Metadata-Version: 2.1
Name: pyteomics
Version: 4.5.2
Summary: A framework for proteomics data analysis.
Home-page: http://pyteomics.readthedocs.io
Author: Anton Goloborodko & Lev Levitsky
Author-email: pyteomics@googlegroups.com
License: License :: OSI Approved :: Apache Software License
Project-URL: Documentation, http://pyteomics.readthedocs.io
Project-URL: Source Code, https://github.com/levitsky/pyteomics
Project-URL: Issue Tracker, https://github.com/levitsky/pyteomics/issues
Project-URL: Mailing List, https://groups.google.com/group/pyteomics
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: XML
Provides-Extra: TDA
Provides-Extra: graphics
Provides-Extra: DF
Provides-Extra: Unimod
Provides-Extra: numpress
Provides-Extra: mzMLb
Provides-Extra: proforma
Provides-Extra: all
License-File: LICENSE
License-File: NOTICE
License-File: AUTHORS

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    :alt: Pyteomics is awesome


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.

Supported Python versions
-------------------------

Pyteomics supports Python 2.7 and Python 3.3+.

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 XML parsing modules)
 - `pandas <http://pandas.pydata.org/>`_ (can be used with **pyteomics.pepxml**,
   **pyteomics.tandem**, **pyteomics.mzid**, **pyteomics.auxiliary**)
 - `sqlalchemy <http://www.sqlalchemy.org/>`_ (used by **pyteomics.mass.unimod**)
 - `pynumpress <https://pypi.org/project/pynumpress/>`_ (adds support for Numpress compression)

All dependencies are optional.

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

The preferred way to obtain Pyteomics is via `pip Python package manager <https://pip.pypa.io/>`_.
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



