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planemo upload for repository https://github.com/bgruening/galaxytools/tree/rna_commander/tools/rna_tools/rna_commender commit cc090387231a51b44f84298cd3e149fc6643abb0
author | bgruening |
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date | Tue, 31 May 2016 04:29:57 -0400 |
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#!/usr/bin/env python """Recommendation.""" import argparse import sys from rbpfeatures import RBPVectorizer from data import PredictDataset from recommend import Predictor from theano import config __author__ = "Gianluca Corrado" __copyright__ = "Copyright 2016, Gianluca Corrado" __license__ = "MIT" __maintainer__ = "Gianluca Corrado" __email__ = "gianluca.corrado@unitn.it" __status__ = "Production" config.floatX = 'float32' if __name__ == '__main__': parser = argparse.ArgumentParser( description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('fasta', metavar='fasta', type=str, help="""Fasta file containing the RBP \ sequences.""") args = parser.parse_args() v = RBPVectorizer(fasta=args.fasta) rbp_fea = v.vectorize() if rbp_fea is not None: # Define and load dataset D = PredictDataset( fp=rbp_fea, fr="AURA_Human_data/RNA_features/HT_utrs.h5") dataset = D.load() model = "AURA_Human_data/model/trained_model.pkl" # Define the Trainer and train the model P = Predictor(predict_dataset=dataset, trained_model=model, serendipity_dic=model + '_', output="output.txt") P.predict() else: sys.exit("""The queried protein has no domain similarity with the proteins in the training dataset. It cannot be predicted.""")