Repository 'pdaug_addclasslabel'
hg clone https://toolshed.g2.bx.psu.edu/repos/jay/pdaug_addclasslabel

Changeset 0:2df11ea23f10 (2020-10-28)
Next changeset 1:8c2ee62ce9d8 (2020-12-29)
Commit message:
"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
added:
PDAUG_AA_Property_Based_Peptide_Descriptor/PDAUG_AA_Property_Based_Peptide_Descriptor.py
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out1.tsv
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out2.tsv
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out3.tsv
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out4.tsv
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out5.tsv
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out5.tsvOLD
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out6.tsv
PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/test.fasta
PDAUG_AA_Property_Based_Peptide_Generation/PDAUG_AA_Property_Based_Peptide_Generation.py
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out1.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out2.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out3.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out4.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out5.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out6.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out7.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out8.fasta
PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out9.fasta
PDAUG_AddClassLabel/PDAUG_AddClassLabel.py
PDAUG_AddClassLabel/PDAUG_AddClassLabel.xml
PDAUG_AddClassLabel/test-data/new.tsv
PDAUG_AddClassLabel/test-data/out.tsv
PDAUG_Basic_Plots/PDAUG_Basic_Plots.py
PDAUG_Basic_Plots/test-data/positive.fasta
PDAUG_Basic_Plots/test-data/test1.tsv
PDAUG_Basic_Plots/test-data/test1/report_dir/report.html
PDAUG_Basic_Plots/test-data/test1/report_dir/report.html.re
PDAUG_Basic_Plots/test-data/test2.tsv
PDAUG_Basic_Plots/test-data/test2/report_dir/.re
PDAUG_Basic_Plots/test-data/test2/report_dir/report.html
PDAUG_Basic_Plots/test-data/test2/report_dir/report.html.re
PDAUG_Basic_Plots/test-data/test3/report_dir/report.html
PDAUG_Basic_Plots/test-data/test3/report_dir/report.html.re
PDAUG_Basic_Plots/test-data/test4/report_dir/report.html.re
PDAUG_Basic_Plots/test-data/test5/out.png
PDAUG_Basic_Plots/test-data/test5/report_dir/Out.png
PDAUG_Basic_Plots/test-data/test5/report_dir/report.html
PDAUG_Fishers_Plot/PDAUG_Fishers_Plot.py
PDAUG_Fishers_Plot/test-data/negative.fasta
PDAUG_Fishers_Plot/test-data/out.png
PDAUG_Fishers_Plot/test-data/positive.fasta
PDAUG_ML_Models/PDAUG_ML_Models.py
PDAUG_ML_Models/test-data/test.tsv
PDAUG_ML_Models/test-data/test1/SVMC.tsv
PDAUG_ML_Models/test-data/test1/report_dir/SVMC.html
PDAUG_ML_Models/test-data/test1/report_dir/SVMC.tsv
PDAUG_ML_Models/test-data/test2/.zip
PDAUG_ML_Models/test-data/test2/GNBC.tsv
PDAUG_ML_Models/test-data/test2/report_dir/GNBC.html
PDAUG_ML_Models/test-data/test2/report_dir/GNBC.tsv
PDAUG_ML_Models/test-data/test3/SGDC.tsv
PDAUG_ML_Models/test-data/test3/report_dir/SGDC.html
PDAUG_ML_Models/test-data/test4/DTC.tsv
PDAUG_ML_Models/test-data/test4/report_dir/DTC.html
PDAUG_ML_Models/test-data/test5/GBC.tsv
PDAUG_ML_Models/test-data/test5/report_dir/GBC.html
PDAUG_ML_Models/test-data/test6/RFC.tsv
PDAUG_ML_Models/test-data/test6/report_dir/RFC.html
PDAUG_ML_Models/test-data/test7/LRC.tsv
PDAUG_ML_Models/test-data/test7/report_dir/LRC.html
PDAUG_ML_Models/test-data/test8/KNC.tsv
PDAUG_ML_Models/test-data/test8/report_dir/KNC.html
PDAUG_ML_Models/test-data/test9/MLP.tsv
PDAUG_ML_Models/test-data/test9/report_dir/MLP.html
PDAUG_Merge_Dataframes/PDAUG_Merge_Dataframes.py
PDAUG_Merge_Dataframes/test-data/.RData
PDAUG_Merge_Dataframes/test-data/.Rhistory
PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Blast_baseline_bacteriocin_paper-checkpoint.ipynb
PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Untitled-checkpoint.ipynb
PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Untitled1-checkpoint.ipynb
PDAUG_Merge_Dataframes/test-data/1.tsv
PDAUG_Merge_Dataframes/test-data/2.tsv
PDAUG_Merge_Dataframes/test-data/3.tsv
PDAUG_Merge_Dataframes/test-data/4.tsv
PDAUG_Merge_Dataframes/test-data/5.tsv
PDAUG_Merge_Dataframes/test-data/6.tsv
PDAUG_Merge_Dataframes/test-data/out.tsv
PDAUG_Peptide_CD_Spectral_Analysis/PDAUG_Peptide_CD_Spectral_Analysis.py
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro1/0.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro1/1.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro2/0.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro2/1.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro3/0.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro3/1.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Halicity.tsv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF1/0.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF1/1.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF1/1_M.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF2/0.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF2/1.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF2/1_M.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF3/0.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF3/1.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/PDF3/1_M.pdf
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Peptide1_T.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/Peptide2_W.csv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/calc_meanres_ellipticity.tsv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/calc_molar_ellipticity.tsv
PDAUG_Peptide_CD_Spectral_Analysis/test-data/helicity.tsv
PDAUG_Peptide_Core_Descriptors/PDAUG_Peptide_Core_Descriptors.py
PDAUG_Peptide_Core_Descriptors/test-data/Out.tsv
PDAUG_Peptide_Core_Descriptors/test-data/test.fasta
PDAUG_Peptide_Core_Functions/PDAUG_Peptide_Core_Functions.py
PDAUG_Peptide_Core_Functions/test-data/out1.fasta
PDAUG_Peptide_Core_Functions/test-data/out2.fasta
PDAUG_Peptide_Core_Functions/test-data/out3.fasta
PDAUG_Peptide_Core_Functions/test-data/out4.fasta
PDAUG_Peptide_Core_Functions/test-data/test1.fasta
PDAUG_Peptide_Core_Functions/test-data/test2.fasta
PDAUG_Peptide_Core_Functions/test-data/test3.fasta
PDAUG_Peptide_Core_Functions/test-data/test4.fasta
PDAUG_Peptide_Data_Access/PDAUG_Peptide_Data_Access.py
PDAUG_Peptide_Data_Access/test-data/apd.tsv
PDAUG_Peptide_Data_Access/test-data/camp.tsv
PDAUG_Peptide_Data_Access/test-data/out.tsv
PDAUG_Peptide_Data_Plotting/PDAUG_Peptide_Data_Plotting.py
PDAUG_Peptide_Data_Plotting/test-data/out1.png
PDAUG_Peptide_Data_Plotting/test-data/out2.png
PDAUG_Peptide_Data_Plotting/test-data/out3.png
PDAUG_Peptide_Data_Plotting/test-data/out4.png
PDAUG_Peptide_Data_Plotting/test-data/test1.tsv
PDAUG_Peptide_Data_Plotting/test-data/test2.fasta
PDAUG_Peptide_Data_Plotting/test-data/test3.tsv
PDAUG_Peptide_Data_Plotting/test-data/test4.fasta
PDAUG_Peptide_Global_Descriptors/.tsv
PDAUG_Peptide_Global_Descriptors/PDAUG_Peptide_Global_Descriptors.py
PDAUG_Peptide_Global_Descriptors/test-data/out.tsv
PDAUG_Peptide_Global_Descriptors/test-data/test.fasta
PDAUG_Peptide_Length_Distribution/PDAUG_Peptide_Length_Distribution.py
PDAUG_Peptide_Length_Distribution/test-data/out.png
PDAUG_Peptide_Length_Distribution/test-data/positive.fasta
PDAUG_Peptide_Ngrams/PDAUG_Peptide_Ngrams.py
PDAUG_Peptide_Ngrams/test-data/out.png
PDAUG_Peptide_Ngrams/test-data/test1.fasta
PDAUG_Peptide_Ngrams/test-data/test2.fasta
PDAUG_Peptide_Sequence_Analysis/PDAUG_Peptide_Sequence_Analysis.py
PDAUG_Peptide_Sequence_Analysis/test-data/ACPs.fasta
PDAUG_Peptide_Sequence_Analysis/test-data/non_ACPs.fasta
PDAUG_Peptide_Sequence_Analysis/test-data/out1.tsv
PDAUG_Peptide_Sequence_Analysis/test-data/test1.fasta
PDAUG_Peptide_Sequence_Analysis/test-data/test1/out.tsv
PDAUG_Peptide_Sequence_Analysis/test-data/test2.fasta
PDAUG_Peptide_Sequence_Analysis/test-data/test2/out2.tsv
PDAUG_Peptide_Sequence_Analysis/test-data/test3/out3.tsv
PDAUG_Peptide_Sequence_Analysis/test-data/test4/report_dir/report.html.re
PDAUG_Peptide_Sequence_Analysis/test-data/test5/out5.tsv
PDAUG_Peptide_Sequence_Analysis/test-data/test6/out.tsv
PDAUG_Peptide_Structure_Builder/PDAUG_Peptide_Structure_Builder.py
PDAUG_Peptide_Structure_Builder/test-data/DataFile/GLF.pdb
PDAUG_Peptide_Structure_Builder/test-data/test.fasta
PDAUG_Sequence_Based_Peptide_Generation/PDAUG_Sequence_Based_Peptide_Generation.py
PDAUG_Sequence_Based_Peptide_Generation/test-data/out1.fasta
PDAUG_Sequence_Based_Peptide_Generation/test-data/out2.fasta
PDAUG_Sequence_Based_Peptide_Generation/test-data/out3.fasta
PDAUG_Sequence_Based_Peptide_Generation/test-data/test1.fasta
PDAUG_Sequence_Network/PDAUG_Sequence_Network.py
PDAUG_Sequence_Network/test-data/out.png
PDAUG_Sequence_Network/test-data/positive.fasta
PDAUG_Sequence_Property_Based_Descriptors/Out.tsv
PDAUG_Sequence_Property_Based_Descriptors/PDAUG_Sequence_Property_Based_Descriptors.py
PDAUG_Sequence_Property_Based_Descriptors/test-data/Out.tsv
PDAUG_Sequence_Property_Based_Descriptors/test-data/Out1.tsv
PDAUG_Sequence_Property_Based_Descriptors/test-data/positive.fasta
PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.py
PDAUG_TSVtoFASTA/test-data/test1.tsv
PDAUG_TSVtoFASTA/test-data/test1/Negative.fasta
PDAUG_TSVtoFASTA/test-data/test1/Positive.fasta
PDAUG_TSVtoFASTA/test-data/test2.tsv
PDAUG_TSVtoFASTA/test-data/test2/Out.fasta
PDAUG_Uversky_Plot/PDAUG_Uversky_Plot.py
PDAUG_Uversky_Plot/test-data/out.png
PDAUG_Uversky_Plot/test-data/test1.fasta
PDAUG_Uversky_Plot/test-data/test2.fasta
PDAUG_Word_Vector_Descriptor/PDAUG_Word_Vector_Descriptor.py
PDAUG_Word_Vector_Descriptor/test-data/Out.tsv
PDAUG_Word_Vector_Descriptor/test-data/model.txt
PDAUG_Word_Vector_Descriptor/test-data/test.fasta
PDAUG_Word_Vector_Model/PDAUG_Word_Vector_Model.py
PDAUG_Word_Vector_Model/test-data/model.txt
PDAUG_Word_Vector_Model/test-data/test.fasta
license.txt
readme.txt
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/PDAUG_AA_Property_Based_Peptide_Descriptor.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/PDAUG_AA_Property_Based_Peptide_Descriptor.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,154 @@
+from modlamp.descriptors import *
+import pandas as pd
+import os
+
+
+
+def PepFasta(InFile):
+    file = open(InFile)
+    lines = file.readlines()
+
+    Index = []
+    Peptides = []
+
+    for line in lines:
+        if '>' in line:
+            Index.append(line.strip('\n'))
+        else:
+            Peptides.append(line.strip('\n'))
+    
+    return Peptides, Index
+
+
+def AutoCorrCal(InFile, window, ScaleName, OutFile):
+
+    list_pep_name,_ = PepFasta(InFile)
+
+    AMP = PeptideDescriptor(list_pep_name, ScaleName)
+    AMP.calculate_autocorr(int(window))
+    df = AMP.descriptor
+
+    columns = ["CroAut_"+str(i) for i in range(len(df[0]))]
+    df = pd.DataFrame(df, columns=columns)
+    df.to_csv(OutFile, index=False,sep='\t')
+
+def CrossCorrCal(InFile, window, ScaleName, OutFile):
+
+    list_pep_name,_ = PepFasta(InFile)
+
+    AMP = PeptideDescriptor(list_pep_name, ScaleName)
+    AMP.calculate_crosscorr(int(window))
+    df = AMP.descriptor
+
+    columns = ["CroCor_"+str(i) for i in range(len(df[0]))]
+    df = pd.DataFrame(df, columns=columns)
+    df.to_csv(OutFile, index=False,sep='\t')
+
+def CalculateMovementCal(InFile, window, angle, modality, ScaleName, OutFile):
+
+
+    list_pep_name,_ = PepFasta(InFile)
+
+    AMP = PeptideDescriptor(list_pep_name, ScaleName)
+    AMP.calculate_moment(int(window), int(angle), modality)
+    df = AMP.descriptor
+
+    df = pd.DataFrame(df, columns=['Movement'])
+    df.to_csv(OutFile, index=False,sep='\t')
+
+def CalculateGlobalCal(InFile, WindowSize, modality, ScaleName, OutFile):
+
+    list_pep_name,_ = PepFasta(InFile)
+
+    AMP = PeptideDescriptor(list_pep_name, ScaleName)
+    AMP.calculate_global(int(WindowSize), modality)
+    df = AMP.descriptor
+
+    df = pd.DataFrame(df, columns=['Global'])
+    df.to_csv(OutFile, index=False, sep='\t')
+
+def CalculateProfileCal(InFile, prof_type, WindowSize, ScaleName, OutFile):
+
+    list_pep_name,_ = PepFasta(InFile)
+
+    AMP = PeptideDescriptor(list_pep_name, ScaleName)
+    AMP.calculate_profile(prof_type, int(WindowSize))
+    df = AMP.descriptor
+
+    df = pd.DataFrame(df, columns=['hyPhoPro','hyPhoMov'])
+    df.to_csv(OutFile, index=False, sep='\t')
+
+def CalculateArcCal(InFile, modality, OutFile): 
+
+    list_pep_name,_ = PepFasta(InFile)
+
+    AMP = PeptideDescriptor(list_pep_name, scalename="peparc")
+    AMP.calculate_arc(modality)
+    df =  AMP.descriptor
+
+    columns = ["Arc_"+str(i) for i in range(len(df[0]))]
+    df = pd.DataFrame(df, columns=columns)
+    df.to_csv(OutFile, index=False, sep='\t')
+
+if __name__=="__main__":
+
+    import argparse
+
+    parser = argparse.ArgumentParser(description='Deployment tool')
+    subparsers = parser.add_subparsers()
+
+    Aut = subparsers.add_parser('AutoCorrCal')
+    Aut.add_argument("-i","--InFile", required=True, default=None, help="")
+    Aut.add_argument("-w","--WindowSize", required=False, default=7, help="")
+    Aut.add_argument("-s","--ScaleName", required=False, default="Eisenberg", help="")
+    Aut.add_argument("-o","--OutFile", required=False, default="Descriptor.tsv", help="")
+
+    Cro = subparsers.add_parser('CrossCorrCal')
+    Cro.add_argument("-i","--InFile", required=True, default=None, help="")
+    Cro.add_argument("-w","--WindowSize", required=False, default=7, help="")
+    Cro.add_argument("-s","--ScaleName", required=False, default="Eisenberg", help="")
+    Cro.add_argument("-o","--OutFile", required=False, default="Descriptor.tsv", help="")
+
+    Mov = subparsers.add_parser('CalculateMovement')
+    Mov.add_argument("-i","--InFile", required=True, default=None, help="")
+    Mov.add_argument("-w","--WindowSize", required=False, default=1000, help="")
+    Mov.add_argument("-a","--Angle", required=False, default=100, help="")
+    Mov.add_argument("-m","--Modality", required=False, default="max", help="")
+    Mov.add_argument("-s","--ScaleName", required=False, default="Eisenberg", help="")
+    Mov.add_argument("-o","--OutFile", required=False, default="Descriptor.tsv", help="")
+
+    Glo = subparsers.add_parser('GlobalCal')
+    Glo.add_argument("-i","--InFile", required="", default="", help="")
+    Glo.add_argument("-w","--WindowSize", required=False, default=1000, help="")
+    Glo.add_argument("-m","--Modality", required=False, default="max", help="")
+    Glo.add_argument("-s","--ScaleName", required=False, default="Eisenberg", help="")
+    Glo.add_argument("-o","--OutFile", required=False, default="Descriptor.tsv", help="")
+
+    Pro = subparsers.add_parser('ProfileCal')
+    Pro.add_argument("-i","--InFile", required=True, default=None, help="")
+    Pro.add_argument("-p","--ProfType", required=False, default="text", help="")
+    Pro.add_argument("-w","--WindowSize", required=False, default=7, help="")
+    Pro.add_argument("-s","--ScaleName", required=False, default="Eisenberg", help="")
+    Pro.add_argument("-o","--OutFile", required=False, default="Descriptor.tsv", help="")
+
+    Arc = subparsers.add_parser('ArcCal')
+    Arc.add_argument("-i","--InFile", required=True, default=None, help="")
+    Arc.add_argument("-m","--Modality", required=False, default="max", help="")
+    Arc.add_argument("-o","--OutFile", required=False, default="Descriptor.tsv", help="")
+
+    args = parser.parse_args()
+
+    if sys.argv[1] == 'AutoCorrCal':
+        AutoCorrCal(args.InFile, args.WindowSize, args.ScaleName, args.OutFile)
+    elif sys.argv[1] == 'CrossCorrCal':
+        CrossCorrCal(args.InFile, args.WindowSize, args.ScaleName, args.OutFile)
+    elif sys.argv[1] == 'CalculateMovement':
+        CalculateMovementCal(args.InFile, args.WindowSize, args.Angle, args.Modality, args.ScaleName, args.OutFile)
+    elif sys.argv[1] == 'GlobalCal':
+        CalculateGlobalCal(args.InFile, args.WindowSize, args.Modality, args.ScaleName, args.OutFile)
+    elif sys.argv[1] == 'ProfileCal':
+         CalculateProfileCal(args.InFile, args.ProfType, args.WindowSize, args.ScaleName, args.OutFile)
+    elif sys.argv[1] == 'ArcCal':
+        CalculateArcCal(args.InFile, args.Modality, args.OutFile)
+    else:
+        print ("You entered Wrong Values: ")
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out1.tsv Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,139 @@\n+CroAut_0\tCroAut_1\tCroAut_2\tCroAut_3\tCroAut_4\tCroAut_5\tCroAut_6\n+0.8795060606060603\t-0.08449999999999992\t-0.288858064516129\t0.042053333333333304\t0.4602827586206896\t-0.2472071428571427\t-0.22341481481481473\n+1.3072923076923075\t-0.01596666666666663\t-0.8552363636363634\t0.47940000000000016\t0.881111111111111\t-0.7545\t-0.6622857142857143\n+1.067375\t0.20328000000000002\t-0.32617142857142867\t0.2960615384615385\t0.4271333333333334\t-0.3241818181818182\t-0.23039999999999994\n+1.067375\t0.19728\t-0.3148857142857143\t0.2876000000000001\t0.4054666666666668\t-0.3241818181818182\t-0.20439999999999997\n+1.0655062499999999\t0.21097333333333335\t-0.3281428571428571\t0.24281538461538468\t0.46703333333333347\t-0.15281818181818183\t-0.22649999999999998\n+1.161125\t0.31423999999999996\t-0.18057142857142863\t0.28510769230769234\t0.3564666666666667\t-0.43916363636363637\t-0.24339999999999998\n+1.0977882352941173\t0.04930000000000001\t-0.29490666666666676\t0.18554285714285718\t0.658523076923077\t-0.31389999999999996\t-0.2557818181818183\n+1.134705882352941\t0.06775000000000002\t-0.4366666666666667\t0.26885714285714285\t0.657046153846154\t-0.292\t-0.4052363636363637\n+1.127741237113402\t-0.15122916666666672\t-0.0018694736842105749\t0.0048787234042553295\t0.05763333333333333\t-0.0038999999999999833\t-0.10195934065934066\n+0.3820692307692308\t-0.058033333333333326\t-0.005454545454545459\t-0.07862\t0.06544444444444447\t-0.160275\t-0.029714285714285717\n+1.9568399999999997\t-0.02258750000000002\t0.01406521739130443\t-0.018986363636363655\t-0.2288714285714286\t0.32322500000000004\t-0.2184315789473683\n+1.510758823529412\t-0.49684999999999996\t-0.3543333333333333\t0.448\t-0.4066923076923077\t-0.6197499999999999\t1.071090909090909\n+0.9799269230769231\t-0.057536000000000004\t-0.4542375\t0.18243478260869567\t0.26691818181818183\t-0.24609523809523814\t-0.24361999999999995\n+0.8490037037037036\t-0.050115384615384624\t-0.29912000000000005\t-0.14101666666666665\t0.46063478260869567\t-0.09202727272727276\t-0.06578095238095243\n+0.8335037037037037\t-0.08829230769230773\t-0.29777600000000004\t-0.02001666666666664\t0.43342608695652174\t-0.08835454545454548\t-0.11131428571428577\n+0.8942370370370369\t0.07759999999999997\t-0.16295999999999997\t0.05993333333333334\t0.5157391304347826\t0.10098181818181819\t-0.2394095238095238\n+0.9382333333333334\t-0.10223076923076922\t-0.30632000000000004\t-0.08289583333333332\t0.5684521739130435\t-0.060363636363636355\t-0.09812380952380947\n+0.9000624999999999\t0.1752869565217392\t0.16538181818181824\t0.20942380952380965\t0.69231\t0.21120000000000005\t0.0031388888888888846\n+1.5424153846153847\t-0.19912499999999997\t-0.8375272727272729\t0.082\t1.2625111111111111\t-0.21862499999999999\t-0.8468857142857142\n+1.4676028571428577\t-0.17619999999999994\t-0.41339393939393926\t0.46677500000000005\t0.21711612903225813\t-0.3798333333333335\t0.1072551724137932\n+1.1935923076923076\t-0.030315789473684192\t-0.4312054054054055\t0.2785972222222222\t0.22475714285714296\t-0.28865588235294115\t0.030763636363636326\n+1.268651351351351\t-0.17602499999999996\t-0.36551142857142843\t0.3631970588235294\t0.15118787878787884\t-0.30184374999999986\t0.1394258064516129\n+1.07070119047619\t0.0029481927710843375\t-0.04242682926829269\t0.16451604938271602\t-0.09436000000000007\t0.0848177215189873\t-0.041247435897435895\n+1.0061217391304347\t-0.00689090909090908\t-0.519847619047619\t0.34750000000000003\t0.3274526315789474\t-0.2984888888888888\t-0.2341411764705882\n+1.384726923076923\t0.6822879999999999\t0.40158333333333335\t0.5240260869565218\t0.27657272727272736\t-0.25318095238095234\t-0.270345\n+0.8908655172413792\t0.03222142857142858\t-0.30648888888888876\t-0.033376923076923075\t0.41872800000000004\t-0.13216666666666668\t-0.06907826086956516\n+1.2803099999999998\t0.13933793103448272\t0.09076071428571426\t-0.20384444444444447\t-0.4154423076923077\t-0.38409199999999977\t-0.25376666666666664\n+2.1052555555555554\t0.1436\t0.25185625\t-0.20522000000000004\t-0.3437071428571429\t0.1856076923076923\t0.9479416666666669\n+1.2939500000000002\t-0.1810461538461538\t-0.32946666666666663\t-0.14132727272727277\t0.009720000000000062\t-0.52128888888'..b'5538031249999998\t0.19567419354838714\t0.13947666666666655\t-0.010051724137931034\t-0.020057142857142864\t0.06804074074074072\t0.1191153846153846\n+0.6597321428571428\t0.20831111111111114\t0.21099230769230773\t0.08905999999999997\t0.026370833333333316\t0.04260869565217394\t0.09268636363636364\n+0.8055310344827585\t0.1853571428571428\t0.04282222222222224\t0.005623076923076902\t0.25551999999999997\t0.10817499999999998\t0.10491739130434782\n+0.6916965517241379\t0.2277535714285714\t-0.15200740740740742\t-0.08980384615384616\t0.17827199999999999\t0.22060833333333338\t0.10639565217391303\n+0.6458964285714285\t0.19743703703703705\t0.1922076923076923\t0.014923999999999944\t0.05652916666666665\t-0.012252173913043484\t0.0686227272727273\n+1.0690363636363638\t0.20934\t0.031466666666666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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out2.