Skip to main content

A framework for proteomics data analysis.

Project description

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.

Pyteomics is hosted at the following sites:

Feedback & Support

Please email to pyteomics@googlegroups.com with any questions about Pyteomics. You are welcome to use the BitBucket issue tracker to report bugs, request features, etc.

Project dependencies

Pyteomics uses the following python packages:

  • numpy

  • matplotlib (used by pyteomics.pylab_aux)

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

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

Windows

  • Download pre-compiled binary packages for Pyteomics dependencies:

  • Download a pre-compiled binary Pyteomics package from the list.

OR

  • If you have Enthought Python Distribution / ActivePython, execute in the command line:

    easy_install pip
    pip install lxml numpy matplotlib pyteomics

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyteomics-1.2.0.tar.gz (38.8 kB view details)

Uploaded Source

Built Distributions

pyteomics-1.2.0.win-amd64_py3.2.exe (264.6 kB view details)

Uploaded Source

pyteomics-1.2.0.win-amd64_py2.7.exe (264.1 kB view details)

Uploaded Source

pyteomics-1.2.0.win32_py3.2.exe (236.5 kB view details)

Uploaded Source

pyteomics-1.2.0.win32_py2.7.exe (236.5 kB view details)

Uploaded Source

File details

Details for the file pyteomics-1.2.0.tar.gz.

File metadata

  • Download URL: pyteomics-1.2.0.tar.gz
  • Upload date:
  • Size: 38.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyteomics-1.2.0.tar.gz
Algorithm Hash digest
SHA256 02a0640955316fe0c871df97f7f5f3f1be4cfa32dc0a3b13120bffe836b87ea1
MD5 361f25295a10b84575152b1708b80dcb
BLAKE2b-256 7d5a5f3f50c1788ba24031fe60e989503496f1bf316770d83f115fe9ed00aa93

See more details on using hashes here.

File details

Details for the file pyteomics-1.2.0.win-amd64_py3.2.exe.

File metadata

File hashes

Hashes for pyteomics-1.2.0.win-amd64_py3.2.exe
Algorithm Hash digest
SHA256 07c060811cda57c3f879b507613a54515a3fb1b4b57117fad99441addaa78f31
MD5 532a0fdfefad7412b9b3a5ae7e385a71
BLAKE2b-256 7c44c6243622f77822ebb006f9d21edb270f4b80af58b81397db5f285205d801

See more details on using hashes here.

File details

Details for the file pyteomics-1.2.0.win-amd64_py2.7.exe.

File metadata

File hashes

Hashes for pyteomics-1.2.0.win-amd64_py2.7.exe
Algorithm Hash digest
SHA256 be2196dabb80bac21288cc8ff5364006f8abb5117f260166fbc88b39e165f5a3
MD5 2ae39cbb8b4a56e1ab452ca0df7b449e
BLAKE2b-256 8808ae1b5b3df1e8c34887a21c270722095e5e3eeeff1595736e6f0c9a5399e2

See more details on using hashes here.

File details

Details for the file pyteomics-1.2.0.win32_py3.2.exe.

File metadata

File hashes

Hashes for pyteomics-1.2.0.win32_py3.2.exe
Algorithm Hash digest
SHA256 6cf5c350c7245c7641de97b297faae4241116320f603426dee5398533cf19945
MD5 7f9132f8c812d8ac372516c43d8187bb
BLAKE2b-256 42207148e203e73c1a514ebda44bea2badc66393d8f9919a257b158909a41da7

See more details on using hashes here.

File details

Details for the file pyteomics-1.2.0.win32_py2.7.exe.

File metadata

File hashes

Hashes for pyteomics-1.2.0.win32_py2.7.exe
Algorithm Hash digest
SHA256 00872deb0d9e5912f4b0c05b5e609b90de3e702ec42e875552d02632690b9474
MD5 052fb6231b36c534e5daa784bd02e8d6
BLAKE2b-256 39e2b7961789559379b8b4cfb389e034a09a44c9695d1252228c8cd98585bd52

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page