PICA

Phenotype Investigation with Classification Algorithms (PICA) is a Python framework for testing genotype-phenotype association algorithms.

Command-line

Use the option -h for help with any command.

• train: Train a given data mining algorithm and output model to file.

Example usage: train.py --algorithm cpar.CPARTrainer --samples examples/genotype_prokaryote.profile --classes examples/phenotype.profile --targetclass THERM --output output.rules

• test

Test a model with a classification algorithm and given model. Example usage: test.py --algorithm cpar.CPARClassifier --samples examples/genotype_prokaryote.profile --classes examples/phenotype.profile --targetclass THERM --model_filename output.rules --model_accuracy mi

• crossvalidate

Train and test various replicates with the given training and testing algorithms. Example usage: crossvalidate.py --training_algorithm cpar.CPARTrainer --classification_algorithm cpar.CPARClassifier --accuracy_measure mi --replicates 10 --folds 5 --samples examples/genotype_prokaryote.profile --classes examples/phenotype.profile --targetclass THERM --output_filename resutls.txt --metadata examples/taxonomic_confounders_propagated.txt