PyAMPA is a complete new implementation of the AMPA algorithm (https://tcoffee.crg.eu/apps/ampa/do), originally designed to predict antimicrobial sequences in proteins. With PyAMPA you can now predict antimicrobial sequences from entire proteomes and has new features such as optimization, mutagenesis and interactive tables for visualizing data.
If you found this work useful, please cite us:
--PyAMPA-- Ramos-Llorens M, Bello-Madruga R, Valle J, Andreu D, Torrent M. 0. PyAMPA: a high-throughput prediction and optimization tool for antimicrobial peptides. mSystems 0:e01358-23.
--Original AMPA-- Marc Torrent, Paolo Di Tommaso, David Pulido, M. Victòria Nogués, Cedric Notredame, Ester Boix, David Andreu: AMPA: an automated web server for prediction of protein antimicrobial regions (2011) Bioinformatics 28(1):130-131.
NEW!: PyAMPA is also available in google colab: PyAMPA.
Follow the instructions below to set up and run the application.
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Python 3 (tested with Python 3.11) Alreday installed by default on macOS and Linux OS but if using Windows you may need to install Python 3 Please check your current version of Python
python --version
If your version is < 3.11, updating Python is suggested
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Tkinter for the GUI
To install Tkinter:
pip install tk
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Additional libraries: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Pillow, BioPython and Tqdm. You can install the required dependencies using the following command:
pip install numpy pandas matplotlib seaborn scikit-learn==1.2.2 pillow biopython tqdm
Download the main.py
file and all other files to your local machine.
After installing the required dependencies and downloading the application, follow the steps below to run it:
- Navigate to the directory containing the
main.py
file. - Run the following command:
python main.py
The application should open, and you can interact with it through the graphical user interface.
Within the application, you can:
- Predict antimicrobial peptides from entire proteomes.
- Select peptide sequences for optimization or mutagenesis.
- Perform various analyses on peptide sequences and visualize the results using heatmaps and other graphical representations.
If you encounter any issues or have questions about specific functionalities, please refer to the code documentation or contact the development team.