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Introduction
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The latest Documentation was generated on: |today|
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General information
*******************
Module to parse mzML data in Python based on cElementTree
Copyright 2010-2011 by:
| T. Bald,
| J. Barth,
| A. Niehues,
| M. Specht,
| M. Hippler,
| C. Fufezan
===================
Contact information
===================
Please refer to:
| Dr. Christian Fufezan
| Institute of Plant Biology and Biotechnology
| Schlossplatz 7 , R 372
| or
| Hindenburgplatz 55 (mail)
| University of Muenster
| Germany
| eMail: christian@fufezan.net
| Tel: +049 251 83 24861
|
| http://www.uni-muenster.de/Biologie.IBBP.AGFufezan
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Summary
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pymzML is an extension to Python that offers
* a) easy access to mass spectrometry (MS) data that allows the rapid development of tools,
* b) a very fast parser for mzML data, the standard in mass spectrometry data format and
* c) a set of functions to compare or handle spectra.
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Implementation
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pymzML requires Python2.6.5+ and is fully compatible with Python3.
The module is freely available on pymzml.github.com or pypi,
published under LGPL and requires no additional modules to be installed.
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Download
********
Get the latest version via github
| https://github.com/pymzml/pymzML
or the latest package at
| http://pymzml.github.com/dist/pymzml.tar.bz2
| http://pymzml.github.com/dist/pymzml.zip
The complete Documentation can be found as pdf
| http://pymzml.github.com/dist/pymzml.pdf
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Citation
********
Please cite us when using pymzML in your work.
Bald, T., Barth, J., Niehues, A., Specht, M., Hippler, M., and Fufezan, C. (2012) pymzML - Python module for high throughput bioinformatics on mass spectrometry data, Bioinformatics, doi: 10.1093/bioinformatics/bts066
The original publication can be found here:
| http://bioinformatics.oxfordjournals.org/content/early/2012/02/02/bioinformatics.bts066.abstract
| http://bioinformatics.oxfordjournals.org/content/early/2012/02/02/bioinformatics.bts066.full.pdf
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Installation
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sudo python setup.py install
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Introduction
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Mass spectrometry has evolved into a very diverse field that relies heavily on
high throughput bioinformatic tools. Due to the increasing complexity of the
questions asked and biological problems addressed, standard tools might not
be sufficient and tailored tools still
have to be developed. However, the development of such tools has been hindered by
proprietary data formats and the lack of an unified mass spectrometric data
file standard.
The latter has been overcome by the publication of the mzML standard
by the HUPO Proteomics Standards Initiative (Deutsch, 2008) (http://www.psidev.info/)
and soon all manufactures will hopefully offer a way to convert
their format into this standardized one in order to stay comparable and competitive.
Therefore in order to rapidly develop bioinformatic tools that can explore
mass spectrometry data one needs a portable, robust, yet quick and
easy interface to mzML files.
The Python scripting language (http://python.org) is predestined for such a task.
Scripting languages carry several advantages compared to compiled programs and
although compiled programs tend to be faster, scripting languages can already
compete successfully in some tasks.
For example, XML parsing is extremely optimized in Python due to the
cElementTree module (http://effbot.org/zone/element-index.htm),
which allows XML parsing in a fraction of classical C/C++ libraries,
such as libxml2 or sgmlop.
Therefore it seems natural that a well designed python mzML parser
can successfully compete with C/C++ libraries currently available
while offering the advantages of a scripting language.
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