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out2.tsv Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,139 @@\n+CroCor_0\tCroCor_1\tCroCor_2\tCroCor_3\tCroCor_4\tCroCor_5\tCroCor_6\n+0.8795060606060603\t-0.08449999999999992\t-0.288858064516129\t0.042053333333333304\t0.4602827586206896\t-0.2472071428571427\t-0.22341481481481473\n+1.3072923076923075\t-0.01596666666666663\t-0.8552363636363634\t0.47940000000000016\t0.881111111111111\t-0.7545\t-0.6622857142857143\n+1.067375\t0.20328000000000002\t-0.32617142857142867\t0.2960615384615385\t0.4271333333333334\t-0.3241818181818182\t-0.23039999999999994\n+1.067375\t0.19728\t-0.3148857142857143\t0.2876000000000001\t0.4054666666666668\t-0.3241818181818182\t-0.20439999999999997\n+1.0655062499999999\t0.21097333333333335\t-0.3281428571428571\t0.24281538461538468\t0.46703333333333347\t-0.15281818181818183\t-0.22649999999999998\n+1.161125\t0.31423999999999996\t-0.18057142857142863\t0.28510769230769234\t0.3564666666666667\t-0.43916363636363637\t-0.24339999999999998\n+1.0977882352941173\t0.04930000000000001\t-0.29490666666666676\t0.18554285714285718\t0.658523076923077\t-0.31389999999999996\t-0.2557818181818183\n+1.134705882352941\t0.06775000000000002\t-0.4366666666666667\t0.26885714285714285\t0.657046153846154\t-0.292\t-0.4052363636363637\n+1.127741237113402\t-0.15122916666666672\t-0.0018694736842105749\t0.0048787234042553295\t0.05763333333333333\t-0.0038999999999999833\t-0.10195934065934066\n+0.3820692307692308\t-0.058033333333333326\t-0.005454545454545459\t-0.07862\t0.06544444444444447\t-0.160275\t-0.029714285714285717\n+1.9568399999999997\t-0.02258750000000002\t0.01406521739130443\t-0.018986363636363655\t-0.2288714285714286\t0.32322500000000004\t-0.2184315789473683\n+1.510758823529412\t-0.49684999999999996\t-0.3543333333333333\t0.448\t-0.4066923076923077\t-0.6197499999999999\t1.071090909090909\n+0.9799269230769231\t-0.057536000000000004\t-0.4542375\t0.18243478260869567\t0.26691818181818183\t-0.24609523809523814\t-0.24361999999999995\n+0.8490037037037036\t-0.050115384615384624\t-0.29912000000000005\t-0.14101666666666665\t0.46063478260869567\t-0.09202727272727276\t-0.06578095238095243\n+0.8335037037037037\t-0.08829230769230773\t-0.29777600000000004\t-0.02001666666666664\t0.43342608695652174\t-0.08835454545454548\t-0.11131428571428577\n+0.8942370370370369\t0.07759999999999997\t-0.16295999999999997\t0.05993333333333334\t0.5157391304347826\t0.10098181818181819\t-0.2394095238095238\n+0.9382333333333334\t-0.10223076923076922\t-0.30632000000000004\t-0.08289583333333332\t0.5684521739130435\t-0.060363636363636355\t-0.09812380952380947\n+0.9000624999999999\t0.1752869565217392\t0.16538181818181824\t0.20942380952380965\t0.69231\t0.21120000000000005\t0.0031388888888888846\n+1.5424153846153847\t-0.19912499999999997\t-0.8375272727272729\t0.082\t1.2625111111111111\t-0.21862499999999999\t-0.8468857142857142\n+1.4676028571428577\t-0.17619999999999994\t-0.41339393939393926\t0.46677500000000005\t0.21711612903225813\t-0.3798333333333335\t0.1072551724137932\n+1.1935923076923076\t-0.030315789473684192\t-0.4312054054054055\t0.2785972222222222\t0.22475714285714296\t-0.28865588235294115\t0.030763636363636326\n+1.268651351351351\t-0.17602499999999996\t-0.36551142857142843\t0.3631970588235294\t0.15118787878787884\t-0.30184374999999986\t0.1394258064516129\n+1.07070119047619\t0.0029481927710843375\t-0.04242682926829269\t0.16451604938271602\t-0.09436000000000007\t0.0848177215189873\t-0.041247435897435895\n+1.0061217391304347\t-0.00689090909090908\t-0.519847619047619\t0.34750000000000003\t0.3274526315789474\t-0.2984888888888888\t-0.2341411764705882\n+1.384726923076923\t0.6822879999999999\t0.40158333333333335\t0.5240260869565218\t0.27657272727272736\t-0.25318095238095234\t-0.270345\n+0.8908655172413792\t0.03222142857142858\t-0.30648888888888876\t-0.033376923076923075\t0.41872800000000004\t-0.13216666666666668\t-0.06907826086956516\n+1.2803099999999998\t0.13933793103448272\t0.09076071428571426\t-0.20384444444444447\t-0.4154423076923077\t-0.38409199999999977\t-0.25376666666666664\n+2.1052555555555554\t0.1436\t0.25185625\t-0.20522000000000004\t-0.3437071428571429\t0.1856076923076923\t0.9479416666666669\n+1.2939500000000002\t-0.1810461538461538\t-0.32946666666666663\t-0.14132727272727277\t0.009720000000000062\t-0.52128888888'..b'5538031249999998\t0.19567419354838714\t0.13947666666666655\t-0.010051724137931034\t-0.020057142857142864\t0.06804074074074072\t0.1191153846153846\n+0.6597321428571428\t0.20831111111111114\t0.21099230769230773\t0.08905999999999997\t0.026370833333333316\t0.04260869565217394\t0.09268636363636364\n+0.8055310344827585\t0.1853571428571428\t0.04282222222222224\t0.005623076923076902\t0.25551999999999997\t0.10817499999999998\t0.10491739130434782\n+0.6916965517241379\t0.2277535714285714\t-0.15200740740740742\t-0.08980384615384616\t0.17827199999999999\t0.22060833333333338\t0.10639565217391303\n+0.6458964285714285\t0.19743703703703705\t0.1922076923076923\t0.014923999999999944\t0.05652916666666665\t-0.012252173913043484\t0.0686227272727273\n+1.0690363636363638\t0.20934\t0.031466666666666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diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out3.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out3.tsv Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out4.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out4.tsv Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out5.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out5.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,139 @@
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out5.tsvOLD
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out5.tsvOLD Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out6.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/out6.tsv Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/test.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Descriptor/test-data/test.fasta Wed Oct 28 02:36:27 2020 +0000
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+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP64
+GLLSVLGSVVKHVIPHVVPVIAEHL
+>ACP66
+GLFKVLGSVAKHLLPHVAPVIAEK
+>ACP68
+GLFGVLGSIAKHVLPHVVPVIAEK
+>ACP70
+GLFVGVLAKVAAHVVPAIAEHF
+>ACP72
+GLFVGLAKVAAHNNPAIAEHFQA
+>ACP74
+GFVDFLKKVAGTIANVVT
+>ACP76
+GLLQTIKEKLESLESLAKGIVSGIQA
+>ACP78
+TRSSRAGLQFPVGRVHRLLRK
+>ACP80
+FFGWLIKGAIHAGKAIHGLIHRRRH
+>ACP82
+GLFDVIKKVASVIGGL
+>ACP84
+GLFDIIKKVASVVGGL
+>ACP86
+GRFKRFRKKFKKLFKKLSPVIPLLHLG
+>ACP88
+GGLRSLGRKILRAWKKYGPIIVPIIRIG
+>ACP90
+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP
+>ACP92
+GLLGPLLKIAAKVGSNLL
+>ACP94
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP96
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP98
+FFHHIFRGIVHVGKTIHRLVTG
+>ACP100
+KLAKLAKKLAKLAK
+>ACP102
+KTCENLADTFRGPCFATSNC
+>ACP104
+IDWKKLLDAAKQIL
+>ACP106
+FLIGMTQGLICLITRKC
+>ACP108
+ILPILSLIGGLLGK
+>ACP110
+GLLGLLGSVVSHVVPAIVGHF
+>ACP112
+GLLGLLGSVVSHVLPAITQHL
+>ACP114
+GIKCRFCCGCCTPGICGVCCRF
+>ACP116
+QSHLSLCRWCCNCCRSNKGC
+>ACP118
+ILGPVISTIGGVLGGLLKNL
+>ACP120
+FLPILASLAAKFGPKLFCLVTKKC
+>ACP122
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP124
+LLGMIPLAISAISALSKL
+>ACP126
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP128
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP130
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP132
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP134
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP136
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP138
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP140
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP142
+GFKDLLKGAAKALVKTVLF
+>ACP144
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP146
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP148
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP150
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP152
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP154
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP156
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP158
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP160
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP162
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP164
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP166
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP168
+VNWKKVLGKIIKVAK
+>ACP170
+VNWKKILGKIIKVAK
+>ACP172
+FFSLLPSLIGGLVSAIK
+>ACP174
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP176
+KWKLFKKIPKFLHLAKKF
+>ACP178
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
+>ACP180
+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP182
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP184
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP186
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP188
+FVDLKKIANIINSIFGK
+>ACP190
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP192
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP194
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP196
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP198
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP200
+GMWSKILGHLIR
+>ACP202
+GKWMSLLKHILK
+>ACP204
+GFGMALKLLKKVL
+>ACP206
+GTGLPMSERRKIMLMMR
+>ACP208
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP210
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP212
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP214
+GDACGETCFTGICFTAGCSCNPWPTCTRN
+>ACP216
+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP218
+IPCGESCVWIPCITAIAGCSCKNKVCYT
+>ACP220
+AIPCGESCVWIPCISTVIGCSCSNKVCYR
+>ACP222
+GEYCGESCYLIPCFTPGCYCVSRQCVNKN
+>ACP224
+IPCGESCVWIPCISGMFGCSCKDKVCYS
+>ACP226
+FLGWLFKWASK
+>ACP228
+FLKWLFKWAKK
+>ACP230
+KWKSFLKTFKSAKKTVLHTALKAISS
+>ACP232
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP234
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP236
+KWKLFKKIGAVLKVL
+>ACP238
+GACFSIAHECGA
+>ACP240
+TCCATGACGTTCCTGACGTT
+>ACP242
+KRFKQDGGASHASPASS
+>ACP244
+KRAKAAGGWSHWSPWSSC
+>ACP246
+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
+>ACP248
+FLGALFKVASKVLPSVKCAITKKC
+>ACP250
+GIGKFLKKAKKFGKAFVKILKK
+>ACP252
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP254
+VECYGPNRPQF
+>ACP256
+KRFKQDGGWSHWSPWSSC
+>ACP258
+RQVFQVAYIIIKA
+>ACP260
+KAFDITYVRLKF
+>ACP262
+DFKLFAVTIKYR
+>ACP264
+DFKLFAVYIKYR
+>ACP266
+WHSDMEWWYLLG
+>ACP268
+HTMYYHHYQHHL
+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/PDAUG_AA_Property_Based_Peptide_Generation.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/PDAUG_AA_Property_Based_Peptide_Generation.py Wed Oct 28 02:36:27 2020 +0000
[
b'@@ -0,0 +1,216 @@\n+from modlamp.sequences import *\n+import argparse, sys\n+import pandas as pd \n+import os\n+\n+def Random_seq(seq_num, lenmin_s, lenmax_s, S_proba, OutFasta):\n+\n+    b = Random(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    b.generate_sequences(proba=float(S_proba))\n+\n+    OutPep = b.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+def Helices_seq(seq_num, lenmin_s, lenmax_s, OutFasta):\n+\n+    h = Helices(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    h.generate_sequences()\n+\n+    OutPep = h.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+ \n+def Kinked_seq(seq_num, lenmin_s, lenmax_s, OutFasta):\n+\n+    k = Kinked(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    k.generate_sequences()\n+\n+    OutPep = k.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+\n+def Oblique_seq(seq_num, lenmin_s, lenmax_s, OutFasta):\n+\n+    o = Oblique(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    o.generate_sequences()\n+    o.sequences\n+\n+    OutPep = o.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+\n+def Centrosymmetric_seq(seq_num, lenmin_s, lenmax_s, symmetry_s, OutFasta):\n+\n+    s = Centrosymmetric(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    s.generate_sequences(symmetry=symmetry_s)\n+\n+    OutPep = s.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+\n+def HelicesACP_seq(seq_num, lenmin_s, lenmax_s, OutFasta):\n+\n+    helACP = HelicesACP(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    helACP.generate_sequences()\n+\n+    OutPep = helACP.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+\n+def Hepahelices_seq(seq_num, lenmin_s, lenmax_s, OutFasta):\n+\n+    h = Hepahelices(int(seq_num), int(lenmin_s),int(lenmax_s))  \n+    h.generate_sequences()\n+\n+    OutPep = h.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+\n+def AMPngrams_seq(seq_num, lenmin_s, lenmax_s, OutFasta):\n+\n+    s = AMPngrams(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    s.generate_sequences()\n+\n+    OutPep = s.sequences\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    for i,O in enumerate(OutPep):\n+        OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+        OutFasta.write(O+\'\\n\')\n+\n+def AmphipathicArc_seq(seq_num, lenmin_s, lenmax_s, gen_seq, hyd_gra, OutFasta):\n+\n+    amphi_hel = AmphipathicArc(int(seq_num), int(lenmin_s),int(lenmax_s))\n+    amphi_hel.generate_sequences(int(gen_seq))\n+    OutFasta = open(OutFasta, \'w\')\n+\n+    if hyd_gra == \'true\':\n+\n+        amphi_hel.make_H_gradient()\n+        OutPep = amphi_hel.sequences\n+                \n+        for i,O in enumerate(OutPep):\n+            OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+            OutFasta.write(O+\'\\n\')\n+\n+    elif hyd_gra == \'false\':\n+\n+        OutPep = amphi_hel.sequences\n+        \n+        for i,O in enumerate(OutPep):\n+            OutFasta.write(">sequence_"+str(i)+\'\\n\')\n+            OutFasta.write(O+\'\\n\')\n+\n+if __name__==\'__main__\':\n+\n+    parser = argparse.ArgumentParser(description=\'Deployment tool\')\n+    subparsers = parser.add_subparsers()\n+\n+    Ran = subparsers.add_parser(\'Random\')\n+    Ran.add_argument("-s","--seq_num", required=True, default=None, help="number of sequences to be generated")\n+    Ran.add_argument("-m","--lenmin_s", required=False, default=7, help="")\n+    Ran.add_ar'..b'Obl.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")\n+\n+    Cen = subparsers.add_parser(\'Centrosymmetric\')\n+    Cen.add_argument("-s","--seq_num", required=True, default=None, help="number of sequences to be generated")\n+    Cen.add_argument("-m","--lenmin_s", required=False, default=7, help="")\n+    Cen.add_argument("-M","--lenmax_s", required=False, default=20, help="Len max")\n+    Cen.add_argument("-S","--symmetry_s", required=False, default="asymmetric", help="symmetric,asymmetric")\n+    Cen.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")\n+\n+    Hel = subparsers.add_parser(\'HelicesACP\')\n+    Hel.add_argument("-s","--seq_num", required=True, default=None, help="number of sequences to be generated")\n+    Hel.add_argument("-m","--lenmin_s", required=False, default=7, help="")\n+    Hel.add_argument("-M","--lenmax_s", required=False, default=20, help="Len max")\n+    Hel.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")\n+\n+    Hep = subparsers.add_parser(\'Hepahelices\')\n+    Hep.add_argument("-s","--seq_num", required=True, default=None, help="number of sequences to be generated")\n+    Hep.add_argument("-m","--lenmin_s", required=False, default=7, help="")\n+    Hep.add_argument("-M","--lenmax_s", required=False, default=20, help="Len max")\n+    Hep.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")\n+\n+    AMP = subparsers.add_parser(\'AMPngrams\')\n+    AMP.add_argument("-s","--seq_num", required=True, default=None, help="number of sequences to be generated")\n+    AMP.add_argument("-m","--n_min", required=False, default=3, help="minimum number of ngrams to take for sequence assembly")\n+    AMP.add_argument("-M","--n_max", required=False, default=1, help="maximum number of ngrams to take for sequence assembly")\n+    AMP.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")\n+    \n+    Arc = subparsers.add_parser(\'AmphipathicArc\')\n+    Arc.add_argument("-s","--seq_num", required=True, default=None, help="number of sequences to be generated")\n+    Arc.add_argument("-m","--lenmin_s", required=False, default=7, help="")\n+    Arc.add_argument("-M","--lenmax_s", required=False, default=20, help="Len max")\n+    Arc.add_argument("-a","--arcsize", help="Choose among 100, 140, 180, 220, 260, or choose mixed to generate a mixture")\n+    Arc.add_argument("-y","--hyd_gra", default=\'False\', help="Method to mutate the generated sequences to have a hydrophobic gradient by substituting the last third of the sequence amino acids to hydrophobic.")\n+    Arc.add_argument("-O", "--OutFasta", required=True, default=None, help="Output Fasta")\n+\n+    args = parser.parse_args()\n+\n+    if sys.argv[1] == \'Random\':\n+        Random_seq(args.seq_num, args.lenmin_s, args.lenmax_s, args.S_proba, args.OutFasta)\n+    elif sys.argv[1] == \'Helices\':\n+        Helices_seq(args.seq_num, args.lenmin_s, args.lenmax_s, args.OutFasta)\n+    elif sys.argv[1] == \'Kinked\':\n+        Kinked_seq(args.seq_num, args.lenmin_s, args.lenmax_s, args.OutFasta)\n+    elif sys.argv[1] == \'Oblique\':\n+        Oblique_seq(args.seq_num, args.lenmin_s, args.lenmax_s, args.OutFasta)\n+    elif sys.argv[1] == \'Centrosymmetric\':\n+        Centrosymmetric_seq(args.seq_num, args.lenmin_s, args.lenmax_s, args.symmetry_s, args.OutFasta)\n+    elif sys.argv[1] == \'HelicesACP\':\n+        HelicesACP_seq(args.seq_num, args.lenmin_s, args.lenmax_s, args.OutFasta)\n+    elif sys.argv[1] == \'Hepahelices\':\n+        Hepahelices_seq(args.seq_num, args.lenmin_s, args.lenmax_s, args.OutFasta)\n+    elif sys.argv[1] == \'AMPngrams\':\n+        AMPngrams_seq(args.seq_num, args.n_min, args.n_max, args.OutFasta)\n+    elif sys.argv[1] == \'AmphipathicArc\':\n+        AmphipathicArc_seq(int(args.seq_num), int(args.lenmin_s), int(args.lenmax_s), int(args.arcsize), args.hyd_gra, args.OutFasta)\n+    else:\n+        print("You entered Wrong Values: ")\n\\ No newline at end of file\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out1.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,6 @@
+sequence_0
+HVLNSPPTMWRCCMDVYCY
+sequence_1
+MYHLHEHQKNQKHPKF
+sequence_2
+AEAFADKGELKRNQ
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out2.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out2.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+AGGKAGKLALKGGRLLAKI
+sequence_1
+IIAKGIRGALK
+sequence_2
+LVKAGRIL
+sequence_3
+AVKGVKIGAKAI
+sequence_4
+VGVKIVRIAVRLARA
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out3.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out3.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+AIRGGPG
+sequence_1
+KGVKVAIRILPLVVRLGRGGA
+sequence_2
+KAIPGAVKG
+sequence_3
+IGRGIPI
+sequence_4
+AIARIAPLIAK
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out4.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out4.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+GRGAKVVI
+sequence_1
+ALRVLKAAGRLARLAVI
+sequence_2
+LIRVGKLAVRALLAIA
+sequence_3
+ALIRVLRVAAKIAI
+sequence_4
+VIIKGGKLLVRGARAAIVV
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out5.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out5.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+VKIWIKVARVYVRAIKLYLKI
+sequence_1
+VKIWIKVAKVWVKAGRVFVRG
+sequence_2
+LRVWVRLVRAWARV
+sequence_3
+LRGFGRLVRAFARV
+sequence_4
+GRAWARGLKVYVKL
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out6.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out6.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+FIGDIAKKAAAVAGKLWC
+sequence_1
+GLFDVIKKIAKVLPASFVGL
+sequence_2
+VLPQIIGVAAGHMVKIIL
+sequence_3
+GLFKIALFVAKHVASTAAGLP
+sequence_4
+GLPSTILG
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out7.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out7.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+TARKKITRAL
+sequence_1
+GAKLIKTAKKKLSRALR
+sequence_2
+GRGLRTIKKKIQRIVK
+sequence_3
+AKIAKSAKKRANKLGRSGAK
+sequence_4
+IGRILKAARKRLTRVIR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out8.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out8.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+PRP
+sequence_1
+KAAGESC
+sequence_2
+GKAAGGLG
+sequence_3
+GGYYGGG
+sequence_4
+CGEIG
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out9.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AA_Property_Based_Peptide_Generation/test-data/Out9.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,10 @@
+sequence_0
+KVIRPIK
+sequence_1
+ALFRKLKRWVRSY
+sequence_2
+RWYKGYA
+sequence_3
+RLLQDVTAFLEHWWK
+sequence_4
+NLIKAFDK
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AddClassLabel/PDAUG_AddClassLabel.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AddClassLabel/PDAUG_AddClassLabel.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,17 @@
+import pandas as pd 
+import argparse
+
+parser = argparse.ArgumentParser()
+
+parser.add_argument("-I", "--InFile", required=True, default=None, help="Input data file")
+parser.add_argument("-C", "--ClassLabel", required=False, default=0, help="Class Label 0 or 1")
+parser.add_argument("-t", "--ClassLabelTitle", required=False, default='Class_label', help="Title to use for class label column (Class_label)")
+parser.add_argument("-O", "--OutFile", required=False, default='OutFile.tsv', help="Output file name")
+
+args = parser.parse_args()
+
+df1 = pd.read_csv(args.InFile, sep="\t")
+df2 = pd.DataFrame([args.ClassLabel]*df1.shape[0], columns=[args.ClassLabelTitle])
+
+df = pd.concat([df1, df2], axis=1)
+df.to_csv(args.OutFile, sep="\t", index=False)
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AddClassLabel/PDAUG_AddClassLabel.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AddClassLabel/PDAUG_AddClassLabel.xml Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,71 @@
+<tool id="pdaug_addclasslabel" name="PDAUG Add Class Label" version="0.1.0">
+  <description> Add class label to the training data set</description>
+
+  <requirements>
+    <requirement type="package" version="2.7.18">python</requirement>
+    <requirement type="package" version="0.24.2">pandas</requirement>
+  </requirements>
+
+
+  <stdio>
+    <exit_code range="1" level="fatal" />
+  </stdio>
+
+    <command detect_errors="exit_code"><![CDATA[
+        python '$__tool_directory__/PDAUG_AddClassLabel.py' -I '$input1' -C '$ClassLabel' -O '$OutFile1' -t '$ClassLabelTitle'
+    ]]></command>
+
+  <inputs>
+    <param name="input1" type="data" label="Input file" format="tabular"  multiple="true" argument= "--InFile" help="Input tabular data file."/>
+    <param name="ClassLabel" type='text' label="Class Label" value="0" argument="--ClassLabel" help="Class Label ex. 0 or 1"/>
+    <param name="ClassLabelTitle" label="Class Label Title"  type='text' value="Class_label" argument="--ClassLabelTitle" help="Name of the Column."/>
+  </inputs>
+
+  <outputs>
+    <data name='OutFile1' format='tabular' label="${tool.name} on $on_string - (tabular)" />
+  </outputs>
+
+  <tests>
+    <test>
+      <param name="input1" value="new.tsv"/>
+      <output name="OutFile1" file="out.tsv"/>
+    </test>
+  </tests>
+
+    <help><![CDATA[
+.. class:: infomark
+
+**What it does**
+
+This tool adds class labels to a dataframe.
