<commit_before>Introduction
############

*pyQms enables universal and accurate quantification of mass spectrometry data*


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Summary
*******

pyQms is an extension to Python that offers amongst other things

    a) fast and accurate quantification of all high-res LC-MS data

    b) full labeling and modification flexibility

    c) full platform independence



Abstract
********

Quantitative mass spectrometry (MS) is a key technique in many research areas (Yates III et al. 2009), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching which offers accurate quality assessment of the quantification and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large-scale and high-throughput, the most challenging task for a quantification algorithm.

            -- <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., and <NAME>. (2017) pyQms enables universal and accurate quantification of mass spectrometry data. MCP In Press

Link to manuscript.

http://www.mcponline.org/content/early/2017/07/20/mcp.M117.068007.abstract 


pyQms module
************
At its core, pyQms is a Python module that allows a isotope pattern library to
be initialized and any list of (mz, intensity) to be matched against the library,
yielding a mScore.

Documentation
*************

http://pyqms.readthedocs.io/en/latest/


Implementation
**************

pyQms requires Python3.4+ .


The module is freely available on pyqms.github.io or pypi,
published under MIT LGPL and requires no additional modules to be installed.
For fast spectra from mzML access we recommend pymzML (Bald et al. 2012).
For example scripts it is necessary to install pymzML as well or
change the code for alternated spectra access. For some scripts also the
openpyxl module is required.

.. _download_instructions:

Download
********

Get the latest version via github
    | https://github.com/pyQms/pyQms


Citation
********

Please cite us when using pyQms in your work.


The original publication can be found here:
    <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., and <NAME>. (2017) pyQms enables universal and accurate quantification of mass spectrometry data. MCP In Press


http://www.mcponline.org/content/early/2017/07/20/mcp.M117.068007.abstract 


.. _installation_instructions:

Installation
************

Install requirements::

    user@localhost:~$ cd pyqms
    user@localhost:~/pyqms$ pip3.4 install -r requirements.txt


.. note:

    Pip is included in Python 3.4 and higher. However, it might not be
    included in in your system's PATH environment variable.
    If this is the case, you can either add the Python scripts directory to your
    PATH env variable or use the path to the pip.exe directly for the
    installation, e.g.: ~/Python34/Scripts/pip.exe install -r requirements.txt

<commit_msg>Updated README with latest citation and DOI<commit_after>Introduction
############

*pyQms enables universal and accurate quantification of mass spectrometry data*


|doc-status| |build-status-travis| |build-status-appveyor|

.. |doc-status| image:: https://readthedocs.org/projects/pyqms/badge/?version=latest
   :target: http://pyqms.readthedocs.io/en/latest/?badge=latest
   :alt: Documentation Status

.. |build-status-travis| image:: https://travis-ci.org/pyQms/pyqms.svg?branch=master
   :target: https://travis-ci.org/pyQms/pyqms
   :alt: Travis CI status

.. |build-status-appveyor| image:: https://ci.appveyor.com/api/projects/status/j6bwfx62l0j8ddsi?svg=true
   :target: https://ci.appveyor.com/project/JB-MS/pyqms
   :alt: AppVeyor CI status


Summary
*******

pyQms is an extension to Python that offers amongst other things

    a) fast and accurate quantification of all high-res LC-MS data

    b) full labeling and modification flexibility

    c) full platform independence



Abstract
********

Quantitative mass spectrometry (MS) is a key technique in many research areas (Yates III et al. 2009), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching which offers accurate quality assessment of the quantification and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large-scale and high-throughput, the most challenging task for a quantification algorithm.

            -- <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., and <NAME>. (2017) pyQms enables universal and accurate quantification of mass spectrometry data. MCP In Press

Link to manuscript.

http://www.mcponline.org/content/early/2017/07/20/mcp.M117.068007.abstract 


pyQms module
************
At its core, pyQms is a Python module that allows a isotope pattern library to
be initialized and any list of (mz, intensity) to be matched against the library,
yielding a mScore.

Documentation
*************

http://pyqms.readthedocs.io/en/latest/


Implementation
**************

pyQms requires Python3.4+ .


The module is freely available on pyqms.github.io or pypi,
published under MIT LGPL and requires no additional modules to be installed.
For fast spectra from mzML access we recommend pymzML (Bald et al. 2012).
For example scripts it is necessary to install pymzML as well or
change the code for alternated spectra access. For some scripts also the
openpyxl module is required.

.. _download_instructions:

Download
********

Get the latest version via github
    | https://github.com/pyQms/pyQms


Citation
********

Please cite us when using pyQms in your work.


The original publication can be found here:
    <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., and <NAME>. (2017) pyQms enables universal and accurate quantification of mass spectrometry data. Mol. Cell. Proteomics 16, 1736–1745
    

Full article
============

http://www.mcponline.org/content/16/10/1736


Early access article version
============================


http://www.mcponline.org/content/early/2017/07/20/mcp.M117.068007.abstract 

DOI
===

10.1074/mcp.M117.068007


.. _installation_instructions:

Installation
************

Install requirements::

    user@localhost:~$ cd pyqms
    user@localhost:~/pyqms$ pip3.4 install -r requirements.txt


.. note:

    Pip is included in Python 3.4 and higher. However, it might not be
    included in in your system's PATH environment variable.
    If this is the case, you can either add the Python scripts directory to your
    PATH env variable or use the path to the pip.exe directly for the
    installation, e.g.: ~/Python34/Scripts/pip.exe install -r requirements.txt


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