Python wrapper for C++ LCMS library OpenMS
Project description
Introduction
This package contains Python bindings for a large part of the OpenMS library (http://www.open-ms.de) for mass spectrometry based proteomics. It thus provides providing facile access to a feature-rich, open-source algorithm library for mass-spectrometry based proteomics analysis. These Python bindings allow raw access to the data-structures and algorithms implemented in OpenMS, specifically those for file access (mzXML, mzML, TraML, mzIdentML among others), basic signal processing (smoothing, filtering, de-isotoping and peak-picking) and complex data analysis (including label-free, SILAC, iTRAQ and SWATH analysis tools).
The pyOpenMS package runs - like OpenMS - on Windows, Linux and OSX.
Installation
We provide binary packages for Python 2.7 and 3.3, 3.4 and 3.5 on Windows (64 bit and 32 bit) and Linux 64 bit which makes the installation very straightforward with pip. Note that Python 3.5 is not yet supported under Windows. For other platforms, please refer to the compilation instructions.
Binary installation
On linux machines you can install pyopenms with (you will need numpy in addition):
$ easy_install pyopenms
For other systems first ensure that your pip is up to date, then install the pyopenms wheel (you will need numpy in addition):
$ pip install -U pip $ pip install -U wheel $ pip install pyopenms
Source installation
Building the Python packages is generally not straight forward, we recommend that you use the binary packages provided for common Python interpreter versions and operating systems. If you decide to build pyOpenMS on your own, please read http://ftp.mi.fu-berlin.de/pub/OpenMS/release-documentation/html/pyOpenMS.html and https://github.com/OpenMS/OpenMS/wiki/Build-pyOpenMS-on-Windows and ask for help on our mailing list https://lists.sourceforge.net/lists/listinfo/open-ms-general
License
pyOpenMS is published under the 3-clause BSD licence, see ./pyOpenMS/License.txt
Documentation
pyOpenMS follows the OpenMS documentation very closely. Additionally, there is also a pyOpenMS Manual available. The online manual contains a complete record of every wrapped class and function while the documentation of the corresponding class or function can be inferred from the OpenMS online documentation.
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