+
+-----
+
+**Inputs**
+    * **--InFile** Takes input as Tabular data file.
+    * **--ClassLabel** Class label. 
+    * **--ClassLLabelTitle** Column name of class label. 
+
+-----
+
+**Outputs**
+    * **--OutFile** Returns a tabular file with the class labels.]]></help>
+
+
+<citations>
+  <citation type="bibtex">
+
+  @misc{PDAUGGITHUB, 
+    author = {Joshi, Jayadev  and Blankenberg, Daniel}, 
+    year = {2020}, 
+    title ={PDAUG - a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling}, 
+    publisher = {GitHub}, 
+    journal = {GitHub repository}, 
+    url =
+    {https://github.com/jaidevjoshi83/pdaug.git}, 
+
+}</citation>
+</citations>
+
+</tool>
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AddClassLabel/test-data/new.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AddClassLabel/test-data/new.tsv Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,13 @@\n+_ChargeC1\t_ChargeC2\t_ChargeC3\t_ChargeD1001\t_ChargeD1025\t_ChargeD1050\t_ChargeD1075\t_ChargeD1100\t_ChargeD2001\t_ChargeD2025\t_ChargeD2050\t_ChargeD2075\t_ChargeD2100\t_ChargeD3001\t_ChargeD3025\t_ChargeD3050\t_ChargeD3075\t_ChargeD3100\t_ChargeT12\t_ChargeT13\t_ChargeT23\t_HydrophobicityC1\t_HydrophobicityC2\t_HydrophobicityC3\t_HydrophobicityD1001\t_HydrophobicityD1025\t_HydrophobicityD1050\t_HydrophobicityD1075\t_HydrophobicityD1100\t_HydrophobicityD2001\t_HydrophobicityD2025\t_HydrophobicityD2050\t_HydrophobicityD2075\t_HydrophobicityD2100\t_HydrophobicityD3001\t_HydrophobicityD3025\t_HydrophobicityD3050\t_HydrophobicityD3075\t_HydrophobicityD3100\t_HydrophobicityT12\t_HydrophobicityT13\t_HydrophobicityT23\t_NormalizedVDWVC1\t_NormalizedVDWVC2\t_NormalizedVDWVC3\t_NormalizedVDWVD1001\t_NormalizedVDWVD1025\t_NormalizedVDWVD1050\t_NormalizedVDWVD1075\t_NormalizedVDWVD1100\t_NormalizedVDWVD2001\t_NormalizedVDWVD2025\t_NormalizedVDWVD2050\t_NormalizedVDWVD2075\t_NormalizedVDWVD2100\t_NormalizedVDWVD3001\t_NormalizedVDWVD3025\t_NormalizedVDWVD3050\t_NormalizedVDWVD3075\t_NormalizedVDWVD3100\t_NormalizedVDWVT12\t_NormalizedVDWVT13\t_NormalizedVDWVT23\t_PolarityC1\t_PolarityC2\t_PolarityC3\t_PolarityD1001\t_PolarityD1025\t_PolarityD1050\t_PolarityD1075\t_PolarityD1100\t_PolarityD2001\t_PolarityD2025\t_PolarityD2050\t_PolarityD2075\t_PolarityD2100\t_PolarityD3001\t_PolarityD3025\t_PolarityD3050\t_PolarityD3075\t_PolarityD3100\t_PolarityT12\t_PolarityT13\t_PolarityT23\t_PolarizabilityC1\t_PolarizabilityC2\t_PolarizabilityC3\t_PolarizabilityD1001\t_PolarizabilityD1025\t_PolarizabilityD1050\t_PolarizabilityD1075\t_PolarizabilityD1100\t_PolarizabilityD2001\t_PolarizabilityD2025\t_PolarizabilityD2050\t_PolarizabilityD2075\t_PolarizabilityD2100\t_PolarizabilityD3001\t_PolarizabilityD3025\t_PolarizabilityD3050\t_PolarizabilityD3075\t_PolarizabilityD3100\t_PolarizabilityT12\t_PolarizabilityT13\t_PolarizabilityT23\t_SecondaryStrC1\t_SecondaryStrC2\t_SecondaryStrC3\t_SecondaryStrD1001\t_SecondaryStrD1025\t_SecondaryStrD1050\t_SecondaryStrD1075\t_SecondaryStrD1100\t_SecondaryStrD2001\t_SecondaryStrD2025\t_SecondaryStrD2050\t_SecondaryStrD2075\t_SecondaryStrD2100\t_SecondaryStrD3001\t_SecondaryStrD3025\t_SecondaryStrD3050\t_SecondaryStrD3075\t_SecondaryStrD3100\t_SecondaryStrT12\t_SecondaryStrT13\t_SecondaryStrT23\t_SolventAccessibilityC1\t_SolventAccessibilityC2\t_SolventAccessibilityC3\t_SolventAccessibilityD1001\t_SolventAccessibilityD1025\t_SolventAccessibilityD1050\t_SolventAccessibilityD1075\t_SolventAccessibilityD1100\t_SolventAccessibilityD2001\t_SolventAccessibilityD2025\t_SolventAccessibilityD2050\t_SolventAccessibilityD2075\t_SolventAccessibilityD2100\t_SolventAccessibilityD3001\t_SolventAccessibilityD3025\t_SolventAccessibilityD3050\t_SolventAccessibilityD3075\t_SolventAccessibilityD3100\t_SolventAccessibilityT12\t_SolventAccessibilityT13\t_SolventAccessibilityT23\n+0.143\t0.786\t0.071\t50.0\t57.143\t50.0\t50.0\t57.143\t7.143\t14.286\t42.857\t78.571\t100.0\t28.571\t28.571\t28.571\t28.571\t28.571\t0.154\t0.0\t0.154\t0.214\t0.286\t0.5\t28.571\t57.143\t28.571\t50.0\t57.143\t7.143\t7.143\t78.571\t85.714\t100.0\t14.286\t14.286\t35.714\t64.286\t92.857\t0.0\t0.308\t0.308\t0.357\t0.429\t0.214\t7.143\t7.143\t28.571\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.857\t21.429\t57.143\t21.429\t50.0\t57.143\t0.385\t0.077\t0.231\t0.5\t0.0\t0.143\t14.286\t14.286\t35.714\t64.286\t92.857\t0\t0\t0\t0\t0\t50.0\t57.143\t50.0\t50.0\t57.143\t0.0\t0.154\t0.0\t0.357\t0.429\t0.214\t7.143\t7.143\t28.571\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.857\t21.429\t57.143\t21.429\t50.0\t57.143\t0.385\t0.077\t0.231\t0.357\t0.357\t0.286\t14.286\t14.286\t50.0\t57.143\t92.857\t21.429\t21.429\t35.714\t42.857\t71.429\t7.143\t7.143\t28.571\t78.571\t100.0\t0.231\t0.231\t0.231\t0.786\t0.214\t0.0\t7.143\t14.286\t42.857\t78.571\t100.0\t28.571\t57.143\t28.571\t50.0\t57.143\t0\t0\t0\t0\t0\t0.308\t0.0\t0.0\n+0.5\t0.5\t0.0\t8.333\t8.333\t58.333\t66.667\t100.0\t16.667\t16.667\t41.667\t50.0\t91.667\t0.0\t0.0\t0.0\t0.0\t0.0\t0.545\t0.0\t0.0\t0.5\t0.0\t0.5\t8.333\t8.333\t58.333\t66.667\t100.0\t0.0\t0.0\t0.0\t0.0\t0.0\t16.667\t16.667\t41.667\t50.0\t91.667\t0.0\t0.545\t0.0\t0.0\t0.5\t0.5\t0.0\t0.0\t0.0\t0.0\t0.0\t16.667\t16.667\t41.667\t50.0\t91.667\t8.333\t8.333\t58.333\t66.667\t100.0\t0.0\t0.0\t0'..b'\t57.143\t28.571\t50.0\t57.143\t7.143\t7.143\t78.571\t85.714\t100.0\t14.286\t14.286\t35.714\t64.286\t92.857\t0.0\t0.308\t0.308\t0.357\t0.429\t0.214\t7.143\t7.143\t28.571\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.857\t21.429\t57.143\t21.429\t50.0\t57.143\t0.385\t0.077\t0.231\t0.5\t0.0\t0.143\t14.286\t14.286\t35.714\t64.286\t92.857\t0\t0\t0\t0\t0\t50.0\t57.143\t50.0\t50.0\t57.143\t0.0\t0.154\t0.0\t0.357\t0.429\t0.214\t7.143\t7.143\t28.571\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.857\t21.429\t57.143\t21.429\t50.0\t57.143\t0.385\t0.077\t0.231\t0.357\t0.357\t0.286\t14.286\t14.286\t50.0\t57.143\t92.857\t21.429\t21.42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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_AddClassLabel/test-data/out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_AddClassLabel/test-data/out.tsv Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,13 @@\n+_ChargeC1\t_ChargeC2\t_ChargeC3\t_ChargeD1001\t_ChargeD1025\t_ChargeD1050\t_ChargeD1075\t_ChargeD1100\t_ChargeD2001\t_ChargeD2025\t_ChargeD2050\t_ChargeD2075\t_ChargeD2100\t_ChargeD3001\t_ChargeD3025\t_ChargeD3050\t_ChargeD3075\t_ChargeD3100\t_ChargeT12\t_ChargeT13\t_ChargeT23\t_HydrophobicityC1\t_HydrophobicityC2\t_HydrophobicityC3\t_HydrophobicityD1001\t_HydrophobicityD1025\t_HydrophobicityD1050\t_HydrophobicityD1075\t_HydrophobicityD1100\t_HydrophobicityD2001\t_HydrophobicityD2025\t_HydrophobicityD2050\t_HydrophobicityD2075\t_HydrophobicityD2100\t_HydrophobicityD3001\t_HydrophobicityD3025\t_HydrophobicityD3050\t_HydrophobicityD3075\t_HydrophobicityD3100\t_HydrophobicityT12\t_HydrophobicityT13\t_HydrophobicityT23\t_NormalizedVDWVC1\t_NormalizedVDWVC2\t_NormalizedVDWVC3\t_NormalizedVDWVD1001\t_NormalizedVDWVD1025\t_NormalizedVDWVD1050\t_NormalizedVDWVD1075\t_NormalizedVDWVD1100\t_NormalizedVDWVD2001\t_NormalizedVDWVD2025\t_NormalizedVDWVD2050\t_NormalizedVDWVD2075\t_NormalizedVDWVD2100\t_NormalizedVDWVD3001\t_NormalizedVDWVD3025\t_NormalizedVDWVD3050\t_NormalizedVDWVD3075\t_NormalizedVDWVD3100\t_NormalizedVDWVT12\t_NormalizedVDWVT13\t_NormalizedVDWVT23\t_PolarityC1\t_PolarityC2\t_PolarityC3\t_PolarityD1001\t_PolarityD1025\t_PolarityD1050\t_PolarityD1075\t_PolarityD1100\t_PolarityD2001\t_PolarityD2025\t_PolarityD2050\t_PolarityD2075\t_PolarityD2100\t_PolarityD3001\t_PolarityD3025\t_PolarityD3050\t_PolarityD3075\t_PolarityD3100\t_PolarityT12\t_PolarityT13\t_PolarityT23\t_PolarizabilityC1\t_PolarizabilityC2\t_PolarizabilityC3\t_PolarizabilityD1001\t_PolarizabilityD1025\t_PolarizabilityD1050\t_PolarizabilityD1075\t_PolarizabilityD1100\t_PolarizabilityD2001\t_PolarizabilityD2025\t_PolarizabilityD2050\t_PolarizabilityD2075\t_PolarizabilityD2100\t_PolarizabilityD3001\t_PolarizabilityD3025\t_PolarizabilityD3050\t_PolarizabilityD3075\t_PolarizabilityD3100\t_PolarizabilityT12\t_PolarizabilityT13\t_PolarizabilityT23\t_SecondaryStrC1\t_SecondaryStrC2\t_SecondaryStrC3\t_SecondaryStrD1001\t_SecondaryStrD1025\t_SecondaryStrD1050\t_SecondaryStrD1075\t_SecondaryStrD1100\t_SecondaryStrD2001\t_SecondaryStrD2025\t_SecondaryStrD2050\t_SecondaryStrD2075\t_SecondaryStrD2100\t_SecondaryStrD3001\t_SecondaryStrD3025\t_SecondaryStrD3050\t_SecondaryStrD3075\t_SecondaryStrD3100\t_SecondaryStrT12\t_SecondaryStrT13\t_SecondaryStrT23\t_SolventAccessibilityC1\t_SolventAccessibilityC2\t_SolventAccessibilityC3\t_SolventAccessibilityD1001\t_SolventAccessibilityD1025\t_SolventAccessibilityD1050\t_SolventAccessibilityD1075\t_SolventAccessibilityD1100\t_SolventAccessibilityD2001\t_SolventAccessibilityD2025\t_SolventAccessibilityD2050\t_SolventAccessibilityD2075\t_SolventAccessibilityD2100\t_SolventAccessibilityD3001\t_SolventAccessibilityD3025\t_SolventAccessibilityD3050\t_SolventAccessibilityD3075\t_SolventAccessibilityD3100\t_SolventAccessibilityT12\t_SolventAccessibilityT13\t_SolventAccessibilityT23\tClass_label\n+0.14300000000000002\t0.7859999999999999\t0.071\t50.0\t57.143\t50.0\t50.0\t57.143\t7.143\t14.286\t42.857\t78.571\t100.0\t28.570999999999998\t28.570999999999998\t28.570999999999998\t28.570999999999998\t28.570999999999998\t0.154\t0.0\t0.154\t0.214\t0.28600000000000003\t0.5\t28.570999999999998\t57.143\t28.570999999999998\t50.0\t57.143\t7.143\t7.143\t78.571\t85.714\t100.0\t14.286\t14.286\t35.714\t64.286\t92.85700000000001\t0.0\t0.308\t0.308\t0.35700000000000004\t0.429\t0.214\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.85700000000001\t21.429000000000002\t57.143\t21.429000000000002\t50.0\t57.143\t0.385\t0.077\t0.231\t0.5\t0.0\t0.14300000000000002\t14.286\t14.286\t35.714\t64.286\t92.85700000000001\t0\t0\t0\t0\t0\t50.0\t57.143\t50.0\t50.0\t57.143\t0.0\t0.154\t0.0\t0.35700000000000004\t0.429\t0.214\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.85700000000001\t21.429000000000002\t57.143\t21.429000000000002\t50.0\t57.143\t0.385\t0.077\t0.231\t0.35700000000000004\t0.35700000000000004\t0.28600000000000003\t14.286\t14.286\t50.0\t57.143\t92.85700000000001\t21.429000000000002\t21.429000000000002\t35.714\t42.857\t71.429\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t0.231\t0.231\t0.231\t0.7859999999999999\t0.214\t0.0\t7.143\t14.286\t42.857\t78'..b'\t92.85700000000001\t0\t0\t0\t0\t0\t50.0\t57.143\t50.0\t50.0\t57.143\t0.0\t0.154\t0.0\t0.35700000000000004\t0.429\t0.214\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.85700000000001\t21.429000000000002\t57.143\t21.429000000000002\t50.0\t57.143\t0.385\t0.077\t0.231\t0.35700000000000004\t0.35700000000000004\t0.28600000000000003\t14.286\t14.286\t50.0\t57.143\t92.85700000000001\t21.429000000000002\t21.429000000000002\t35.714\t42.857\t71.429\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t0.231\t0.231\t0.231\t0.7859999999999999\t0.214\t0.0\t7.143\t14.286\t42.857\t78.571\t100.0\t28.570999999999998\t57.143\t28.570999999999998\t50.0\t57.143\t0\t0\t0\t0\t0\t0.308\t0.0\t0.0\t0\n+0.5\t0.5\t0.0\t8.333\t8.333\t58.333\t66.667\t100.0\t16.667\t16.667\t41.667\t50.0\t91.667\t0.0\t0.0\t0.0\t0.0\t0.0\t0.545\t0.0\t0.0\t0.5\t0.0\t0.5\t8.333\t8.333\t58.333\t66.667\t100.0\t0.0\t0.0\t0.0\t0.0\t0.0\t16.667\t16.667\t41.667\t50.0\t91.667\t0.0\t0.545\t0.0\t0.0\t0.5\t0.5\t0.0\t0.0\t0.0\t0.0\t0.0\t16.667\t16.667\t41.667\t50.0\t91.667\t8.333\t8.333\t58.333\t66.667\t100.0\t0.0\t0.0\t0.545\t0.5\t0.0\t0.5\t16.667\t16.667\t41.667\t50.0\t91.667\t0\t0\t0\t0\t0\t8.333\t8.333\t58.333\t66.667\t100.0\t0.0\t0.545\t0.0\t0.0\t0.5\t0.5\t0.0\t0.0\t0.0\t0.0\t0.0\t16.667\t16.667\t41.667\t50.0\t91.667\t8.333\t8.333\t58.333\t66.667\t100.0\t0.0\t0.0\t0.545\t1.0\t0.0\t0.0\t8.333\t25.0\t50.0\t75.0\t100.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.5\t0.5\t0.0\t16.667\t16.667\t41.667\t50.0\t91.667\t8.333\t8.333\t58.333\t66.667\t100.0\t0\t0\t0\t0\t0\t0.545\t0.0\t0.0\t0\n+0.33299999999999996\t0.667\t0.0\t11.110999999999999\t100.0\t11.110999999999999\t66.667\t100.0\t22.221999999999998\t22.221999999999998\t44.443999999999996\t55.556000000000004\t88.889\t0.0\t0.0\t0.0\t0.0\t0.0\t0.5\t0.0\t0.0\t0.33299999999999996\t0.0\t0.667\t11.110999999999999\t100.0\t11.110999999999999\t66.667\t100.0\t0.0\t0.0\t0.0\t0.0\t0.0\t22.221999999999998\t22.221999999999998\t44.443999999999996\t55.556000000000004\t88.889\t0.0\t0.5\t0.0\t0.0\t0.667\t0.33299999999999996\t0.0\t0.0\t0.0\t0.0\t0.0\t22.221999999999998\t22.221999999999998\t44.443999999999996\t55.556000000000004\t88.889\t11.110999999999999\t100.0\t11.110999999999999\t66.667\t100.0\t0.0\t0.0\t0.5\t0.667\t0.0\t0.33299999999999996\t22.221999999999998\t22.221999999999998\t44.443999999999996\t55.556000000000004\t88.889\t0\t0\t0\t0\t0\t11.110999999999999\t100.0\t11.110999999999999\t66.667\t100.0\t0.0\t0.5\t0.0\t0.0\t0.667\t0.33299999999999996\t0.0\t0.0\t0.0\t0.0\t0.0\t22.221999999999998\t22.221999999999998\t44.443999999999996\t55.556000000000004\t88.889\t11.110999999999999\t100.0\t11.110999999999999\t66.667\t100.0\t0.0\t0.0\t0.5\t1.0\t0.0\t0.0\t11.110999999999999\t22.221999999999998\t44.443999999999996\t66.667\t100.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.0\t0.667\t0.33299999999999996\t0.0\t22.221999999999998\t22.221999999999998\t44.443999999999996\t55.556000000000004\t88.889\t11.110999999999999\t100.0\t11.110999999999999\t66.667\t100.0\t0\t0\t0\t0\t0\t0.5\t0.0\t0.0\t0\n+0.14300000000000002\t0.7859999999999999\t0.071\t50.0\t57.143\t50.0\t50.0\t57.143\t7.143\t14.286\t42.857\t78.571\t100.0\t28.570999999999998\t28.570999999999998\t28.570999999999998\t28.570999999999998\t28.570999999999998\t0.154\t0.0\t0.154\t0.214\t0.28600000000000003\t0.5\t28.570999999999998\t57.143\t28.570999999999998\t50.0\t57.143\t7.143\t7.143\t78.571\t85.714\t100.0\t14.286\t14.286\t35.714\t64.286\t92.85700000000001\t0.0\t0.308\t0.308\t0.35700000000000004\t0.429\t0.214\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.85700000000001\t21.429000000000002\t57.143\t21.429000000000002\t50.0\t57.143\t0.385\t0.077\t0.231\t0.5\t0.0\t0.14300000000000002\t14.286\t14.286\t35.714\t64.286\t92.85700000000001\t0\t0\t0\t0\t0\t50.0\t57.143\t50.0\t50.0\t57.143\t0.0\t0.154\t0.0\t0.35700000000000004\t0.429\t0.214\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t14.286\t14.286\t42.857\t64.286\t92.85700000000001\t21.429000000000002\t57.143\t21.429000000000002\t50.0\t57.143\t0.385\t0.077\t0.231\t0.35700000000000004\t0.35700000000000004\t0.28600000000000003\t14.286\t14.286\t50.0\t57.143\t92.85700000000001\t21.429000000000002\t21.429000000000002\t35.714\t42.857\t71.429\t7.143\t7.143\t28.570999999999998\t78.571\t100.0\t0.231\t0.231\t0.231\t0.7859999999999999\t0.214\t0.0\t7.143\t14.286\t42.857\t78.571\t100.0\t28.570999999999998\t57.143\t28.570999999999998\t50.0\t57.143\t0\t0\t0\t0\t0\t0.308\t0.0\t0.0\t0\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/PDAUG_Basic_Plots.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/PDAUG_Basic_Plots.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,185 @@
+from wordcloud import WordCloud, STOPWORDS 
+import matplotlib.pyplot as plt 
+import glob, os, sys
+import pandas as pd 
+import plotly.express as px
+###################################
+from wordcloud import WordCloud, STOPWORDS 
+import matplotlib.pyplot as plt 
+
+
+def ReturnPeptide(Infile):
+
+    file = open(Infile)
+    lines = file.readlines()
+
+    Index = []
+    Pep = []
+
+    for line in lines:
+        if '>' in line:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Index.append(line.strip('\n'))
+        else:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Pep.append(line)
+    return Pep, Index
+
+
+def FragReturn(Seq, d):
+
+    tokens = []
+    for seq in Seq: 
+
+        for l in range(d):
+            if l < d:
+                for x in range(int(len(seq)/d)):
+                    s = (x*d)+l
+                    e = s+d
+                    if len(seq[s:e]) == d:
+                        tokens.append(seq[s:e])
+          
+                    else:
+                        pass
+            else:
+                pass
+    return tokens
+
+def PlotWordCloud(TokenList, OutFile):
+
+    comment_words = '' 
+    stopwords = set(STOPWORDS) 
+    comment_words += " ".join(TokenList)+" "
+      
+    wordcloud = WordCloud(width = 800, height = 800, 
+                    background_color ='white', 
+                    stopwords = stopwords, 
+                    min_font_size = 10).generate(comment_words) 
+                       
+    plt.figure(figsize = (8, 8), facecolor = None) 
+    plt.imshow(wordcloud) 
+    plt.axis("off") 
+    plt.tight_layout(pad = 0) 
+    plt.savefig(OutFile,dpi=600)
+
+
+def HeatMapPlot(Infile,  IndexColumn, x_label, y_label,  Workdirpath, htmlOutDir, htmlFname):
+
+    if not os.path.exists(htmlOutDir):
+        os.makedirs(htmlOutDir)
+
+    df  = pd.read_csv(Infile, sep="\t")
+    y_ticks = list(df[IndexColumn])
+
+    fig = px.imshow(df[df.columns.tolist()[1:]], labels=dict(x=x_label, y=y_label), y=y_ticks)
+    fig.update_xaxes(side="top")
+
+    fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname))
+
+
+def BoxPlot(InFile, Feature, label,  Workdirpath, htmlOutDir, htmlFname):
+
+    Workdirpath = os.path.join(os.getcwd(),'report_dir')
+
+    if not os.path.exists(htmlOutDir):
+        os.makedirs(htmlOutDir)
+
+    df  = pd.read_csv(InFile, sep="\t")
+    fig = px.box(df, y=Feature, color=label, notched=True, title="Box plot of "+Feature )
+    fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname))
+
+
+def ScatterPlot(InFile, Feature1, Feature2, Feature3, Label, PlotType, Workdirpath, htmlOutDir, htmlFname):
+
+    Workdirpath = os.path.join(os.getcwd(),'report_dir')
+
+    if not os.path.exists(htmlOutDir):
+        os.makedirs(htmlOutDir)
+
+    df  = pd.read_csv(InFile, sep="\t")
+
+
+    if PlotType == "3D":
+        fig = px.scatter_3d(df, x=Feature1, y=Feature2, z=Feature3, color=Label)
+        fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname))
+
+    elif PlotType == "2D":
+        fig = px.scatter(df, x=Feature1, y=Feature2, color=Label)
+        fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname))
+
+
+def WordCloudPlot(InFile, d, Workdirpath, htmlOutDir, htmlFname):
+
+    Workdirpath = os.path.join(os.getcwd(),'report_dir')
+    if not os.path.exists(htmlOutDir):
+        os.makedirs(htmlOutDir)
+
+    Peps,_ = ReturnPeptide(InFile)
+    Frags = FragReturn(Peps, int(d))
+
+    PlotWordCloud(Frags, "out.png")
+    #HTML_Gen(os.path.join(Workdirpath, htmlOutDir, htmlFname))
+
+
+if __name__=="__main__":
+
+
+    import argparse
+
+    parser = argparse.ArgumentParser(description='Deployment tool')
+    subparsers = parser.add_subparsers()
+
