The latest Documentation was generated on: October 25, 2014
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
Please refer to:
Dr. Christian FufezanInstitute of Plant Biology and BiotechnologySchlossplatz 7 , R 372orHindenburgplatz 55 (mail)University of MuensterGermanyeMail: christian@fufezan.netTel: +049 251 83 24861
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.
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
sudo python setup.py install
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.