pyteomics

A framework for proteomics data analysis.

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Project links

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.

Supported Python versions

Pyteomics supports Python 2.7 and Python 3.3+.

Project dependencies

Pyteomics uses the following Python packages:

numpy

matplotlib (used by pyteomics.pylab_aux)

lxml (used by XML parsing modules)

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

sqlalchemy (used by pyteomics.mass.unimod)

pynumpress (adds support for Numpress compression)

All dependencies are optional.

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:

python-pyteomics

python2-pyteomics

Windows

Get pip, if you don’t have it yet.

Install Pyteomics and its dependencies:

pip install lxml numpy matplotlib pyteomics

Project details

These details have not been verified by PyPI

Project links

Release history Release notifications | RSS feed

4.7.5

Oct 18, 2024

4.7.4

Oct 1, 2024

4.7.3

Jul 30, 2024

4.7.2

Apr 26, 2024

4.7.1

Feb 14, 2024

4.7

Feb 5, 2024

4.6.3

Nov 1, 2023

4.6.2

Sep 7, 2023

4.6.1

Aug 31, 2023

4.6

Apr 20, 2023

4.5.6

Oct 31, 2022

4.5.5

Aug 21, 2022

4.5.4

Jul 18, 2022

4.5.3

Feb 23, 2022

This version

4.5.2

Dec 16, 2021

4.5.1

Dec 10, 2021

4.5

Sep 20, 2021

4.4.2

Mar 26, 2021

4.4.1

Jan 14, 2021

4.4.0

Nov 16, 2020

4.4.0b0 pre-release

Nov 7, 2020

4.3.3

Sep 29, 2020

4.3.2

May 20, 2020

4.3.1

May 18, 2020

4.3

May 18, 2020

4.3a1 pre-release yanked

May 18, 2020

4.2

Feb 3, 2020

4.1.2

Jun 7, 2019

4.1.1

May 6, 2019

4.1

Mar 14, 2019

4.0.1

Jan 7, 2019

4.0

Jan 5, 2019

3.5.1

May 28, 2018

3.5

May 28, 2018

3.4.2

Jun 30, 2017

3.4.1

Feb 20, 2017

3.4

Sep 8, 2016

3.3.1

May 27, 2016

3.3

May 19, 2016

3.2

Feb 18, 2016

3.1.1

Oct 11, 2015

3.1

Sep 22, 2015

3.0.1

Apr 15, 2015

3.0.0

Apr 7, 2015

2.5.5

Jan 13, 2015

2.5.4

Jan 1, 2015

2.5.3

Dec 19, 2014

2.5.2

Nov 21, 2014

2.5.1

Oct 28, 2014

2.5.0

Oct 20, 2014

2.4.3

Jun 20, 2014

2.4.2

May 6, 2014

2.4.1

May 4, 2014

2.4.0

Apr 1, 2014

2.3.0

Feb 20, 2014

2.2.2

Dec 22, 2013

2.2.1

Nov 27, 2013

2.2.0

Oct 28, 2013

2.1.6

Sep 3, 2013

2.1.5

Apr 25, 2013

2.1.4

Apr 10, 2013

2.1.3

Feb 26, 2013

2.1.2

Feb 1, 2013

2.1.1

Jan 27, 2013

2.1.0

Jan 14, 2013

2.0.3

Oct 23, 2012

2.0.2

Oct 4, 2012

2.0.1

Oct 4, 2012

2.0

Oct 3, 2012

1.2.5

Jun 17, 2012

1.2.4

Apr 25, 2012

1.2.3

Apr 18, 2012

1.2.2

Apr 10, 2012

1.2.1

Apr 7, 2012

1.2.0

Apr 5, 2012

1.1.0

Mar 9, 2012

1.0.0

Feb 14, 2012

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