+    HM = subparsers.add_parser('HeatMap')
+    HM.add_argument("-I", "--InFile", required=True, default=None, help="Path to target tsv file")
+    HM.add_argument("-C",  "--IndexColumn", required=True, help="")
+    HM.add_argument("-x", "--x_label", required=True, help="")
+    HM.add_argument("-y","--y_label", required=True, help="")
+    HM.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="Path to html directory")
+    HM.add_argument("--htmlFname", required=False, help="HTML out file", default="report.html")
+    HM.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Path to working directory")
+
+    BP = subparsers.add_parser('BoxPlot')
+    BP.add_argument("-I", "--InFile", required=True, default=None, help="Input file")
+    BP.add_argument("-F", "--Feature", required=True, default=None, help="Feature list")
+    BP.add_argument("-O", "--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'),  help="Path to html dir")
+    BP.add_argument("-Hf", "--htmlFname", required=False, help="HTML out file", default="report.html")
+    BP.add_argument("-Wp", "--Workdirpath", required=False, default=os.getcwd(), help="Path to Working Directory")
+    BP.add_argument("-L", "--Label", required=False, default=False, help="Working Directory Path")
+    
+    SP = subparsers.add_parser('ScatterPlot')
+    SP.add_argument("-I", "--InFile", required=True, default=None, help="Path to target tsv file")
+    SP.add_argument("-F1", "--Feature1", required=True, default=True, help="Path to target tsv file")   
+    SP.add_argument("-F2", "--Feature2", required=True, default=True, help="Roatate ticks")
+    SP.add_argument("-F3", "--Feature3", required=False,  help="Roatate ticks")
+    SP.add_argument("-O","--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'),  help="HTML Out Dir")
+    SP.add_argument("-Hf","--htmlFname", required=False, help="HTML out file", default="jai.html")
+    SP.add_argument("-Wp","--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
+    SP.add_argument("-T", "--PlotType", required=True,  help="")
+    SP.add_argument("-L","--Label", required=False, default=False, help="Working Directory Path")
+
+    WC = subparsers.add_parser('WordCloud')
+    WC.add_argument("-I", "--InFile", required=True, default=None, help="Path to target tsv file")
+    WC.add_argument("-D", "--FragSize", required=True, default=None, help="Path to target tsv file")
+    WC.add_argument("-O","--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'),  help="HTML Out Dir")
+    WC.add_argument("-Hf","--htmlFname", required=False, help="HTML out file", default="report.html")
+    WC.add_argument("-Wp","--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
+
+
+    args = parser.parse_args()
+
+    if sys.argv[1] == "HeatMap":
+        HeatMapPlot(args.InFile,  args.IndexColumn, args.x_label, args.y_label, args.Workdirpath, args.htmlOutDir, args.htmlFname)
+                    
+    elif sys.argv[1] == "ScatterPlot":
+        ScatterPlot(args.InFile, args.Feature1, args.Feature2, args.Feature3, args.Label, args.PlotType, args.Workdirpath,  args.htmlOutDir, args.htmlFname)
+
+    elif sys.argv[1] == "BoxPlot":
+        BoxPlot(args.InFile, args.Feature, args.Label,  args.Workdirpath,  args.htmlOutDir, args.htmlFname)
+
+    elif sys.argv[1] == "WordCloud":
+        WordCloudPlot(args.InFile, args.FragSize, args.Workdirpath,  args.htmlOutDir, args.htmlFname)   
+
+    else:
+        print("In Correct Option:")
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/positive.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/positive.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLFDIIKKIAESI
+>ACP4
+GLLDIVKKVVGAFGSL
+>ACP6
+GLFDIVKKVVGALGSL
+>ACP8
+GLFDIVKKVVGTLAGL
+>ACP10
+GLFDIAKKVIGVIGSL
+>ACP12
+GLFDIVKKIAGHIAGSI
+>ACP14
+GLFDIVKKIAGHIVSSI
+>ACP16
+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF
+>ACP18
+HGVSGHGQHGVHG
+>ACP20
+FKCRRWQWRMKKLGAPSITCVRRAF
+>ACP22
+KWKLFKKIKFLHSAKKF
+>ACP24
+KSSAYSLQMGATAIKQVKKLFKKWGW
+>ACP26
+GIGTKILGGVKTALKGALKELASTYAN
+>ACP28
+GIGGKILSGLKTALKGAAKELASTYLH
+>ACP30
+GIGGVLLSAGKAALKGLAKVLAEKYAN
+>ACP32
+SIGAKILGGVKTFFKGALKELASTYLQ
+>ACP34
+FLPLLAGLAANFLPTIICKISYKC
+>ACP36
+FVQWFSKFLGRIL
+>ACP38
+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL
+>ACP40
+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK
+>ACP42
+KWKLFKKIEKVGQNIRDGIIKAGPAVAVVGQATQIAK
+>ACP44
+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK
+>ACP46
+GIGKFLHSAKKFGKAFVGEIMNS
+>ACP48
+GIGAVLKVLTTGLPALISWIKRKRQQ
+>ACP50
+ALWKNMLKGIGKLAGQAALGAVKTLVGAE
+>ACP52
+ACYCRIPACIAGERRYGTCIYQGRLWAFCC
+>ACP54
+ECRRLCYKQRCVTYCRGR
+>ACP56
+LKLKSIVSWAKKVL
+>ACP58
+KWCFRVCYRGICYRRCR
+>ACP60
+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK
+>ACP62
+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP64
+GLLSVLGSVVKHVIPHVVPVIAEHL
+>ACP66
+GLFKVLGSVAKHLLPHVAPVIAEK
+>ACP68
+GLFGVLGSIAKHVLPHVVPVIAEK
+>ACP70
+GLFVGVLAKVAAHVVPAIAEHF
+>ACP72
+GLFVGLAKVAAHNNPAIAEHFQA
+>ACP74
+GFVDFLKKVAGTIANVVT
+>ACP76
+GLLQTIKEKLESLESLAKGIVSGIQA
+>ACP78
+TRSSRAGLQFPVGRVHRLLRK
+>ACP80
+FFGWLIKGAIHAGKAIHGLIHRRRH
+>ACP82
+GLFDVIKKVASVIGGL
+>ACP84
+GLFDIIKKVASVVGGL
+>ACP86
+GRFKRFRKKFKKLFKKLSPVIPLLHLG
+>ACP88
+GGLRSLGRKILRAWKKYGPIIVPIIRIG
+>ACP90
+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP
+>ACP92
+GLLGPLLKIAAKVGSNLL
+>ACP94
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP96
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP98
+FFHHIFRGIVHVGKTIHRLVTG
+>ACP100
+KLAKLAKKLAKLAK
+>ACP102
+KTCENLADTFRGPCFATSNC
+>ACP104
+IDWKKLLDAAKQIL
+>ACP106
+FLIGMTQGLICLITRKC
+>ACP108
+ILPILSLIGGLLGK
+>ACP110
+GLLGLLGSVVSHVVPAIVGHF
+>ACP112
+GLLGLLGSVVSHVLPAITQHL
+>ACP114
+GIKCRFCCGCCTPGICGVCCRF
+>ACP116
+QSHLSLCRWCCNCCRSNKGC
+>ACP118
+ILGPVISTIGGVLGGLLKNL
+>ACP120
+FLPILASLAAKFGPKLFCLVTKKC
+>ACP122
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP124
+LLGMIPLAISAISALSKL
+>ACP126
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP128
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP130
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP132
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP134
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP136
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP138
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP140
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP142
+GFKDLLKGAAKALVKTVLF
+>ACP144
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP146
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP148
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP150
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP152
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP154
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP156
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP158
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP160
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP162
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP164
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP166
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP168
+VNWKKVLGKIIKVAK
+>ACP170
+VNWKKILGKIIKVAK
+>ACP172
+FFSLLPSLIGGLVSAIK
+>ACP174
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP176
+KWKLFKKIPKFLHLAKKF
+>ACP178
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
+>ACP180
+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP182
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP184
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP186
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP188
+FVDLKKIANIINSIFGK
+>ACP190
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP192
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP194
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP196
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP198
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP200
+GMWSKILGHLIR
+>ACP202
+GKWMSLLKHILK
+>ACP204
+GFGMALKLLKKVL
+>ACP206
+GTGLPMSERRKIMLMMR
+>ACP208
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP210
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP212
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP214
+GDACGETCFTGICFTAGCSCNPWPTCTRN
+>ACP216
+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP218
+IPCGESCVWIPCITAIAGCSCKNKVCYT
+>ACP220
+AIPCGESCVWIPCISTVIGCSCSNKVCYR
+>ACP222
+GEYCGESCYLIPCFTPGCYCVSRQCVNKN
+>ACP224
+IPCGESCVWIPCISGMFGCSCKDKVCYS
+>ACP226
+FLGWLFKWASK
+>ACP228
+FLKWLFKWAKK
+>ACP230
+KWKSFLKTFKSAKKTVLHTALKAISS
+>ACP232
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP234
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP236
+KWKLFKKIGAVLKVL
+>ACP238
+GACFSIAHECGA
+>ACP240
+TCCATGACGTTCCTGACGTT
+>ACP242
+KRFKQDGGASHASPASS
+>ACP244
+KRAKAAGGWSHWSPWSSC
+>ACP246
+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
+>ACP248
+FLGALFKVASKVLPSVKCAITKKC
+>ACP250
+GIGKFLKKAKKFGKAFVKILKK
+>ACP252
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP254
+VECYGPNRPQF
+>ACP256
+KRFKQDGGWSHWSPWSSC
+>ACP258
+RQVFQVAYIIIKA
+>ACP260
+KAFDITYVRLKF
+>ACP262
+DFKLFAVTIKYR
+>ACP264
+DFKLFAVYIKYR
+>ACP266
+WHSDMEWWYLLG
+>ACP268
+HTMYYHHYQHHL
+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test1.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,9 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.7809999999999999 0.608 0.537 0.608
+SGDC 0.5 0.35 0.5 0.33399999999999996 0.608
+DTC 0.608 0.7809999999999999 0.608 0.537 0.608
+GBC 0.608 0.7809999999999999 0.608 0.537 0.608
+RFC 0.5 0.25 0.5 0.33299999999999996 0.5
+LRC 0.608 0.7809999999999999 0.608 0.537 0.608
+KNC 0.5 0.25 0.5 0.33299999999999996 0.608
+GNBC 0.608 0.7809999999999999 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test1/report_dir/report.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test1/report_dir/report.html Wed Oct 28 02:36:27 2020 +0000
[
b'@@ -0,0 +1,67 @@\n+<html>\n+<head><meta charset="utf-8" /></head>\n+<body>\n+    <div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: \'local\'};</script>\n+        <script type="text/javascript">/**\n+* plotly.js v1.55.2\n+* Copyright 2012-2020, Plotly, Inc.\n+* All rights reserved.\n+* Licensed under the MIT license\n+*/\n+!function(t){if("object"==typeof exports&&"undefined"!=typeof module)module.exports=t();else if("function"==typeof define&&define.amd)define([],t);else{("undefined"!=typeof window?window:"undefined"!=typeof global?global:"undefined"!=typeof self?self:this).Plotly=t()}}((function(){return function t(e,r,n){function a(o,s){if(!r[o]){if(!e[o]){var l="function"==typeof require&&require;if(!s&&l)return l(o,!0);if(i)return i(o,!0);var c=new Error("Cannot find module \'"+o+"\'");throw c.code="MODULE_NOT_FOUND",c}var u=r[o]={exports:{}};e[o][0].call(u.exports,(function(t){return a(e[o][1][t]||t)}),u,u.exports,t,e,r,n)}return r[o].exports}for(var i="function"==typeof require&&require,o=0;o<n.length;o++)a(n[o]);return a}({1:[function(t,e,r){"use strict";var n=t("../src/lib"),a={"X,X div":"direction:ltr;font-family:\'Open Sans\', verdana, arial, sans-serif;margin:0;padding:0;","X input,X button":"font-family:\'Open Sans\', verdana, arial, sans-serif;","X input:focus,X button:focus":"outline:none;","X a":"text-decoration:none;","X a:hover":"text-decoration:none;","X .crisp":"shape-rendering:crispEdges;","X .user-select-none":"-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;user-select:none;","X svg":"overflow:hidden;","X svg a":"fill:#447adb;","X svg a:hover":"fill:#3c6dc5;","X .main-svg":"position:absolute;top:0;left:0;pointer-events:none;","X .main-svg .draglayer":"pointer-events:all;","X .cursor-default":"cursor:default;","X .cursor-pointer":"cursor:pointer;","X .cursor-crosshair":"cursor:crosshair;","X .cursor-move":"cursor:move;","X .cursor-col-resize":"cursor:col-resize;","X .cursor-row-resize":"cursor:row-resize;","X .cursor-ns-resize":"cursor:ns-resize;","X .cursor-ew-resize":"cursor:ew-resize;","X .cursor-sw-resize":"cursor:sw-resize;","X .cursor-s-resize":"cursor:s-resize;","X .cursor-se-resize":"cursor:se-resize;","X .cursor-w-resize":"cursor:w-resize;","X .cursor-e-resize":"cursor:e-resize;","X .cursor-nw-resize":"cursor:nw-resize;","X .cursor-n-resize":"cursor:n-resize;","X .cursor-ne-resize":"cursor:ne-resize;","X .cursor-grab":"cursor:-webkit-grab;cursor:grab;","X .modebar":"position:absolute;top:2px;right:2px;","X .ease-bg":"-webkit-transition:background-color 0.3s ease 0s;-moz-transition:background-color 0.3s ease 0s;-ms-transition:background-color 0.3s ease 0s;-o-transition:background-color 0.3s ease 0s;transition:background-color 0.3s ease 0s;","X .modebar--hover>:not(.watermark)":"opacity:0;-webkit-transition:opacity 0.3s ease 0s;-moz-transition:opacity 0.3s ease 0s;-ms-transition:opacity 0.3s ease 0s;-o-transition:opacity 0.3s ease 0s;transition:opacity 0.3s ease 0s;","X:hover .modebar--hover .modebar-group":"opacity:1;","X .modebar-group":"float:left;display:inline-block;box-sizing:border-box;padding-left:8px;position:relative;vertical-align:middle;white-space:nowrap;","X .modebar-btn":"position:relative;font-size:16px;padding:3px 4px;height:22px;cursor:pointer;line-height:normal;box-sizing:border-box;","X .modebar-btn svg":"position:relative;top:2px;","X .modebar.vertical":"display:flex;flex-direction:column;flex-wrap:wrap;align-content:flex-end;max-height:100%;","X .modebar.vertical svg":"top:-1px;","X .modebar.vertical .modebar-group":"display:block;float:none;padding-left:0px;padding-bottom:8px;","X .modebar.vertical .modebar-group .modebar-btn":"display:block;text-align:center;","X [data-title]:before,X [data-title]:after":"position:absolute;-webkit-transform:translate3d(0, 0, 0);-moz-transform:translate3d(0, 0, 0);-ms-transform:translate3d(0, 0, 0);-o-transform:translate3d(0, 0, 0);transform:translate3d(0, 0, 0);display:none'..b'rker": {"colorbar": {"outlinewidth": 0, "ticks": ""}}, "type": "scatterpolar"}], "scatterpolargl": [{"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}}, "type": "scatterpolargl"}], "scatterternary": [{"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}}, "type": "scatterternary"}], "surface": [{"colorbar": {"outlinewidth": 0, "ticks": ""}, "colorscale": [[0.0, "#0d0887"], [0.1111111111111111, "#46039f"], [0.2222222222222222, "#7201a8"], [0.3333333333333333, "#9c179e"], [0.4444444444444444, "#bd3786"], [0.5555555555555556, "#d8576b"], [0.6666666666666666, "#ed7953"], [0.7777777777777778, "#fb9f3a"], [0.8888888888888888, "#fdca26"], [1.0, "#f0f921"]], "type": "surface"}], "table": [{"cells": {"fill": {"color": "#EBF0F8"}, "line": {"color": "white"}}, "header": {"fill": {"color": "#C8D4E3"}, "line": {"color": "white"}}, "type": "table"}]}, "layout": {"annotationdefaults": {"arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1}, "coloraxis": {"colorbar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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test1/report_dir/report.html.re
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test1/report_dir/report.html.re Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test2.tsv
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test2/report_dir/.re
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test2/report_dir/report.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test2/report_dir/report.html Wed Oct 28 02:36:27 2020 +0000
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test2/report_dir/report.html.re
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test2/report_dir/report.html.re Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test3/report_dir/report.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test3/report_dir/report.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test3/report_dir/report.html.re
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test3/report_dir/report.html.re Wed Oct 28 02:36:27 2020 +0000
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test4/report_dir/report.html.re
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test4/report_dir/report.html.re Wed Oct 28 02:36:27 2020 +0000
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test5/out.png
b
Binary file PDAUG_Basic_Plots/test-data/test5/out.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test5/report_dir/Out.png
b
Binary file PDAUG_Basic_Plots/test-data/test5/report_dir/Out.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Basic_Plots/test-data/test5/report_dir/report.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Basic_Plots/test-data/test5/report_dir/report.html Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,39 @@
+
+
+    <!DOCTYPE html>
+    <html lang="en">
+    <head>
+      <title>Bootstrap Example</title>
+      <meta charset="utf-8">
+      <meta name="viewport" content="width=device-width, initial-scale=1">
+      <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.0/css/bootstrap.min.css">
+      <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.0/jquery.min.js"></script>
+      <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.0/js/bootstrap.min.js"></script>
+    <body>
+    <style>
+    div.container_1 {
+      width:600px;
+      margin: auto;
+     padding-right: 10; 
+    }
+    div.table {
+      width:600px;
+      margin: auto;
+     padding-right: 10; 
+    }
+    </style>
+    </head>
+    <div class="jumbotron text-center">
+      <h1> Word Cloud </h1>
+    </div>
+    <div class="container">
+      <div class="row">
+        <div class="col-sm-4">
+          <img src="Out.png" alt="Smiley face" height="1000" width="800">
+        </div>
+
+      </div>
+    </div>
+    </body>
+    </html>
+    
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Fishers_Plot/PDAUG_Fishers_Plot.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Fishers_Plot/PDAUG_Fishers_Plot.py Wed Oct 28 02:36:27 2020 +0000
[
