CLI interface for the PSAP classifier, Mierlo, G. van. Predicting protein condensate formation using machine learning (Manuscript in Preparation).

• Free software: MIT license

git clone https://github.com/vanheeringen-lab/psap.git
cd psap && python setup.py install

psap train -f /path/to/peptide-trainingset.fasta  -o /output/directory

The trained RandomForest classifier is exported to json format and stored in the output directory.

psap predict -m /path/to/model.json -f /path/to/peptid-testset.fasta -o /output/directory

When no model is provided (-m) psap loads the default classifier stored in /data/model.

psap annotate -f /path/to/peptide.fasta -o /output/directory

Annotates a peptide fasta with biochemical features. This step is included in train and predict.

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.