Pyteomics documentation v4.7.1

Welcome to Pyteomics tutorial!

Contents   ::   Introduction  »

Welcome to Pyteomics tutorial!

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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.

Citation

Pyteomics is distributed under Apache License version 2.0.

When using or redistributing Pyteomics, or parts of it, please cite the following papers:

Goloborodko, A.A.; Levitsky, L.I.; Ivanov, M.V.; and Gorshkov, M.V. (2013) “Pyteomics - a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics”, Journal of The American Society for Mass Spectrometry, 24(2), 301–304. DOI: 10.1007/s13361-012-0516-6

Levitsky, L.I.; Klein, J.; Ivanov, M.V.; and Gorshkov, M.V. (2018) “Pyteomics 4.0: five years of development of a Python proteomics framework”, Journal of Proteome Research. DOI: 10.1021/acs.jproteome.8b00717

Backup of old repo

Pyteomics source code used to be hosted on Bitbucket. An archive of issues and pull requests is stored at: https://levitsky.github.io/bitbucket_backup/#!/levitsky/pyteomics.

Pyteomics Extensions

Additional, third-party packages extending the Pyteomics functionality can be insalled separately:

Feedback & Support

Your questions and suggestions are welcome at:

Relation to other proteomics data analysis tools

Our goal is to create an infrastructure for proteomics data analysis within Python ecosystem. Pyteomics is not a proteomic search engine, nor does it any data conversion. There are other tools for that. Pyteomics does not aim to substitute any of these, but rather to coexist and complement them.

Contents:

Indices and tables

Contents   ::   Introduction  »