b'@@ -0,0 +1,420 @@\n+import matplotlib\n+matplotlib.use(\'Agg\')\n+import os\n+import sys\n+sys.path.insert(0, os.path.abspath(\'..\'))\n+\n+import quantiprot\n+from quantiprot.utils.io import load_fasta_file\n+from quantiprot.utils.feature import Feature, FeatureSet\n+from quantiprot.metrics.aaindex import get_aa2volume, get_aa2hydropathy\n+from quantiprot.metrics.basic import average\n+\n+from matplotlib import pyplot as plt\n+\n+\n+from math import log10, floor\n+import numpy as np\n+from matplotlib import pyplot as plt\n+from scipy.stats import fisher_exact\n+from quantiprot.utils.sequence import SequenceSet, compact\n+\n+\n+def _count_frame(data, frame_range, num_bins):\n+    """\n+    Count instances in a 2D frame\n+\n+    The function discretizes the feature space into a grid of cells.\n+    Then it counts the number of instances that fall into each cell.\n+    An efficient method for counting instances is used. It performs parallel\n+    logical comparisons of data instances to vectors that hold information on\n+    grid lines.\n+\n+    Args:\n+        data (numpy.matrix): a Nx2 data matrix\n+        frame_range (numpy.matrix): a 2x2 matrix which defines feature ranges\n+        num_bins (list): a pair defining the resolution of the 2D grid\n+    Returns:\n+        cell_counts (numpy.matrix): a matrix holding counts of instances in\n+            each grid cell\n+        bin_ranges (tuple): a pair of numpy matrices holding information on\n+            bin(grid_cell) ranges\n+    """\n+    grid_x = np.linspace(start=frame_range[0, 0], stop=frame_range[1, 0],\\\n+                          num=num_bins[0]+1, endpoint=True)\n+    grid_y = np.linspace(start=frame_range[0, 1], stop=frame_range[1, 1],\\\n+                          num=num_bins[1]+1, endpoint=True)\n+    # copy because we add ones in the next lines\n+    bin_ranges = (np.copy(grid_x), np.copy(grid_y))\n+\n+\n+    #Count points in each grid cell\n+    grid_x[-1] += 1 # the last cell has to contain data at the border\n+    grid_y[-1] += 1 # the last cell has to contain data at the border\n+\n+    gte_x = np.matrix(data[:, 0] >= grid_x, dtype=\'float64\')\n+    lt_x = np.matrix(data[:, 0] < grid_x, dtype=\'float64\')\n+    gte_y = np.matrix(data[:, 1] >= grid_y, dtype=\'float64\')\n+    lt_y = np.matrix(data[:, 1] < grid_y, dtype=\'float64\')\n+\n+    dif_x = gte_x - lt_x\n+    dif_y = gte_y - lt_y\n+\n+    bins_x = dif_x.argmin(axis=1) - 1\n+    bins_y = dif_y.argmin(axis=1) - 1\n+\n+    coords = np.concatenate((bins_x, bins_y), axis=1)\n+\n+    cell_counts = np.zeros(shape=(len(grid_x)-1, len(grid_y)-1))\n+\n+    for i in range(coords.shape[0]):\n+        cell_counts[coords[i, 0], coords[i, 1]] += 1\n+\n+    return cell_counts, bin_ranges\n+\n+\n+def local_fisher_2d(set1, set2, features=None, \\\n+                    windows_per_frame=10, overlap_factor=1, frame_range=None):\n+    """\n+    Compare local and global distribution of samples from two populations\n+    in the 2d feature space using the Fisher\'s exact test.\n+\n+    The function performs the Fisher Exact Test for comparing local and global\n+    ratia of instance counts from two different populations. It uses the\n+    \'_count_frame\' function to discretize the feature space and get instance\n+    counts. Then it scans the 2d feature space with a sliding window and\n+    performs the Fisher Exact test.\n+\n+        Args:\n+            set1 (SequenceSet or numpy.matrix): the first set with at least\n+                2 sequence features.\n+            set2 (SequenceSet or numpy.matrix): the second set with at least\n+                2 sequence features.\n+            features (tuple or list): strings with feature names for running\n+                the 2d Fisher test. If None then the first two features are\n+                used. Relevant only if \'set1\' or \'set2\' are SequenceSets.\n+            windows_per_frame (int): ratio between the whole feature space and\n+                the sliding window (default 10).\n+            overlap_factor (int):ratio between the size of a sliding window\n+                and a dis'..b'iewport" content="width=device-width, initial-scale=1">\n+      <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.0/css/bootstrap.min.css">\n+      <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.0/jquery.min.js"></script>\n+      <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.0/js/bootstrap.min.js"></script>\n+    <body>\n+    <style>\n+    div.container_1 {\n+      width:600px;\n+      margin: auto;\n+     padding-right: 10; \n+    }\n+    div.table {\n+      width:600px;\n+      margin: auto;\n+     padding-right: 10; \n+    }\n+    </style>\n+    </head>\n+    <div class="jumbotron text-center">\n+      <h1> Fisher\'s Plot </h1>\n+    </div>\n+    <div class="container">\n+      <div class="row">\n+        <div class="col-sm-4">\n+          <img src="1.png" alt="Smiley face" height="800" width="800">\n+        </div>\n+\n+      </div>\n+    </div>\n+    </body>\n+    </html>\n+    """ \n+    out_html.write(part_1)\n+    out_html.close()\n+# Load sets of amyloidogenic and non-amyloidogenic peptides:\n+\n+def run(Fasta1, Fasta2, windows_per_frame, overlap_factor, xlabel, ylabel, pop1_label, pop2_label, htmlOutDir, htmlFname, Workdirpath):\n+\n+    if not os.path.exists(htmlOutDir):\n+        os.makedirs(htmlOutDir)\n+\n+    amyload_pos_seq = load_fasta_file(Fasta1)\n+    amyload_neg_seq = load_fasta_file(Fasta2)\n+\n+    # Calculate quantitive features: volume and hydropathy\n+    mean_volume = Feature(get_aa2volume()).then(average)\n+    mean_hydropathy = Feature(get_aa2hydropathy()).then(average)\n+\n+    fs = FeatureSet("volume\'n\'hydropathy")\n+    fs.add(mean_volume)\n+    fs.add(mean_hydropathy)\n+\n+    amyload_pos_conv_seq = fs(amyload_pos_seq)\n+    amyload_neg_conv_seq = fs(amyload_neg_seq)\n+\n+    # Do local Fisher:\n+    result = local_fisher_2d(amyload_pos_conv_seq, amyload_neg_conv_seq,\n+                             windows_per_frame=int(windows_per_frame), overlap_factor=int(overlap_factor))\n+\n+    # Plot local Fisher:\n+    _plot_local_fisher_2d(result, xlabel=xlabel,\n+                                  ylabel=ylabel,\n+                                  pop1_label=pop1_label,\n+                                  pop2_label=pop2_label,\n+                                  out_file_path =os.path.join(os.getcwd(), "out.png") \n+                                  )\n+\n+    \n+    #   plt.savefig(os.path.join(Workdirpath, htmlOutDir, "1.png"))\n+\n+    HTML_Gen(os.path.join(Workdirpath, htmlOutDir, htmlFname))\n+\n+if __name__=="__main__":\n+    \n+    \n+    import argparse\n+    \n+    parser = argparse.ArgumentParser()\n+    \n+    parser.add_argument("-f1", "--Fasta1", required=True, default=None, help="First fasta file ")                \n+    parser.add_argument("-f2", "--Fasta2", required=True, default=None, help="Second fasta file")   \n+    parser.add_argument("-o", "--overlap_factor", required=False, default=5, help="Overlap factor")  \n+    parser.add_argument("-w", "--windows_per_frame", required=False, default=5, help="Windows per frame")  \n+    parser.add_argument("-x", "--xlabel", required=True, default=None, help="X label")  \n+    parser.add_argument("-y", "--ylabel", required=True, default=None, help="Y label")  \n+    parser.add_argument("-p1", "--pop1_label", required=True, default=None, help="First population label")  \n+    parser.add_argument("-p2", "--pop2_label", required=True, default=None, help="Second population label") \n+    parser.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),\'report_dir\'),  help="Path to html dir")\n+    parser.add_argument("--htmlFname",  required=False, help="html output file", default="report.html")\n+    parser.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Path to output Working Directory")                          \n+    args = parser.parse_args()\n+\n+    run(args.Fasta1, args.Fasta2, args.windows_per_frame, args.overlap_factor, args.xlabel, args.ylabel, args.pop1_label, args.pop2_label, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Fishers_Plot/test-data/negative.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Fishers_Plot/test-data/negative.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>non-ACP0
+MTISLIWGIAMVVCCCIWVIFDRRRRKAGEPPL
+>non-ACP2
+MFATPLRQPTNASGARPAVSMDGQETPFQYEITD
+>non-ACP4
+LLWRKVAGATVGPGPVPA
+>non-ACP6
+DSPDPMNGASSNALIAKMNSAKLLYQHY
+>non-ACP8
+NNQEVIDAISQAISQTPGCVL
+>non-ACP10
+KKVVEKNADPETTLLVYLRRKLGLCGTKLGCGEG
+>non-ACP12
+CSRLLPSLAQEEG
+>non-ACP14
+KNDFAALQAKLDADAAEIEKWWSDSR
+>non-ACP16
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+>non-ACP18
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+>non-ACP20
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+>non-ACP22
+MFRKLLKMWILLRPTHWLILIALCAVTCAGYWLLWSE
+>non-ACP24
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+>non-ACP26
+NNPNNSNSHLRPHAYNNSRRDDSD
+>non-ACP28
+VVILASLSVMFLVSLWQQKIRERLPPGPTPLPFIGNY
+>non-ACP30
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+>non-ACP36
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+>non-ACP38
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+>non-ACP40
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+>non-ACP42
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+>non-ACP44
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+>non-ACP46
+FSPQRDRFQAEGS
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+GTLWALVFLGILVGMVVPSPAGTRANNTLLDSRG
+>non-ACP50
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+>non-ACP54
+ATLANGMSLQPPLEEVS
+>non-ACP56
+PLTATNSGLAVNN
+>non-ACP58
+VRACHKVCRCLLSGFGGRVDAGQPELLTER
+>non-ACP60
+TAGILLLLLLGTLEGS
+>non-ACP62
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+>non-ACP64
+MKNCFQLLCNLKVPAAGFKNTVKS
+>non-ACP66
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+>non-ACP68
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+>non-ACP70
+ARTLNNKLSLSKPKFSGFT
+>non-ACP72
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+>non-ACP74
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+>non-ACP122
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+>non-ACP124
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+>non-ACP126
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+>non-ACP128
+AVFGLGGVGLSVIMGCKAAGASRIIAVDIN
+>non-ACP130
+PNAKQSILQKNPDDVVIVAAYRTA
+>non-ACP132
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+>non-ACP134
+LLAAGFCPAVLCH
+>non-ACP136
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+>non-ACP138
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+>non-ACP142
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+WVTVRSQQRGLFPAI
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+HLGRPSAPTIVAQPVSGLASPASFQPEQFQYTLDNNVLT
+>non-ACP152
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+>non-ACP156
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+>non-ACP176
+VAGTESAQGPPGPAASLELWLNKATDPS
+>non-ACP178
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+>non-ACP180
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+>non-ACP182
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+>non-ACP184
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+>non-ACP186
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+>non-ACP188
+LLLLSWVALGPRSLEGADPGTPGEAEGPACP
+>non-ACP190
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+>non-ACP192
+GLLLLAGLCCLVFGIMAEDAQVAQGPSQQI
+>non-ACP194
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+>non-ACP198
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+>non-ACP200
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+>non-ACP202
+LCTSGLWTAQASTNESSNSHRGLAPTNV
+>non-ACP204
+PAIQPVLSGLSRIVNGEEA
+>non-ACP206
+GCQASLSTAQERLGHPGVPTREGVR
+>non-ACP208
+RKVLILTLVVAACGFVLWSSNGR
+>non-ACP210
+GRVRSRCPGPALLLLLALAARPALAGPPAAALQ
+>non-ACP212
+CRITKPALLVLNQETAKVVQT
+>non-ACP214
+KAEVCMAVPWLSLQ
+>non-ACP216
+SHLELNNGTKMPTLGLGT
+>non-ACP218
+LLLPEAAAERDAREKLALWDRRPDTTAPL
+>non-ACP220
+LLALSLVLLYRYATYSHGFFKKLGIPGPKPLPLFGNVLS
+>non-ACP222
+LLSLWRQSSGRGKLPPGPTPLPVIGNILQIGIKD
+>non-ACP224
+AFKSMEVANFYYEADCLAAAYGGKAAPAAPPADRPGPR
+>non-ACP226
+SLFWAARPLQRCGQLVRMAIRAQH
+>non-ACP228
+MRPPRTLTSTATMSALSTSMPMEIDDVMDEDAVNGQA
+>non-ACP230
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+>non-ACP232
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+>non-ACP234
+PQGFDVDRDAKKLNKACKGMGTNEAAIIEILSG
+>non-ACP236
+IFCLILWVVKAWQPRLPKGLKSPPGPWGWPLLG
+>non-ACP238
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+>non-ACP242
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+>non-ACP248
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+LLSALTLETWVLLAVILVLLYRLG
+>non-ACP252
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+>non-ACP254
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+>non-ACP256
+VRSVRAAVGGLRAISAPSAPCLPRPWGLRAG
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+>non-ACP260
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+>non-ACP262
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+>non-ACP270
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+>non-ACP272
+LPFKLLLFVLLDGWTRLTH
+>non-ACP274
+QALWLVLVLSMPPVLVAAVVGTLVSLVQ
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Fishers_Plot/test-data/out.png
b
Binary file PDAUG_Fishers_Plot/test-data/out.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Fishers_Plot/test-data/positive.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Fishers_Plot/test-data/positive.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLFDIIKKIAESI
+>ACP4
+GLLDIVKKVVGAFGSL
+>ACP6
+GLFDIVKKVVGALGSL
+>ACP8
+GLFDIVKKVVGTLAGL
+>ACP10
+GLFDIAKKVIGVIGSL
+>ACP12
+GLFDIVKKIAGHIAGSI
+>ACP14
+GLFDIVKKIAGHIVSSI
+>ACP16
+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF
+>ACP18
+HGVSGHGQHGVHG
+>ACP20
+FKCRRWQWRMKKLGAPSITCVRRAF
+>ACP22
+KWKLFKKIKFLHSAKKF
+>ACP24
+KSSAYSLQMGATAIKQVKKLFKKWGW
+>ACP26
+GIGTKILGGVKTALKGALKELASTYAN
+>ACP28
+GIGGKILSGLKTALKGAAKELASTYLH
+>ACP30
+GIGGVLLSAGKAALKGLAKVLAEKYAN
+>ACP32
+SIGAKILGGVKTFFKGALKELASTYLQ
+>ACP34
+FLPLLAGLAANFLPTIICKISYKC
+>ACP36
+FVQWFSKFLGRIL
+>ACP38
+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL
+>ACP40
+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK
+>ACP42
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+>ACP44
+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK
+>ACP46
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+>ACP48
+GIGAVLKVLTTGLPALISWIKRKRQQ
+>ACP50
+ALWKNMLKGIGKLAGQAALGAVKTLVGAE
+>ACP52
+ACYCRIPACIAGERRYGTCIYQGRLWAFCC
+>ACP54
+ECRRLCYKQRCVTYCRGR
+>ACP56
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+>ACP58
+KWCFRVCYRGICYRRCR
+>ACP60
+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK
+>ACP62
+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP64
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+>ACP94
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP96
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP98
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+>ACP100
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+>ACP122
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP124
+LLGMIPLAISAISALSKL
+>ACP126
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP128
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP130
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP132
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP134
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP136
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP138
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP140
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP142
+GFKDLLKGAAKALVKTVLF
+>ACP144
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP146
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP148
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP150
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP152
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP154
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP156
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP158
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP160
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP162
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP164
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP166
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP168
+VNWKKVLGKIIKVAK
+>ACP170
+VNWKKILGKIIKVAK
+>ACP172
+FFSLLPSLIGGLVSAIK
+>ACP174
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP176
+KWKLFKKIPKFLHLAKKF
+>ACP178
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
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+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP182
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP184
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP186
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP188
+FVDLKKIANIINSIFGK
+>ACP190
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP192
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP194
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP196
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP198
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP200
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+>ACP202
+GKWMSLLKHILK
+>ACP204
+GFGMALKLLKKVL
+>ACP206
+GTGLPMSERRKIMLMMR
+>ACP208
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP210
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP212
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP214
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+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP218
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+>ACP232
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP234
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP236
+KWKLFKKIGAVLKVL
+>ACP238
+GACFSIAHECGA
+>ACP240
+TCCATGACGTTCCTGACGTT
+>ACP242
+KRFKQDGGASHASPASS
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+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
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+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/PDAUG_ML_Models.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/PDAUG_ML_Models.py Wed Oct 28 02:36:27 2020 +0000
[
