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-1.1.0.tar.gz (36.8 kB view details)

Uploaded Source

Built Distributions

pyteomics-1.1.0.win-amd64_py2.7.exe (263.0 kB view details)

Uploaded Source

pyteomics-1.1.0.win-amd64_py2.6.exe (263.0 kB view details)

Uploaded Source

pyteomics-1.1.0.win32_py2.7.exe (235.4 kB view details)

Uploaded Source

pyteomics-1.1.0.win32_py2.6.exe (235.4 kB view details)

Uploaded Source

File details

Details for the file pyteomics-1.1.0.tar.gz.

File metadata

  • Download URL: pyteomics-1.1.0.tar.gz
  • Upload date:
  • Size: 36.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyteomics-1.1.0.tar.gz
Algorithm Hash digest
SHA256 72f9b88994e7d5180fe423d3fe1586f17910550d31443cc4be7e20b0d14640f3
MD5 ab7845a2bc60ff3d6f808992a4e70777
BLAKE2b-256 9ab193ddb8d260266970cc1c93009a86b3eeecc47a20f9546f5ea0218841904e

See more details on using hashes here.

File details

Details for the file pyteomics-1.1.0.win-amd64_py2.7.exe.

File metadata

File hashes

Hashes for pyteomics-1.1.0.win-amd64_py2.7.exe
Algorithm Hash digest
SHA256 04b5ab2e786b65873f5129e708a66282aa42c06ddfe92d52f5fc5c23c5520bbe
MD5 2ca97deb812de228e133f338c201ff40
BLAKE2b-256 bbca476c7c6266133e992dc3b00349b3c71a702c084e51c907486b7527767cad

See more details on using hashes here.

File details

Details for the file pyteomics-1.1.0.win-amd64_py2.6.exe.

File metadata

File hashes

Hashes for pyteomics-1.1.0.win-amd64_py2.6.exe
Algorithm Hash digest
SHA256 1b70083ee10aefe449597f7bb38b0ebbf28e8668a6ffa0515f9632ce10acb187
MD5 1bec4deb43701a84fc3278566f70cc18
BLAKE2b-256 4c571ae971bd404cb52d6f13689486cb3d629408e7a610de51fb5ed184b9298c

See more details on using hashes here.

File details

Details for the file pyteomics-1.1.0.win32_py2.7.exe.

File metadata

File hashes

Hashes for pyteomics-1.1.0.win32_py2.7.exe
Algorithm Hash digest
SHA256 55e385e6f2c8a6f1fec2cd6a4a310eed756f6a587f32aaf0b7d31e1c8cd17ddb
MD5 b45fdbdeeda739c7ab07f9c740bc1d71
BLAKE2b-256 904dd2c18bc424c58f593542aba9d3411f3278be10a0a10503fefed006cb2f12

See more details on using hashes here.

File details

Details for the file pyteomics-1.1.0.win32_py2.6.exe.

File metadata

File hashes

Hashes for pyteomics-1.1.0.win32_py2.6.exe
Algorithm Hash digest
SHA256 e108c2901ddf653435f391d1603634c2834e78707adc0ed9b61ca6854319308d
MD5 8cd0e0ce1afe33f75419041bb922cd95
BLAKE2b-256 60192453aa52e50c9492f71fbd52b4d45c94267b4b168716ee7f838dd937724e

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