Mercurial > repos > jay > pdaug_peptide_data_plotting
view PDAUG_Uversky_Plot/PDAUG_Uversky_Plot.py @ 7:86cb904383fb draft
"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit 32b9c48c81639a81be24bb3e2f48dc0a81c0deca"
author | jay |
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date | Sun, 09 Jan 2022 05:03:52 +0000 |
parents | 9e347250e3a1 |
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import matplotlib matplotlib.use('Agg') import os import sys sys.path.insert(0, os.path.abspath('..')) from quantiprot.utils.io import load_fasta_file from quantiprot.utils.feature import Feature, FeatureSet from quantiprot.utils.sequence import compact from quantiprot.metrics.aaindex import get_aa2charge, get_aa2hydropathy from quantiprot.metrics.basic import average, average_absolute from matplotlib import pyplot as plt def Run_Uverskey(Fasta1, Fasta2, OutFile): amyload_seq = load_fasta_file(Fasta1) disprot_seq = load_fasta_file(Fasta2) net_abs_charge = Feature(get_aa2charge(default=0)).then(average_absolute) mean_hydropathy = Feature(get_aa2hydropathy(default=0)).then(average) uversky_fs = FeatureSet("uversky") uversky_fs.add(mean_hydropathy, name="mean_hydropathy") uversky_fs.add(net_abs_charge, name="net_abs_charge") amyload_uversky_seq = uversky_fs(amyload_seq) disprot_uversky_seq = uversky_fs(disprot_seq) amyload_data_x = amyload_uversky_seq.columns(feature="mean_hydropathy")[0] amyload_data_y = amyload_uversky_seq.columns(feature="net_abs_charge")[0] plt.plot(amyload_data_x, amyload_data_y,'.', label="Amyload") disprot_data = compact(disprot_uversky_seq).columns() plt.plot(disprot_data[0], disprot_data[1],'.', label="Disprot") plt.plot([-0.78, 0.835], [0.0, 0.5],'k') plt.xlabel("mean hydrophobicity") plt.ylabel("net abs charge") plt.legend() plt.savefig(OutFile) if __name__=="__main__": import argparse parser = argparse.ArgumentParser() parser.add_argument("-f1", "--Fasta1", required=True, default=None, help="pep file") parser.add_argument("-f2", "--Fasta2", required=True, default=None, help="out put file name for str Descriptors") parser.add_argument("--OutFile", required=False, help="HTML out file", default="out.png") args = parser.parse_args() Run_Uverskey(args.Fasta1, args.Fasta2, args.OutFile)