b"@@ -0,0 +1,1088 @@\n+\n+import numpy as np\n+import sys,os\n+from scipy import interp\n+import pandas as pd\n+\n+###############################################################\n+from sklearn.metrics import *\n+from sklearn import preprocessing\n+from sklearn.metrics import accuracy_score\n+from sklearn.metrics import precision_recall_fscore_support\n+from sklearn.metrics import roc_curve, auc\n+from sklearn.model_selection import StratifiedKFold\n+from sklearn.preprocessing import StandardScaler\n+from sklearn.preprocessing import MinMaxScaler\n+###############################################################\n+from sklearn.linear_model import LogisticRegression\n+from sklearn.naive_bayes import GaussianNB\n+from sklearn.neighbors import KNeighborsClassifier\n+from sklearn.tree import DecisionTreeClassifier\n+from sklearn.svm import SVC\n+from sklearn.ensemble import RandomForestClassifier\n+from sklearn.linear_model import SGDClassifier\n+from sklearn.ensemble import GradientBoostingClassifier\n+from sklearn.neural_network import MLPClassifier\n+###############################################################\n+from itertools import cycle\n+################################################################\n+from sklearn.model_selection import train_test_split\n+\n+\n+\n+def ReturnData(TrainFile,  TestMethod, TestFile=None):\n+    \n+    if (TestFile == None) and (TestMethod == 'Internal' or 'CrossVal'):\n+\n+        df = pd.read_csv(TrainFile, sep='\\t')\n+        clm_list = df.columns.tolist()\n+        X_train = df[clm_list[0:len(clm_list)-1]].values\n+        y_train = df[clm_list[len(clm_list)-1]].values\n+        X_test = None \n+        y_test = None\n+        return X_train, y_train, X_test, y_test\n+\n+    elif (TestFile is not None) and (TestMethod == 'External'):\n+\n+        df = pd.read_csv(TrainFile, sep='\\t')\n+        clm_list = df.columns.tolist()\n+        X_train = df[clm_list[0:len(clm_list)-1]].values\n+        y_train = df[clm_list[len(clm_list)-1]].values\n+        df1 = pd.read_csv(TestFile, sep='\\t')\n+        clm_list = df1.columns.tolist()\n+        X_test = df1[clm_list[0:len(clm_list)-1]].values\n+        y_test = df1[clm_list[len(clm_list)-1]].values\n+        return X_train, y_train, X_test, y_test\n+\n+    elif (TestFile is not None) and (TestMethod == 'Predict'):\n+\n+        df = pd.read_csv(TrainFile, sep='\\t')\n+        clm_list = df.columns.tolist()\n+        X_train = df[clm_list[0:len(clm_list)-1]].values\n+        y_train = df[clm_list[len(clm_list)-1]].values\n+\n+        df = pd.read_csv(TestFile, sep='\\t')\n+        X_test = df\n+        y_test = None\n+        return X_train, y_train, X_train, y_train\n+\n+def Fit_Model(TrainData, Test_Method, Algo, Selected_Sclaer,  Workdirpath,  htmlOutDir, OutFile, htmlFname,    NoOfFolds=None, TestSize=None, TestData=None ):\n+\n+    if not os.path.exists(htmlOutDir):\n+        os.makedirs(htmlOutDir)\n+\n+    if Test_Method == 'Internal':\n+        X,y,_,_ = ReturnData(TrainData, Test_Method)\n+\n+        mean_tpr = 0.0\n+        mean_fpr = np.linspace(0, 1, 100)\n+\n+        specificity_list = []\n+        sensitivity_list = []\n+        precison_list = []\n+        mcc_list =  []\n+        f1_list = []\n+        \n+        folds = StratifiedKFold(n_splits=5)\n+        mean_tpr = 0.0\n+        mean_fpr = np.linspace(0, 1, 100)\n+\n+        ##########################\n+        accuracy_score_l = []\n+        cohen_kappa_score_l = []\n+        matthews_corrcoef_l = []\n+        precision_l = []\n+        recall_l = []\n+        f_score_l = []\n+        ##########################\n+\n+        folds = StratifiedKFold(n_splits=5)\n+\n+        for i, (train, test) in enumerate(folds.split(X, y)):\n+\n+            if Selected_Sclaer=='Min_Max':\n+                scaler = MinMaxScaler().fit(X[train])\n+                x_train = scaler.transform(X[train])\n+                x_test = scaler.transform(X[test])\n+\n+            elif Selected_Sclaer=='Standard_Scaler':\n+                scaler = preprocessing.StandardScaler().fit(X[train])\n+                x_train = "..b' args.cache_size, args.verbose, args.max_iter, args.decision_function_shape, args.randomState, args.breakties, args.TrainFile, args.TestMethod,  args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+elif sys.argv[1] == \'SGDC\':   \n+    SGD_Classifier( args.loss, args.penalty, args.alpha, args.l1_ratio, args.fit_intercept, args.max_iter, args.tol, args.shuffle, args.verbose, args.epsilon, args.n_jobs, args.random_state, args.learning_rate, args.eta0, args.power_t, args.early_stopping, args.validation_fraction, args.n_iter_no_change, args.warm_start, args.average, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+elif sys.argv[1] == \'DTC\':\n+    DT_Classifier(args.criterion, args.splitter, args.max_depth, args.min_samples_split, args.min_samples_leaf, args.min_weight_fraction_leaf,  args.random_state, args.max_leaf_nodes, args.min_impurity_decrease, args.min_impurity_split,  args.presort, args.ccpalpha, args.max_features, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+elif sys.argv[1] == \'GBC\':\n+    GB_Classifier(args.loss, args.learning_rate, args.n_estimators, args.subsample, args.criterion, args.min_samples_split, args.min_samples_leaf, args.min_weight_fraction_leaf,  args.max_depth, args.min_impurity_decrease, args.min_impurity_split, args.init, args.random_state, args.verbose, args.max_leaf_nodes, args.warm_start, args.presort, args.validation_fraction, args.n_iter_no_change, args.tol, args.ccpalpha, args.max_features, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+elif sys.argv[1] == \'RFC\':\n+    RF_Classifier( args.n_estimators, args.criterion, args.max_depth, args.min_samples_split, args.min_samples_leaf, args.min_weight_fraction_leaf, args.max_features, args.max_leaf_nodes, args.min_impurity_decrease,  args.min_impurity_split, args.bootstrap, args.oob_score, args.n_jobs, args.random_state, args.verbose, args.warm_start,  args.ccp_alpha, args.max_samples, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+elif sys.argv[1] == \'LRC\':\n+    LR_Classifier(args.penalty, args.dual, args.tol, args.C, args.fit_intercept, args.intercept_scaling,  args.random_state, args.solver, args.max_iter, args.multi_class, args.verbose, args.warm_start, args.n_jobs, args.l1_ratio, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+elif sys.argv[1] == \'KNC\':\n+    KN_Classifier(args.n_neighbors, args.weights, args.algorithm, args.leaf_size, args.p, args.metric, args.metric_params,  args.n_jobs, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+elif sys.argv[1] == \'GNBC\':\n+    GNB_Classifier( args.var_smoothing, args.TrainFile, args.TestMethod,  args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)  \n+elif sys.argv[1] == \'MLP\' :\n+    MLP_Classifier(args.hidden_layer_sizes, args.activation, args.solver, args.alpha, args.batch_size, args.learning_rate, args.learning_rate_init, args.power_t, args.max_iter, args.shuffle, args.random_state, args.tol, args.verbose, args.warm_start, args.momentum, args.nesterovs_momentum, args.early_stopping, args.validation_fraction, args.beta_1, args.beta_2, args.epsilon, args.n_iter_no_change, args.max_fun, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.Testspt, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)\n+else:\n+    print ("option not correct")\n+    exit()\n+\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test.tsv Wed Oct 28 02:36:27 2020 +0000
b
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test1/SVMC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test1/SVMC.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+SVMC 0.999 0.999 0.999 0.999 0.995
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test1/report_dir/SVMC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test1/report_dir/SVMC.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test1/report_dir/SVMC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test1/report_dir/SVMC.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test2/.zip
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test2/GNBC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test2/GNBC.tsv Wed Oct 28 02:36:27 2020 +0000
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@@ -0,0 +1,2 @@
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test2/report_dir/GNBC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test2/report_dir/GNBC.tsv
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+++ b/PDAUG_ML_Models/test-data/test2/report_dir/GNBC.tsv Wed Oct 28 02:36:27 2020 +0000
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@@ -0,0 +1,2 @@
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test3/SGDC.tsv
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b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+SGDC 0.697 0.826 0.697 0.628 0.9
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test3/report_dir/SGDC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test3/report_dir/SGDC.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test4/DTC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test4/DTC.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+DTC 0.997 0.997 0.997 0.997 0.993
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test4/report_dir/DTC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test4/report_dir/DTC.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test5/GBC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test5/GBC.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+GBC 0.998 0.998 0.998 0.998 0.995
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test5/report_dir/GBC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test5/report_dir/GBC.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test6/RFC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test6/RFC.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+RFC 0.5 0.25 0.5 0.333 0.5
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test6/report_dir/RFC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test6/report_dir/RFC.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test7/LRC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test7/LRC.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+LRC 1.0 1.0 1.0 1.0 0.995
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test7/report_dir/LRC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test7/report_dir/LRC.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test8/KNC.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test8/KNC.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+KNC 0.999 0.999 0.999 0.999 0.995
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test8/report_dir/KNC.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test8/report_dir/KNC.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test9/MLP.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test9/MLP.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy precision recall f1 mean_auc
+MLP 0.999 0.999 0.999 0.999 0.995
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_ML_Models/test-data/test9/report_dir/MLP.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_ML_Models/test-data/test9/report_dir/MLP.html Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/PDAUG_Merge_Dataframes.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/PDAUG_Merge_Dataframes.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,28 @@
+import glob
+import pandas as pd 
+import sys
+
+files = sys.argv[1]
+out_file = sys.argv[2]
+
+
+data_frame = pd.read_csv(files.split(',')[0],sep='\t')
+
+
+for file in files.split(',')[1:]: 
+
+    df1 = pd.read_csv(file,sep='\t')
+    data_frame =  pd.concat([data_frame,df1])
+
+final_DF = data_frame.fillna(0)
+
+final_DF.to_csv(out_file,sep="\t", index=False)
+
+
+
+
+
+
+
+
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/.RData
b
Binary file PDAUG_Merge_Dataframes/test-data/.RData has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/.Rhistory
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/.Rhistory Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,11 @@
+install.pcakges("igraph")
+install.packages("igraph")
+library(igraph)
+library(igraph)
+st <- make_star(40)
+st
+tr <- make_tree(40, children = 3, mode = "undirected")
+tr
+er <- sample_gnm(n=100, m=40)
+er
+q()
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Blast_baseline_bacteriocin_paper-checkpoint.ipynb
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Blast_baseline_bacteriocin_paper-checkpoint.ipynb Wed Oct 28 02:36:27 2020 +0000
[
b'@@ -0,0 +1,2618 @@\n+{\n+ "cells": [\n+  {\n+   "cell_type": "markdown",\n+   "metadata": {},\n+   "source": [\n+    "## Import libraries"\n+   ]\n+  },\n+  {\n+   "cell_type": "code",\n+   "execution_count": 1,\n+   "metadata": {},\n+   "outputs": [\n+    {\n+     "name": "stderr",\n+     "output_type": "stream",\n+     "text": [\n+      "/home/nafizh/anaconda3/lib/python3.6/site-packages/Bio/SearchIO/__init__.py:211: BiopythonExperimentalWarning: Bio.SearchIO is an experimental submodule which may undergo significant changes prior to its future official release.\\n",\n+      "  BiopythonExperimentalWarning)\\n",\n+      "/home/nafizh/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\\n",\n+      "  from ._conv import register_converters as _register_converters\\n",\n+      "Using TensorFlow backend.\\n",\n+      "/home/nafizh/anaconda3/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module \'tensorflow.python.framework.fast_tensor_util\' does not match runtime version 3.6\\n",\n+      "  return f(*args, **kwds)\\n"\n+     ]\n+    }\n+   ],\n+   "source": [\n+    "import os\\n",\n+    "from Bio import SearchIO\\n",\n+    "from Bio.SearchIO import HmmerIO\\n",\n+    "from Bio import SeqIO\\n",\n+    "%matplotlib inline\\n",\n+    "import matplotlib.pyplot as plt\\n",\n+    "plt.rcParams[\'figure.figsize\'] = (10.0, 7.0)\\n",\n+    "\\n",\n+    "import math\\n",\n+    "import numpy as np\\n",\n+    "#seed = 1337\\n",\n+    "seed = 42\\n",\n+    "np.random.seed(seed)\\n",\n+    "# THEANO_FLAGS=\\"dnn.conv.algo_bwd_filter=deterministic, dnn.conv.algo_bwd_data=deterministic\\"\\n",\n+    "\\n",\n+    "# %matplotlib inline\\n",\n+    "# import matplotlib.pyplot as plt\\n",\n+    "# plt.rcParams[\'figure.figsize\'] = (10.0, 7.0)\\n",\n+    "\\n",\n+    "#import numpy as np\\n",\n+    "#import matplotlib.pyplot as plt\\n",\n+    "import os\\n",\n+    "import pandas as pd\\n",\n+    "from collections import defaultdict\\n",\n+    "from Bio import SeqIO\\n",\n+    "from nltk import bigrams\\n",\n+    "from nltk import trigrams\\n",\n+    "import gensim, logging\\n",\n+    "logging.basicConfig(format=\'%(asctime)s : %(levelname)s : %(message)s\', level=logging.INFO)\\n",\n+    "\\n",\n+    "# import theano\\n",\n+    "# theano.config.device = \'gpu\'\\n",\n+    "# theano.config.floatX = \'float32\'\\n",\n+    "from keras.layers import Dropout\\n",\n+    "from keras.layers import Input, Dense, Lambda, LSTM, RepeatVector, Conv1D, MaxPooling1D, UpSampling1D\\n",\n+    "from keras.models import Model\\n",\n+    "from keras import backend as K\\n",\n+    "from keras import objectives\\n",\n+    "from keras.datasets import mnist\\n",\n+    "from keras import regularizers\\n",\n+    "from keras.layers import GaussianNoise\\n",\n+    "from keras.layers import Activation\\n",\n+    "from keras.callbacks import LearningRateScheduler, EarlyStopping\\n",\n+    "\\n",\n+    "from keras.layers.normalization import BatchNormalization\\n",\n+    "from keras.models import Sequential\\n",\n+    "from keras.layers import Dense\\n",\n+    "from keras.wrappers.scikit_learn import KerasClassifier\\n",\n+    "from keras.utils import np_utils\\n",\n+    "from keras import regularizers\\n",\n+    "#from keras.regularizers import l2, activity_l2, l1, activity_l1\\n",\n+    "from keras.optimizers import Adam, SGD\\n",\n+    "\\n",\n+    "from keras.wrappers.scikit_learn import KerasClassifier\\n",\n+    "from sklearn.decomposition import TruncatedSVD\\n",\n+    "from sklearn.manifold import TSNE\\n",\n+    "from sklearn.preprocessing import normalize\\n",\n+    "from sklearn.utils import shuffle\\n",\n+    "from sklearn.model_selection import train_test_split\\n",\n+    "from sklearn import metrics\\n",\n+    "from sklearn.model_selection import KFold\\n",\n+    "from sklearn.preprocessing import LabelEncoder\\n",\n+    "from sklearn.pipeline import Pipeline\\n",\n+    "from sklearn.metrics import precision_score\\'..b'gwePJjw8HAcHBxMdmZMSUkhISFB7cxrmKTLMLuzwaFDh3jnnXfQ6/Vo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\\n",\n+      "text/plain": [\n+       "<matplotlib.figure.Figure at 0x7f3a60385e48>"\n+      ]\n+     },\n+     "metadata": {},\n+     "output_type": "display_data"\n+    }\n+   ],\n+   "source": [\n+    "cluster_size_dict_list = [value for key, value in cluster_sizes_dict.items()]\\n",\n+    "\\n",\n+    "plt.rc(\'ytick\',labelsize=24)\\n",\n+    "plt.rc(\'xtick\',labelsize=24)\\n",\n+    "\\n",\n+    "_, ax = plt.subplots(1, 1, figsize=(12,9))\\n",\n+    "#fig.set_size_inches(12, 9)\\n",\n+    "ax.spines[\\"top\\"].set_visible(False)  \\n",\n+    "ax.spines[\\"right\\"].set_visible(False)\\n",\n+    "ax.hist(cluster_size_dict_list, bins=np.arange(min(cluster_size_dict_list),max(cluster_size_dict_list)), \\n",\n+    "                                               align=\'left\', \\n",\n+    "                                               color=\'r\', edgecolor = \'black\')\\n",\n+    "# plt.title(\\"%i Negative bacteriocin sequences\\\\nLengths %i to %i\\" \\\\\\n",\n+    "#             % (len(sizes),min(sizes),max(sizes)))\\n",\n+    "ax.set_ylabel(\'Count\',fontsize = 28)\\n",\n+    "ax.set_xlabel(\'Bacteriocin cluster sizes\',fontsize = 28)\\n",\n+    "plt.xlim(1.0, )\\n",\n+    "plt.tick_params(size = 10)\\n",\n+    "#plt.xlabel(\\"Sequence length\\")\\n",\n+    "#plt.ylabel(\\"Count\\")\\n",\n+    "# ax.figure.savefig(\'bacteriocin_cluster_sizes.eps\', format = \'eps\', dpi = 1200, bbox_inches=\\"tight\\")\\n",\n+    "# ax.figure.savefig(\'bacteriocin_cluster_sizes.png\', format = \'png\', dpi = 1200, bbox_inches=\\"tight\\")\\n",\n+    "# ax.figure.savefig(\'bacteriocin_cluster_sizes.pdf\', format = \'pdf\', dpi = 1200, bbox_inches=\\"tight\\")\\n",\n+    "#plt.show()"\n+   ]\n+  },\n+  {\n+   "cell_type": "code",\n+   "execution_count": null,\n+   "metadata": {\n+    "collapsed": true,\n+    "hidden": true\n+   },\n+   "outputs": [],\n+   "source": []\n+  }\n+ ],\n+ "metadata": {\n+  "kernelspec": {\n+   "display_name": "Python 2",\n+   "language": "python",\n+   "name": "python2"\n+  },\n+  "language_info": {\n+   "codemirror_mode": {\n+    "name": "ipython",\n+    "version": 2\n+   },\n+   "file_extension": ".py",\n+   "mimetype": "text/x-python",\n+   "name": "python",\n+   "nbconvert_exporter": "python",\n+   "pygments_lexer": "ipython2",\n+   "version": "2.7.16"\n+  }\n+ },\n+ "nbformat": 4,\n+ "nbformat_minor": 2\n+}\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Untitled-checkpoint.ipynb
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Untitled-checkpoint.ipynb Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Untitled1-checkpoint.ipynb
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/.ipynb_checkpoints/Untitled1-checkpoint.ipynb Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Warning message in read.table(file = file, header = header, sep = sep, quote = quote, :\n",
+      "“incomplete final line found by readTableHeader on '/Users/joshij/Desktop/GitRepos/Peptide/align/New.csv'”\n"
+     ]
+    },
+    {
+     "ename": "ERROR",
+     "evalue": "Error in data[[rowvar]]: attempt to select less than one element in get1index\n",
+     "output_type": "error",
+     "traceback": [
+      "Error in data[[rowvar]]: attempt to select less than one element in get1index\nTraceback:\n",
+      "1. read.csv(\"/Users/joshij/Desktop/GitRepos/Peptide/align/New.csv\", \n .     sep = \",\", header = TRUE, row.names = \"index\")",
+      "2. read.table(file = file, header = header, sep = sep, quote = quote, \n .     dec = dec, fill = fill, comment.char = comment.char, ...)"
