Software toolkit for protein complex prediction and differential analysis of cofractionation mass spectrometry datasets.
These instructions will guide you to obtain a copy of the project, to run on your local machine, and to test the compatibility with your current Python packages.
We recommend using anaconda as it contains the majority of the required packages for PCprophet. If you are using Windows and having problems adding paths of anaconda and Python, please click here for guidance. Please also refer to this page for potential errors when importing python packages in Windows.
Ensure that you have installed the GitHub tool and 'git-lfs' command specifically for large file transfer. Please see here for installing GitHub and here for the installing 'git-lfs' command.
git-lfs clone https://github.com/anfoss/PCprophet PCprophet
This will get you a working copy of PCprophet into a folder called PCprophet.
For usage of PCprophet, refer to the PCprophet_instructions.md.
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
- Andrea Fossati - Initial work - anfoss andrea.fossati@ucsf.edu
- Chen Li - Initial work - chen.li@monash.edu
This project is licensed under the MIT License - see the LICENSE.md file for details.
PCprophet citation:
Fossati, A., Li, C., Uliana, F., Wendt, F., Frommelt, F., Sykacek, P., Heusel, M., Hallal, M., Bludau, I., Capraz, T., Xue, P., Song, J., Wollscheid, B., Purcell, A. W., Gstaiger, M., & Aebersold, R. (2021). PCprophet: a framework for protein complex prediction and differential analysis using proteomic data. Nature Methods, 13. https://doi.org/10.1038/s41592-021-01107-5
- mojaje for the implementation of GO tree parsing.