A framework for proteomics data analysis.

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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.

Required Python versions

Pyteomics supports Python 2.7 and Python 3. Python 2.6 and older are not supported.

Project dependencies

Pyteomics uses the following python packages:

  • numpy

  • matplotlib (used by pyteomics.pylab_aux)

  • lxml (used by pyteomics.mzml, pyteomics.pepxml, pyteomics.mzid, pyteomics.tandem)

  • pandas (can be used with pyteomics.pepxml, pyteomics.tandem, pyteomics.auxiliary)

  • sqlalchemy (used by pyteomics.mass.unimod)

GNU/Linux

The preferred way to obtain Pyteomics is via pip Python package manager. 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:

Windows

  • Get pip, if you don’t have it yet.

  • Install Pyteomics and its dependencies:

    pip install lxml numpy matplotlib pyteomics

Project details

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4.7.5

4.7.4

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