+     ]
+    }
+   ],
+   "source": [
+    "m <- read.csv(\"/Users/joshij/Desktop/GitRepos/Peptide/align/New.csv\", sep=\",\",header=TRUE, row.names='index')\n",
+    "\n",
+    "\n",
+    "m <- as.matrix(read.table(\"/Users/joshij/Desktop/GitRepos/Peptide/align/New.csv\", sep=\",\", header=TRUE, row.names='index')[, 1:4])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "library(igraph)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ERROR",
+     "evalue": "Error in mde(x): 'list' object cannot be coerced to type 'double'\n",
+     "output_type": "error",
+     "traceback": [
+      "Error in mde(x): 'list' object cannot be coerced to type 'double'\nTraceback:\n",
+      "1. graph.adjacency(m, mode = \"undirected\", weighted = TRUE)",
+      "2. graph.adjacency.dense(adjmatrix, mode = mode, weighted = weighted, \n .     diag = diag)",
+      "3. `mode<-`(`*tmp*`, value = \"double\")"
+     ]
+    }
+   ],
+   "source": [
+    "m <- as.matrix(read.table(\"out_1.csv\", sep=\",\", header=TRUE, row.names='index')[, 1:4])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "R",
+   "language": "R",
+   "name": "ir"
+  },
+  "language_info": {
+   "codemirror_mode": "r",
+   "file_extension": ".r",
+   "mimetype": "text/x-r-source",
+   "name": "R",
+   "pygments_lexer": "r",
+   "version": "4.0.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/1.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.781 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/2.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/2.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.781 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/3.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/3.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.781 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/4.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/4.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.781 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/5.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/5.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.781 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/6.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/6.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.781 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Merge_Dataframes/test-data/out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Merge_Dataframes/test-data/out.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,7 @@
+Algo accuracy presision recall f1 mean_auc
+SVMC 0.608 0.7809999999999999 0.608 0.537 0.608
+SVMC 0.608 0.7809999999999999 0.608 0.537 0.608
+SVMC 0.608 0.7809999999999999 0.608 0.537 0.608
+SVMC 0.608 0.7809999999999999 0.608 0.537 0.608
+SVMC 0.608 0.7809999999999999 0.608 0.537 0.608
+SVMC 0.608 0.7809999999999999 0.608 0.537 0.608
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/PDAUG_Peptide_CD_Spectral_Analysis.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/PDAUG_Peptide_CD_Spectral_Analysis.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,125 @@
+import glob
+import pandas as pd 
+import sys
+import os
+import argparse
+
+from modlamp.wetlab import CD
+
+parser = argparse.ArgumentParser(description='Deployment tool')
+subparsers = parser.add_subparsers()
+
+calc_ellipticity = subparsers.add_parser('calc_ellipticity')
+calc_ellipticity.add_argument("-T","--Type", required=True, default=None, help="Input fasta sequence")
+calc_ellipticity.add_argument("-H","--DirPath", required=False, default=os.getcwd(), help="Input fasta sequence")
+calc_ellipticity.add_argument("-Wn","--WMin", required=True, default=None, help="Number of mutations to perform per sequence")
+calc_ellipticity.add_argument("-Wx","--Wmax", required=True, default=None, help="Probability of mutating a sequence")
+calc_ellipticity.add_argument("-A","--Amide", required=True, default=None, help="Mutated output fasta")
+calc_ellipticity.add_argument("-P","--Pathlen", required=True, default=None, help="Mutated output fasta")
+calc_ellipticity.add_argument("-O","--OutPut", required=False, default="OutFile.tsv", help="Mutated output fasta")
+
+PlotData = subparsers.add_parser('PlotData')
+
+PlotData.add_argument("-H","--DirPath", required=False, default=os.getcwd(), help="Input fasta sequence")
+PlotData.add_argument("-T","--Type", required=True, default=None, help="Input fasta sequence")
+PlotData.add_argument("-Wn","--WMin", required=True, default=None, help="Number of mutations to perform per sequence")
+PlotData.add_argument("-Wx","--Wmax", required=True, default=None, help="Probability of mutating a sequence")
+PlotData.add_argument("-A","--Amide", required=True, default=None, help="Mutated output fasta")
+PlotData.add_argument("-P","--Pathlen", required=True, default=None, help="Mutated output fasta")
+
+Dichroweb = subparsers.add_parser("Dichroweb")
+Dichroweb.add_argument("-H","--DirPath", required=False, default=os.getcwd(), help="Input fasta sequence")
+Dichroweb.add_argument("-T","--Type", required=True, default=None, help="Input fasta sequence")
+Dichroweb.add_argument("-Wn","--WMin", required=True, default=None, help="Number of mutations to perform per sequence")
+Dichroweb.add_argument("-Wx","--Wmax", required=True, default=None, help="Probability of mutating a sequence")
+Dichroweb.add_argument("-A","--Amide", required=True, default=None, help="Mutated output fasta")
+Dichroweb.add_argument("-P","--Pathlen", required=True, default=None, help="Mutated output fasta")
+
+helicity = subparsers.add_parser('helicity')
+
+helicity.add_argument("-H","--DirPath", required=False, default=os.getcwd(), help="Input fasta sequence")
+helicity.add_argument("-Wn","--WMin", required=True, default=None, help="Number of mutations to perform per sequence")
+helicity.add_argument("-Wx","--Wmax", required=True, default=None, help="Probability of mutating a sequence")
+helicity.add_argument("-A","--Amide", required=True, default=None, help="Mutated output fasta")
+helicity.add_argument("-P","--Pathlen", required=True, default=None, help="Mutated output fasta")
+helicity.add_argument("-t","--temperature", required=False, default=24.0, help="")
+helicity.add_argument("-k","--k", required=True, default=2.4, help="")
+helicity.add_argument("-I","--Induction", required=False, default=True, help="")
+helicity.add_argument("-O","--OutPut", required=False, default="result.tsv", help="")
+
+
+args = parser.parse_args()
+
+if sys.argv[1] == "calc_ellipticity":
+
+    if args.Type == "calc_molar_ellipticity":
+
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_molar_ellipticity()
+        df = cd.molar_ellipticity
+        df = pd.DataFrame(df[0])
+        df.to_csv(args.OutPut, index=None, sep="\t")
+
+    elif args.Type == "calc_meanres_ellipticity":
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_meanres_ellipticity()
+        df = cd.meanres_ellipticity
+        df = pd.DataFrame(df[0])
+        df.to_csv(args.OutPut, index=None, sep="\t")
+    else:
+        pass
+
+if sys.argv[1] == "PlotData":
+
+    os.system('ls temp')
+
+    if args.Type == "mean residue ellipticity":
+
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_meanres_ellipticity()
+        cd.plot(data="mean residue ellipticity", combine='solvent')
+
+    elif args.Type == "molar ellipticity":
+
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_molar_ellipticity()
+        cd.plot(data="molar ellipticity", combine='solvent')
+
+    elif args.Type == "circular dichroism":
+
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_molar_ellipticity()
+        cd.plot(data="circular dichroism", combine='solvent')
+
+    else:
+        pass
+
+if sys.argv[1] == "Dichroweb":
+
+    if args.Type == "mean residue ellipticity":
+
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_meanres_ellipticity()
+        cd.dichroweb(data="mean residue ellipticity")
+
+    elif args.Type == "molar ellipticity":
+
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_molar_ellipticity()
+        cd.dichroweb(data='molar ellipticity')
+
+    elif args.Type == "circular dichroism":
+
+        cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))
+        cd.calc_molar_ellipticity()
+        cd.dichroweb(data='circular dichroism')
+
+
+if sys.argv[1] == "helicity":
+    cd = CD(args.DirPath, wmin=int(args.WMin), wmax=int(args.Wmax), amide=args.Amide, pathlen=float(args.Pathlen))    
+    cd.calc_meanres_ellipticity()
+    cd.helicity(temperature=float(args.temperature), k=float(args.k), induction=args.Induction, filename=args.OutPut )
+
+
+
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro1/0.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro1/0.csv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,82 @@
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro1/1.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro1/1.csv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,82 @@
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro2/0.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro2/0.csv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,82 @@
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro2/1.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro2/1.csv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,82 @@
+V1;V2
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro3/0.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro3/0.csv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,82 @@
+V1;V2
+260.0;-0.010606
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro3/1.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Dichro3/1.csv Wed Oct 28 02:36:27 2020 +0000
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Halicity.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Halicity.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,3 @@
+Name Solvent Helicity Induction
+Peptide1 T 76.06 11.403
+Peptide1 W 6.67 0.0
b
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Peptide1_T.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Peptide1_T.csv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,85 @@
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+GLFDIVKKVLKLLK
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/Peptide2_W.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/Peptide2_W.csv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,85 @@
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/calc_meanres_ellipticity.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/calc_meanres_ellipticity.tsv Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/calc_molar_ellipticity.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/calc_molar_ellipticity.tsv Wed Oct 28 02:36:27 2020 +0000
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_CD_Spectral_Analysis/test-data/helicity.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_CD_Spectral_Analysis/test-data/helicity.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,7 @@
+Name,Solvent,Helicity,Induction
+"Peptide1
+","W
+",6.98,0.088
+"Peptide1
+","T
+",79.68,0.0
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Descriptors/PDAUG_Peptide_Core_Descriptors.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Descriptors/PDAUG_Peptide_Core_Descriptors.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,43 @@
+from modlamp.core import BaseDescriptor
+from modlamp.descriptors import PeptideDescriptor
+import pandas as pd
+import argparse, os
+
+parser = argparse.ArgumentParser()
+
+parser.add_argument("-I", "--InFile", required=True, default=None, help="Input file")
+parser.add_argument("-O", "--OutFile", required=True, default=None, help="Output file")
+parser.add_argument("-N", "--Ngrams", required=True, default=None, help="ngrams")
+
+args = parser.parse_args()
+
+file = open(args.InFile)
+lines = file.readlines()
+
+Index = []
+Pep = []
+
+
+for line in lines:
+    if '>' in line:
+        Index.append(line.strip('\n'))
+    else:
+        line = line.strip('\n')
+        line = line.strip('\r')
+        Pep.append(line)
+
+df =    pd.DataFrame()
+
+for i, l in enumerate(Pep):
+
+    D = PeptideDescriptor(l)
+    D.count_ngrams([int(args.Ngrams)])
+
+    df1 = pd.DataFrame(D.descriptor, index=["sequence"+str(i),])
+    df = pd.concat([df, df1], axis=0)
+
+df =  df.fillna(0)
+df.to_csv(args.OutFile, sep='\t', index=None)
+
+
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Descriptors/test-data/Out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Descriptors/test-data/Out.tsv Wed Oct 28 02:36:27 2020 +0000
b
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n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Descriptors/test-data/test.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Descriptors/test-data/test.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
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+FLGALFKVASKVLPSVKCAITKKC
+>ACP250
+GIGKFLKKAKKFGKAFVKILKK
+>ACP252
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP254
+VECYGPNRPQF
+>ACP256
+KRFKQDGGWSHWSPWSSC
+>ACP258
+RQVFQVAYIIIKA
+>ACP260
+KAFDITYVRLKF
+>ACP262
+DFKLFAVTIKYR
+>ACP264
+DFKLFAVYIKYR
+>ACP266
+WHSDMEWWYLLG
+>ACP268
+HTMYYHHYQHHL
+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/PDAUG_Peptide_Core_Functions.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/PDAUG_Peptide_Core_Functions.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,168 @@
+from modlamp.core import BaseSequence
+import pandas as pd
+import os, sys
+import argparse
+
+
+parser = argparse.ArgumentParser(description='Deployment tool')
+subparsers = parser.add_subparsers()
+
+mutateAA = subparsers.add_parser('mutateAA')
+mutateAA.add_argument("-I","--InFile", required=True, default=None, help="Input fasta sequence")
+mutateAA.add_argument("-N","--nr", required=True, default=None, help="Number of mutations to perform per sequence")
+mutateAA.add_argument("-P","--Prob", required=True, default=None, help="Probability of mutating a sequence")
+mutateAA.add_argument("-F","--FastOut", required=False, default='Out.fasta', help="Mutated output fasta")
+
+filterduplicates = subparsers.add_parser('filterduplicates')
+filterduplicates.add_argument("-I","--InFile", required=True, default=None, help="Input file")
+filterduplicates.add_argument("-F","--FastOut", required=False, default='Out.fasta', help="Output file")
+
+
+keepnaturalaa = subparsers.add_parser('keepnaturalaa')
+keepnaturalaa.add_argument("-I","--InFile", required=True, default=None, help="Inputt file")
+keepnaturalaa.add_argument("-F","--FastOut", required=False, default='Out.fasta', help="Output file")
+
+
+filteraa = subparsers.add_parser('filteraa')
+filteraa.add_argument("-I","--InFile", required=True, default=None, help="Input file")
+filteraa.add_argument("-F","--FastOut", required=False, default='Out.fasta', help="Output file")
+filteraa.add_argument("-A","--FilterAA", required=True, default=None, help="Filter amino acide")
+
+args = parser.parse_args()
+
+if sys.argv[1] == 'mutateAA':
+
+    Pep = []
+    Index = []
+
+    f = open(args.InFile)
+    lines = f.readlines()
+
+    for line in lines:
+        if '>' in line:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Index.append(line)
+        else:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Pep.append(line)
+
+    b = BaseSequence(len(Pep))
+    b.sequences = Pep
+    b.mutate_AA(int(args.nr), float(args.Prob))
+    OutPep = b.sequences
+
+    OutFasta = open(args.FastOut, 'w')
+
+    for i,O in enumerate(OutPep):
+
+        OutFasta.write(Index[i]+'\n')
+        OutFasta.write(O+'\n')
+
+
+elif sys.argv[1] == 'filterduplicates':
+
+    Pep = []
+    Index = []
+
+    f = open(args.InFile)
+    lines = f.readlines()
+
+    for line in lines:
+        if '>' in line:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Index.append(line)
+        else:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Pep.append(line)
+
+    b = BaseSequence(len(Pep))
+
+    b.sequences = Pep
+
+    b.filter_duplicates()
+
+    OutPep = b.sequences
+
+    OutFasta = open(args.FastOut, 'w')
+
+    for i,O in enumerate(OutPep):
+
+        OutFasta.write(Index[i]+'\n')
+        OutFasta.write(O+'\n')
+
+
+elif sys.argv[1] == 'keepnaturalaa':
+
+    Pep = []
+    Index = []
+
+    f = open(args.InFile)
+    lines = f.readlines()
+
+    for line in lines:
+        if '>' in line:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Index.append(line)
+        else:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Pep.append(line)
+
+    b = BaseSequence(len(Pep))
+    b.sequences = Pep
+    b.keep_natural_aa()
+
+    OutFasta = open(args.FastOut, 'w')
+
+    OutPep = b.sequences
+
+    for i,O in enumerate(OutPep):
+
+        OutFasta.write(Index[i]+'\n')
+        OutFasta.write(O+'\n')
+
+
+elif sys.argv[1] == 'filteraa':
+
+    Pep = []
+    Index = []
+
+    f = open(args.InFile)
+    lines = f.readlines()
+
+    for line in lines:
+        if '>' in line:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Index.append(line)
+        else:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            Pep.append(line)
+
+
+    b = BaseSequence(len(Pep))
+    b.sequences = Pep
+
+    FilterAA = args.FilterAA.split(',')
+
+    b.filter_aa(FilterAA)
+
+    OutPep = b.sequences
+
+    OutFasta = open(args.FastOut, 'w')
+
+    for i,O in enumerate(OutPep):
+
+        OutFasta.write(Index[i]+'\n')
+        OutFasta.write(O+'\n')
+    
+
+
+
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/out1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/out1.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+>ACP0
+GFWSKIQEVGKEAAKAAAVAAGKAALGAVSEAV
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/out2.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/out2.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,6 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP1
+GLWSKIKKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLWSKIKEVGKEAAKKAAGKAALGAVSEAV
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/out3.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/out3.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+>ACP0
+GFWSKIQEVGKE
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/out4.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/out4.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/test1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/test1.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/test2.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/test2.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,8 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP1
+GLWSKIKKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLWSKIKEVGKEAAKKAAGKAALGAVSEAV
+>ACP3
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/test3.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/test3.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,4 @@
