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Python Package for the downstream analysis of label-free mass-spectrometry-based proteomics data

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An open-source Python package of the AlphaPept ecosystem from the Mann Group at the University of Copenhagen.


About

An open-source Python package for downstream mass spectrometry downstream data analysis from the Mann Group at the University of Copenhagen.


Citation

Manuscript: AlphaPeptStats: an open-source Python package for automated, scalable and industrial-strength statistical analysis of mass spectrometry-based proteomics

Citation:
Krismer, E., Strauss M. & Mann M. (2023). AlphaPeptStats: an open-source Python package > for automated, scalable and industrial-strength statistical analysis of mass >spectrometry-based proteomics. BioRxiv [Preprint] https://doi.org/10.1101/2023.03.10.532057


Installation

AlphaPeptStats can be used as python library (pip-installation), or Graphical User Interface (either pip-installation or one-click installer). Further we provide a Dockerimage for the GUI.


## Pip Installation

AlphaStats can be installed in an existing Python 3.8/3.9/3.10 environment with a single bash command.

pip install alphastats

Usage

For the Graphical User Interface

alphastats gui

AlphaStats can be imported as a Python package into any Python script or notebook with the command import alphastats.

A brief Jupyter notebook tutorial on how to use the API is also present in the nbs folder.


One Click Installer

One click Installer for MacOS, Windows and Linux can be found here


## Docker Image

We provide two Dockerfiles, one for the library and one for the Graphical User Interface. The Image can be pulled from Dockerhub

docker pull elenakrismer/alphapeptstats_streamlit

GUI

Troubleshooting

In case of issues, check out the following:

  • Issues: Try a few different search terms to find out if a similar problem has been encountered before

License

AlphaStats was developed by the Mann Group at the University of Copenhagen and is freely available with an Apache License. External Python packages (available in the requirements folder) have their own licenses, which can be consulted on their respective websites.


How to contribute

If you like this software, you can give us a star to boost our visibility! All direct contributions are also welcome. Feel free to post a new issue or clone the repository and create a pull request with a new branch. For an even more interactive participation, check out the discussions and the the Contributors License Agreement.


Changelog

See the HISTORY.md for a full overview of the changes made in each version.

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Python Package for the downstream analysis of label-free mass-spectrometry-based proteomics data

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  • Jupyter Notebook 98.6%
  • Python 1.4%