XML
Requires-Dist: lxml; extra == 'XML'
Requires-Dist: numpy; extra == 'XML'
Provides-Extra: graphics
Requires-Dist: matplotlib; extra == 'graphics'

What is Pyteomics?
------------------

Pyteomics is a collection of lightweight and handy tools for Python that help
to handle various sorts of proteomics data. Pyteomics provides a growing set of
modules to facilitate the most common tasks in proteomics data analysis, such as:

* calculation of basic physico-chemical properties of polypeptides:

  * mass and isotopic distribution
  * charge and pI
  * chromatographic retention time

* access to common proteomics data:

  * MS or LC-MS data
  * FASTA databases
  * search engines output

* easy manipulation of sequences of modified peptides and proteins

The goal of the Pyteomics project is to provide a versatile, reliable and
well-documented set of open tools for the wide proteomics community.
One of the project's key features is Python itself, an open source language
increasingly popular in scientific programming. The main
applications of the library are reproducible statistical data analysis and rapid
software prototyping.

Required Python versions
------------------------

Pyteomics supports Python 2.7 and Python 3. Python 2.6 and older are not
supported.

Project dependencies
--------------------

Pyteomics uses the following python packages:

 - `numpy <http://pypi.python.org/pypi/numpy>`_
 - `matplotlib <http://sourceforge.net/projects/matplotlib/files/matplotlib/>`_
   (used by **pyteomics.pylab_aux**)
 - `lxml <http://pypi.python.org/pypi/lxml>`_ (used by **pyteomics.mzml**,
   **pyteomics.pepxml**, **pyteomics.mzid**,
   **pyteomics.tandem**)
 - `pandas <http://pandas.pydata.org/>`_ (can be used with **pyteomics.pepxml**,
   **pyteomics.tandem**, **pyteomics.auxiliary**)
 - `sqlalchemy <http://www.sqlalchemy.org/>`_ (used by **pyteomics.mass.unimod**)

GNU/Linux
---------

The preferred way to obtain Pyteomics is via pip Python
package manager. The shell code for a freshly installed Ubuntu system::

    sudo apt-get install python-setuptools python-dev build-essential
    sudo easy_install pip
    sudo pip install lxml numpy matplotlib pyteomics

Arch-based distros
..................

On Arch Linux and related distros, you can install Pyteomics from AUR:

 - `python-pyteomics <https://aur.archlinux.org/packages/python-pyteomics/>`_
 - `python2-pyteomics <https://aur.archlinux.org/packages/python2-pyteomics/>`_


Windows
-------

- `Get pip <https://pip.pypa.io/en/stable/installing/>`_, if you don't have it yet.

- Install Pyteomics and its dependencies::

    pip install lxml numpy matplotlib pyteomics