+>ACP0
+GFWSKIQEVGKX
+>ACP1
+GFWSKIQEVGKE
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Core_Functions/test-data/test4.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Core_Functions/test-data/test4.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Access/PDAUG_Peptide_Data_Access.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Access/PDAUG_Peptide_Data_Access.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,77 @@
+import modlamp
+from modlamp.datasets import load_AMPvsTM
+from modlamp.datasets import load_AMPvsUniProt
+from modlamp.datasets import load_ACPvsTM
+from modlamp.datasets import load_ACPvsRandom
+from modlamp.database import query_apd
+from modlamp.database import query_camp
+import os
+import pandas as pd
+
+def DataGen(DataBaseType, OutFile, IDs):
+
+    if DataBaseType == 'AMPvsTM':
+        data = load_AMPvsTM()
+
+    elif DataBaseType == 'AMPvsUniProt':
+        data = load_AMPvsUniProt()
+
+    elif DataBaseType == 'ACPvsTM':
+        data = load_ACPvsTM()
+
+    elif DataBaseType == 'ACPvsRandom':
+        data = load_ACPvsRandom()
+
+    elif DataBaseType == 'query_apd':
+
+        data = query_apd([int(i) for i in IDs.split(',')])
+        df = pd.DataFrame(data, columns=['Peptides'])
+        df.to_csv(OutFile, index=False, sep='\t')
+        exit()
+
+    elif DataBaseType == 'query_camp':
+        data = query_camp([int(i) for i in IDs.split(',')])
+        df = pd.DataFrame(data, columns=['Peptides'])
+        df.to_csv(OutFile, index=False, sep='\t')
+        exit()
+
+    else:
+        print ("Enter Correct Values")
+        exit()
+
+    Target = data.target.tolist()
+    Target_list = set(Target)
+    df = data.sequences
+
+
+    Target = pd.DataFrame(Target, columns=['Target'])
+    df = pd.DataFrame(df, columns=['Peptide'])
+    
+    df = pd.DataFrame(df)
+    df = pd.concat([df, Target], axis=1)
+
+    df.to_csv(OutFile, index=False, sep='\t')
+
+
+if __name__=="__main__":
+
+    import argparse
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("-d", "--DataBaseType",
+                        required=True,
+                        default=None,
+                        help="Name of the dataset ")
+                        
+    parser.add_argument("-o", "--OutFile",
+                        required=False,
+                        default='Out.tsv',
+                        help="Out put file name for str descriptors")   
+
+    parser.add_argument("-L", "--List",
+     required=False,
+     default=None,
+     help="List of integer as ID")
+
+    args = parser.parse_args()
+    DataGen(args.DataBaseType, args.OutFile, args.List)
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Access/test-data/apd.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Access/test-data/apd.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,4 @@
+Peptides
+NLCERASLTWTGNCGNTGHCDTQCRNWESAKHGACHKRGNWKCFCYFDC
+VFIDILDKVENAIHNAAQVGIGFAKPFEKLINPK
+GNNRPVYIPQPRPPHPRI
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Access/test-data/camp.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Access/test-data/camp.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,5 @@
+Peptides
+RFRPPIRRPPIRPPFYPPFRPPIRPPIFPPIRPPFRPPLRFP
+ICIFCCGCCHRSKCGMCCKT
+FLSLLPSIVSGAVSLAKKLG
+FLPIIAKLLGGLL
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Access/test-data/out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Access/test-data/out.tsv Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,413 @@\n+Peptide\tTarget\n+AAGAATVLLVIVLLAGSYLAVLA\t0\n+LWIVIACLACVGSAAALTLRA\t0\n+FYRFYMLREGTAVPAVWFSIELIFGLFA\t0\n+GTLELGVDYGRAN\t0\n+KLFWRAVVAEFLATTLFVFISIGSALGFK\t0\n+HGSIGAGVDW\t0\n+ATIYLVCFCFFKQLAMIFMSVLAGNMYE\t0\n+GKLSLAATRSSE\t0\n+TSRLLLAGVALGIICSALMTWAIYF\t0\n+LGFFLVTFGFIWGMMLL\t0\n+YMLFTMIFVISSIIITVVVI\t0\n+ACFSAKVN\t0\n+LIWVAATLAGAIIAVLLVIYA\t0\n+HIPFAFAFAILAYLTLVLFRPVM\t0\n+CGLLVLLTLLLMGAIVTLGVF\t0\n+TGVYILVGVVLWTA\t0\n+LSMFIITPVMVLGTIFIFVMG\t0\n+MTLVALLVIGVSLTGYLGLKA\t0\n+QLYYQVLNFGMIVSSALMIW\t0\n+ALGALCLLLSVGSATACLLLGA\t0\n+LAVIFFFASALLYSQAAT\t0\n+MGHQLLVQLESIAITIVWSGVVAFIGYKLADLT\t0\n+ADILILSLLVIQCALGLLTIPFSA\t0\n+RHQQATFAGFIKGATWVSILSIAVLVFLALAN\t0\n+GTKWWTVGIRPMYKW\t0\n+PAIRVFATYAKWDEK\t0\n+PHVFLLFITFPILFIGWGSQS\t0\n+AGLVLWGAIIFVGWNALLLLFFW\t0\n+TQIVLLGLVTAALWAGLLTLLLLWHW\t0\n+SFIGRVFLFLMIVLPLWCGLHRMHHAMHD\t0\n+MYLGAGIALIPVIMSINYL\t0\n+FQTGFDFSD\t0\n+LISGTLGIICLSLMATLGILL\t0\n+FPFLNNLSFWFTVVGVILVNVSLG\t0\n+LDIYTRLGGMVWR\t0\n+FLIFLLVIMTVITVALLTLLF\t0\n+KDIGILYLFTAGIVGLISVCFTVYMRMELQH\t0\n+PLFYIINILVPCVLISFMINLVFYL\t0\n+HKALKTLGIIMGVFTLCWLPFFLVNIVNVF\t0\n+ANLKKLKTLMSAFLIVLGLLTFGA\t0\n+IWVGIFLLAALLAALFVCLKA\t0\n+KGAAGITGAGFITLAATLS\t0\n+VVLLAIVTLISVVQNGFFAHKV\t0\n+IAIDVLAVLVPLAAFLLDGSPDWSLYCAVWLLKPLRDS\t0\n+ALTVGTLLFLTGIGAASWAIV\t0\n+ITLIIFGVMAGVIGTILLISYGI\t0\n+WVWISLYYVAFYVVMSGIFAL\t0\n+GSNVALHVN\t0\n+GVLELGVDYGRAN\t0\n+IYLLILIILSMLCLVYASVPL\t0\n+LCSFLFVIVLFVATFYTL\t0\n+PLYFIVNVVIPCLLFSFLTGLVFYL\t0\n+ALLIAGGVGLLALAAALVLNA\t0\n+IWTWLRTTL\t0\n+PAHMIAISFFFTNALALALHGALVLSAA\t0\n+GGSLYIVGIFLPIWTFMIYIF\t0\n+GLTLGTGGR\t0\n+STVTGGYAQS\t0\n+DCFLLLVLLLYAPVGFCLLVL\t0\n+FWRAVVAEFLAMILFIFISIGSALG\t0\n+DPVLYQHILWFFGHPEVYIIILPGFGIISHVISTFAK\t0\n+LTFTEKWN\t0\n+IRDTLMRLVLTVRSN\t0\n+GKLSLAATRSTE\t0\n+GYNKFVVQYATDA\t0\n+QFHTMLMIAASGAVLIALGILCLVIQMYVSIR\t0\n+LILVLFVVLVSSVGVSLTLYA\t0\n+MASLWADYT\t0\n+DAWSGFVRGYGYDNRTN\t0\n+RWLWDFVNA\t0\n+MFVALLGLGLGQVVCSVALFF\t0\n+NMSTYVDYII\t0\n+IWVKMTFIVVLGLCFVFFWSF\t0\n+SLLISVVLVAYYLYIPLPDAI\t0\n+RKTTINGLIVAVILGVCFTGLQAYEYSHA\t0\n+IPVQLLWVNLVTDGLPATALG\t0\n+LAVIAGGVGFIMVAVLLVLFA\t0\n+MNKRNIMNLILAGGAGLPITTLALGYGAFF\t0\n+IALIVAGLSALGIATALVLNA\t0\n+NGNMWRILDHGAISL\t0\n+VAIICAAVVAVGLIVGLSVGL\t0\n+FSFLIVAGATTLFCLLHFGVI\t0\n+VGISIATIVAIIAAIYYVPW\t0\n+PLFAWSVFITAWLILLSLPVLAGAITMLLMDRNF\t0\n+LILIGAGLGVLALAAGLILTA\t0\n+LGLAAGAIYYYNTSNVFA\t0\n+QLGAGAFGGYQV\t0\n+IAIALLVILVVCSLITMSVIL\t0\n+LAFLIGGIIGGLLLLIGVSCCLW\t0\n+NGHMLRILDHGAISM\t0\n+MALILGIDRFMSECRALTNF\t0\n+AVIAGTTLAITALAVTS\t0\n+LYIVLAILCGVSIAVALALTA\t0\n+AAVTLGVLCLGLLVTVILLILQL\t0\n+LWLVIGVLTAAALAVTLIALA\t0\n+GTLLLLTAIGAASWAIVAVLL\t0\n+LLLVASVIQGLGLLLCFTYICLHFSAL\t0\n+AMIVALIVICITAVVAALV\t0\n+LVFIGTCGAVLAVALGLVLWA\t0\n+TRFGIAAKYQ\t0\n+IPWAVLIVVLITSLIIALIAL\t0\n+LWVVCAVLAGLGLTTALVLYA\t0\n+FAGRVLAGAVMMSGIGIFGLWAGIL\t0\n+LLIVLAGLAVVAVASGLILNA\t0\n+VGSIVGGIYLGFCFNAGAPAVEAFI\t0\n+MLSLGVSYR\t0\n+LTKWFFCCVCTILTMPFF\t0\n+LATIAASAIVLVVAVGLGLMA\t0\n+PIVVTGAVY\t0\n+KPHNLPMVFTGTAILYIGWFGFNAGSA\t0\n+DEFGEQLSKVISLICVAVWL\t0\n+HTLLTGVDF\t0\n+SVELIALLAISCTFFLFMHT\t0\n+LLIALLIYWTLAFITKTIKF\t0\n+FKLVIFVVLGIAIASGLMLYA\t0\n+CTLSISVLLAQTIFLFLIA\t0\n+FVIAGGTLAIPILAFVASFLL\t0\n+LLVITAIVLILSAAVGLVMYA\t0\n+LALATALIGGVAAIASLLLYA\t0\n+NPVIVIINLITLAAALLHTKTWFEL\t0\n+FIVVAGVVILAVTIALLVYFL\t0\n+IGLMCFLSIIITTVCIIMIAT\t0\n+FSVDTQLQS\t0\n+EVYILLNWIGYVNSGFNPLIYCRS\t0\n+LTLAVALIVGVSAIASLLLYA\t0\n+LYLAVVVLIGIGLTTTLVLYA\t0\n+MSTAISVLLAQAVFLLLT\t0\n+ALPGLMNKMEKAGCKRSVV\t0\n+KQFIRYLISSNVGEVVCIFL\t0\n+KYVVSSLVLVYGLIKVLTWIF\t0\n+TGVSPVFAGGVEYA\t0\n+IVIVLGILCFLLLLTVAVLVI\t0\n+KSLGILGILLGVAALCTIVALSVV\t0\n+LCLFVVTPVMVVGTAWIFL\t0\n+LYLAIVVLIGVALTATLMLYA\t0\n+LTILLAIAPVLALAVGLALYG\t0\n+FFVLLLMILILVNLAMTIWIL\t0\n+FIVLIPSVVITVIFLFFWLFM\t0\n+ILVLLILAVITIFALVCVLLV\t0\n+TYFIVLIPSVVITVIFLFFWLFM\t0\n+FLVLFIFLTSFFLNYSHTMVA\t0\n+GDKIGMFFQAMATFFGGFIIGF\t0\n+SNGVIVGTCLAFVAGMIGMAYAA\t0\n+FTFEGAARSDD\t0\n+MNYMVYFNFFACVLVPLLLMLGVYL\t0\n+AGLILLVVTLIGMSVLVRVLI\t0\n+VFLAVYLLGGITFLPLVLFTL\t0\n+LIKISALVFVTVAFFYLG\t0\n+GFFGVATFFFAALGIILIAWSAVL\t0\n+GQWEISVIWGLGVAMAIYLTA\t0\n+LWWIQAMTGFAMFFLGSVHLYIMMT\t0\n+IAVVITVVFLTLLSVVILIFF\t0\n+QVVATATFR\t0\n+MLLCFAFLWVLGIAYYMY\t0\n+IFCIIMLFALLGFL\t0\n+PLCICVAFTCLALVLVTSIVL\t0\n+LIIVLAIVVGVGAAVGLALSA\t0\n+ILVPCVLGLLLLPILAMLMALCV\t0\n+LGLLLAALICVGIATTLVLNA\t0\n+GYAAYYLVRKNFALAMPYLVE\t0\n+LPRTLAVLLVGAALAISGAVMQALF\t0\n+ILLFYVIFYGCLAGIFIGTIQ\t0\n+IMSTLLEVGYDNVKSQ\t0\n+LLAVALIIAMSISLAWQAAG'..b'GCKIKGEC\t1\n+GIFSKLAGKKLKNLLISGLKNVGKEVGMDVVRTGIDIAGCKIKGEC\t1\n+GIFSKLGRKKIKNLLISGLKNVGKEVGMDVVRTGIDIAGCKIKGEC\t1\n+GIFSLIKGAAQLIGKTVAKEAGKTGLELMACKVTKQC\t1\n+GIFTLIKGAAKLIGKTVAKEAGKTGLELMACKITNQC\t1\n+GILDAIKAIAKAAG\t1\n+GILDFAKTVVGGIRNALGI\t1\n+GILSLFTGGIKALGKTLFKMAGKAGAEHLACKATNQC\t1\n+GILSSIKGVAKGVAKNVAAQLLDTLKCKITGC\t1\n+GIMDSVKGLAKNLAGKLLDSLKCKITGC\t1\n+GIMDTIKDTAKTVAVGLLNKLKCKITGC\t1\n+GINTLKKVIQGLHEVIKLVSNHA\t1\n+GINTLKKVIQGLHEVIKLVSNHE\t1\n+GIPCGESCVWIPCISAALGCSCKNKVCYRN\t1\n+GKLQAFLAKMKEIAAQTL\t1\n+GKVWDWIKSAAKKIWSSEPVSQLKGQVLNAAKNYVAEKIGATPT\t1\n+GLADFLNKAVGKVVDFVKS\t1\n+GLFDVVKGVLKGVGKNVAGSLLEQLKCKLSGGC\t1\n+GLFKVLGSVAKHLLPHVAPIIAEKL\t1\n+GLFLDTLKGAAKDVAGKLLEGLKCKIAGCKP\t1\n+GLFLDTLKGLAGKLLQGLKCIKAGCKP\t1\n+GLFSILRGAAKFASKGLGKDLTKLGVDLVACKISKQC\t1\n+GLFSKFNKKKIKSGLFKIIKTAGKEAGLEALRTGIDVIGCKIKGEC\t1\n+GLFSKFNKKKIKSGLIKIIKTAGKEAGLEALRTGIDVIGCKIKGEC\t1\n+GLFSVLGSVAKHLLPHVAPIIAEKL\t1\n+GLFSVLGSVAKHLLPHVVPVIAEKL\t1\n+GLFTLIKGAAKLIGKTVAKEAGKTGLELMACKITNQC\t1\n+GLLDFVTGVGKDIFAQLIKQI\t1\n+GLLDSIKGMAISAGKGALQNLLKVASCKLDKTC\t1\n+GLLDSLKNLAINAAKGAGQSVLNTLSCKLSKTC\t1\n+GLLDTIKGVAKTVAASMLDKLKCKISGC\t1\n+GLLGGLLGPLLGGGGGGGGGLL\t1\n+GLLGPLLKIAAKVGSNLL\t1\n+GLLGSIFGAGKKIACALSGLC\t1\n+GLLGSLFGAGKKVACALSGLC\t1\n+GLLKRIKTLL\t1\n+GLLSGLKKVGKHVAKNVAVSLMDSLKCKISGDC\t1\n+GLLSKVLGVGKKVLCGVSGLC\t1\n+GLLSVLGSVAKHVLPHVVPVIAEHL\t1\n+GLMSSIGKALGGLIVDVLKPKTPAS\t1\n+GLNALKKVFQGIHEAIKLINNHVQ\t1\n+GLNTLKKVFQGLHEAIKLINNHVQ\t1\n+GLWNKIKEAASKAAGKAALGFVNEMV\t1\n+GLWSKIKAAGKEAAKAAAKAAGKAALNAVSEAV\t1\n+GLWSKIKEAAKTAGLMAMGFVNDMV\t1\n+GLWSTIKQKGKEAAIAAAKAAGQAALGAL\t1\n+GPLSCGRNGGVCIPIRCPVPMRQIGTCFGRPVKCCRSW\t1\n+GRLQAFLAKMKEIAAQTL\t1\n+GRPNPVNNKPTPHPRL\t1\n+GRPNPVNTKPTPYPRL\t1\n+GSGRGSCRSQCMRRHEDEPWRVQECVSQCRRRRGGGD\t1\n+GSKKPVPIIYCNRRTGKCQRM\t1\n+GVLDILKNAAKNILAHAAEQI\t1\n+GVVDILKGAGKDLLAHLVGKISEKV\t1\n+GWKDWAKKAGGWLKKKGPGMAKAALKAAMQ\t1\n+GWKDWLKKGKEWLKAKGPGIVKAALQAATQ\t1\n+GWKDWLNKGKEWLKKKGPGIMKAALKAATQ\t1\n+HGVSGHGQHGVHG\t1\n+IFGAILPLALGALKNLIK\t1\n+IIEKLVNTALGLLSGL\t1\n+IIGHLIKTALGMLGL\t1\n+ILGTILGLLKGL\t1\n+ILGTILGLLKSL\t1\n+ILPLVGNLLNDLL\t1\n+ILQKAVLDCLKAAGSSLSKAAITAIYNKIT\t1\n+INWKKIAEIGKQVLSAL\t1\n+INWKKIAEVGGKILSSL\t1\n+INWLKLGKAIIDAL\t1\n+IPRPLDPCIAQNGRCFTGICRYPYFWIGTCRNGKSCCRRR\t1\n+IWLTALKFLGKHAAKHLAKQQLSKL\t1\n+KDRPKKPGLCPPRPQKPCVKECKNDDSCPGQQKCCNYGCKDECRDPIFVG\t1\n+KTCEHLADTYRGVCFTNASCDDHCKNKAHLISGTCHNWKCFCTQNC\t1\n+KTCENLADTY\t1\n+KTCENLSGTFKGPCIPDGNCNKHCRNNEHLLSGRCRDDFRCWCTNRC\t1\n+KTCMTKKEGWGRCLIDTTCAHSCRKYGYMGGKCQGITRRCYCLLNC\t1\n+KWCFRVCYRGICYRKCR\t1\n+KWCFRVCYRGICYRRCR\t1\n+KYYGNGVSCNKKGCSVDWGKAIGIIGNNSAANLATGGAAGWSK\t1\n+LCNERPSQTWSGNCGNTAHCDKQCQDWEKASHGACHKRENHWKCFCYFNC\t1\n+LFCRKGTCHFGGCPAHLVKVGSCFGFRACCKWPWDV\t1\n+LLGRCKVKSNRFHGPCLTDTHCSTVCRGEGYKGGDCHGLRRRCMCLC\t1\n+LLGRCKVKSNRFNGPCLTDTHCSTVCRGEGYKGGDCHGLRRRCMCLC\t1\n+LLKELWTKIKGAGKAVLGKIKGLL\t1\n+LLKELWTKMKGAGKAVLGKIKGLL\t1\n+LLPILGNLLNGLL\t1\n+LLPNLLKSLL\t1\n+LMCTHPLDCSN\t1\n+LNLKGIFKKVASLLT\t1\n+LPVNEAQCRQVGGYCGLRICNFPSRFLGLCTRNHPCCSRVWV\t1\n+MSWLNFLKYIAKYGKKAVSAAWKYKGKVLEWLNVGPTLEWVWQKLKKIAGL\t1\n+QDKCKKVYENYPVSKCQLANQCNYDCKLDKHARSGECFYDEKRNLQCICDYCEY\t1\n+QGVRNHVTCRIYGGFCVPIRCPGRTRQIGTCFGRPVKCCRRW\t1\n+QKLCERPSGTWSGVCGNNNACKNQCINLEKARHGSCNYVFPAHKCICYFPC\t1\n+QQCGRQASGRLCGNRLCCSQWGYCGSTASYCGAGCQSQCRS\t1\n+QRFIHPTYRPPPQPRRPVIMRA\t1\n+RQRVEELSKFSKKGAAARRRK\t1\n+RSGRGECRRQCLRRHEGQPWETQECMRRCRRRG\t1\n+RSVCRQIKICRRRGGCYYKCTNRPY\t1\n+SAPRGCWTKSYPPKPCK\t1\n+SCTTCVCTCSCCTT\t1\n+SFGLCRLRRGFCARGRCRFPSIPIGRCSRFVQCCRRVW\t1\n+SGISGPLSCGRNGGVCIPIRCPVPMRQIGTCFGRPVKCCRSW\t1\n+SIVPIRCRSNRDCRRFCGFRGGRCTYARQCLCGY\t1\n+SKGKKANKDVELARG\t1\n+SMLSVLKNLGKVGLGFVACKINKQC\t1\n+TSYGNGVHCNKSKCWIDVSELETYKAGTVSNPKDILW\t1\n+VDKGSYLPRPTPPRPIYNRN\t1\n+VDKPDYRPRPRPPNM\t1\n+VDKPDYRPRPWPRNMI\t1\n+VDKPDYRPRPWPRPN\t1\n+VDKPDYRPRPWPRPNM\t1\n+VLPIIGNLLNSLL\t1\n+VLPLISMALGKLL\t1\n+VNPIILGVLPKFVCLITKKC\t1\n+VRNFVTCRINRGFCVPIRCPGHRRQIGTCLGPQIKCCR\t1\n+VRNHVTCRINRGFCVPIRCPGRTRQIGTCFGPRIKCCRSW\t1\n+VTCDLLSFEAKGFAANHSLCAAHCLAIGRRGGSCERGVCICRR\t1\n+VTCDLLSIKGVAEHSACAANCLSMGKAGGRCENGICLCRKTTFKELWDKRF\t1\n+VTCFCKRPVCDSGETQIGYCRLGNTFYRLCCRQ\t1\n+WLGSALKIGAKLLPSVVGLFKKKKQ\t1\n+WNPFKELERAGQRVRDAIISAGPAVATVGQAAAIARG\t1\n+WNPFKELERAGQRVRDAVISAAPAVATVGQAAAIARG\t1\n+YDLSKNCRLRGGICYIGKCPRRFFRSGSCSRGNVCCLRFG\t1\n+YSKSLPLSVLNP\t1\n+YVSCLFRGARCRVYSGRSCCFGYYCRRDFPGSIFGTCSRRNF\t1\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/PDAUG_Peptide_Data_Plotting.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Plotting/PDAUG_Peptide_Data_Plotting.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,115 @@
+from modlamp.plot import helical_wheel
+from modlamp.plot import plot_pde
+from modlamp.plot import plot_violin
+from modlamp.plot import plot_aa_distr
+import pandas as pd
+import argparse
+import sys, os
+
+
+
+parser = argparse.ArgumentParser(description='Deployment tool')
+subparsers = parser.add_subparsers()
+
+HelWhl = subparsers.add_parser('HelWhl')
+
+HelWhl.add_argument("-I","--InFile", required=True, default=None, help="Input data file")
+HelWhl.add_argument("-C","--colorcoding", required=False, default='rainbow', help="available: , charge, polar, simple, amphipathic, none")
+HelWhl.add_argument("-L","--lineweights", required=False, default=True, help="(boolean) defines whether connection lines decrease in thickness along the sequence")
+HelWhl.add_argument("-F","--filename", required=False, default="out.png", help="")
+HelWhl.add_argument("-s","--seq", required=False, default=False, help="")
+HelWhl.add_argument("-M","--movment", required=False, default=False, help="")
+HelWhl.add_argument("-O", "--OutFile", required=False, default="out.png", help="OutFile")
+
+
+PltPde = subparsers.add_parser('PltPde')
+PltPde.add_argument("-I","--InFile", required=True, default=None, help="Input data file")
+PltPde.add_argument("-l", "--ClmList", required=True, default=None, help="")
+PltPde.add_argument("-F","--filename", required=False, default="out.png", help="filename where to safe the plot. default = None > show the plot")
+PltPde.add_argument("-O", "--OutFile", required=False, default="out.png", help="OutFile")
+
+PltVio = subparsers.add_parser('PltVio')
+PltVio.add_argument("-I","--InFile", required=True, default=None, help="Input data file")
+PltVio.add_argument("-l", "--ClmList", required=True, default=None, help="Column list")
+PltVio.add_argument("-C","--colors", required=False, default=None, help='Data to be plotted')
+PltVio.add_argument("-B","--bp", required=False, default=False, help="Print a box blot inside violin")
+PltVio.add_argument("-T","--title", required=False, default=None, help="Title of the plot.")
+PltVio.add_argument("-a","--axlabels", required=False, default=None, help="list containing the axis labels for the plot")
+PltVio.add_argument("-M","--y_max", required=False, default=1, help='y-axis maximum.')
+PltVio.add_argument("-m","--y_min", required=False, default=0, help="y-axis minimum.")
+PltVio.add_argument("-O", "--OutFile", required=False, default="out.png", help="OutFile")
+
+
+PltAaDis = subparsers.add_parser('PltAaDis')
+PltAaDis.add_argument("-I","--InFile", required=True, default=None, help="Input data file")
+PltAaDis.add_argument("-O", "--OutFile", required=False, default="out.png", help="OutFile")
+
+args = parser.parse_args()
+
+
+if sys.argv[1] == 'HelWhl':
+
+    f = open(args.InFile)
+    lines = f.readlines()
+    sequence = lines[1].strip('\n')
+
+    if args.movment == 'true':
+        mvt = True
+    else:
+      mvt = False
+
+    if args.seq == 'true':
+        sq = True
+    else:
+      sq = False
+
+    if args.lineweights == 'true':
+        lw = True
+    else:
+      lw = False
+
+    helical_wheel(sequence, colorcoding=args.colorcoding, lineweights=args.lineweights, filename=args.OutFile, seq=args.seq, moment=mvt)
+
+
+elif sys.argv[1] == 'PltPde':
+
+    df = pd.read_csv(args.InFile, sep="\t")
+
+    data = df[args.ClmList.split(',')].as_matrix().T
+
+    plot_pde(data, filename=args.OutFile)
+
+elif sys.argv[1] == 'PltVio':
+
+    df = pd.read_csv(args.InFile, sep="\t")
+
+    data = df[args.ClmList.split(',')].as_matrix().T
+
+    c = ['#0B486B']*len(args.ClmList.split(','))
+
+    plot_violin(data, colors=c, bp=True, filename=args.OutFile)
+
+
+elif sys.argv[1] == 'PltAaDis':
+
+    f = open(args.InFile)
+    lines = f.readlines()
+
+    sequences = []
+
+    for line in lines:
+        if '>' in line:
+            pass
+        else:
+            sequences.append(line.strip('\n'))
+
+    plot_aa_distr(sequences, color='#0B486B', filename=args.OutFile) 
+
+
+
+
+
+
+
+
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/out1.png
b
Binary file PDAUG_Peptide_Data_Plotting/test-data/out1.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/out2.png
b
Binary file PDAUG_Peptide_Data_Plotting/test-data/out2.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/out3.png
b
Binary file PDAUG_Peptide_Data_Plotting/test-data/out3.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/out4.png
b
Binary file PDAUG_Peptide_Data_Plotting/test-data/out4.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/test1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Plotting/test-data/test1.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,101 @@
+a1 a2 a3 a4 class
+0.745792458 0.426207561 0.191600108 0.288065693 1
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/test2.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Plotting/test-data/test2.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,8 @@
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/test3.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Plotting/test-data/test3.tsv Wed Oct 28 02:36:27 2020 +0000
b
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Data_Plotting/test-data/test4.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Data_Plotting/test-data/test4.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
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+>non-ACP22
+MFRKLLKMWILLRPTHWLILIALCAVTCAGYWLLWSE
+>non-ACP24
+HLRGPADSGWMPQAAPCLSGAPQAS
+>non-ACP26
+NNPNNSNSHLRPHAYNNSRRDDSD
+>non-ACP28
+VVILASLSVMFLVSLWQQKIRERLPPGPTPLPFIGNY
+>non-ACP30
+ICLSCLISFFLWNQNRAKGKLPPG
+>non-ACP32
+VVMNSLRVILQAS
+>non-ACP34
+ARPRLDLQLVQRFVRIQKVF
+>non-ACP36
+MLAKGLSLRSVLAKGCQPFLSPTWQSSVLATGGGANIS
+>non-ACP38
+AAGLPGAALPLRKRPLRAPSPEPAAPRGAAGLVV
+>non-ACP40
+PPMPSAPPVHPPP
+>non-ACP42
+SCPIDKRRPLIAFLRRLRD
+>non-ACP44
+RLGLWASGLILILGFLKLLRLLLRRQRLARAMD
+>non-ACP46
+FSPQRDRFQAEGS
+>non-ACP48
+GTLWALVFLGILVGMVVPSPAGTRANNTLLDSRG
+>non-ACP50
+MNRLLQKGTSLVPSWRTR
+>non-ACP52
+MTTSLIWGIAIAACCCLWLILGIRRRQT
+>non-ACP54
+ATLANGMSLQPPLEEVS
+>non-ACP56
+PLTATNSGLAVNN
+>non-ACP58
+VRACHKVCRCLLSGFGGRVDAGQPELLTER
+>non-ACP60
+TAGILLLLLLGTLEGS
+>non-ACP62
+MEPSILLLLALLVGFLLLLVRGH
+>non-ACP64
+MKNCFQLLCNLKVPAAGFKNTVKS
+>non-ACP66
+SVIHTQAHASGLQQVPQLVPAGPGGGGKAVAPSKQSK
+>non-ACP68
+KPLGLLKPSSLMKVSGRFKAHQDA
+>non-ACP70
+ARTLNNKLSLSKPKFSGFT
+>non-ACP72
+LLLVIIWTLFGPSGLGEELLSLSLASLLPAPASPGPP
+>non-ACP74
+WPGILVGGARVASCRYPALGPRLA
+>non-ACP76
+RSVKGLVALITGGASGL
+>non-ACP78
+AAAALRARILQVSSKVN
+>non-ACP80
+TGCCIAGRLANLDDQNLTVAL
+>non-ACP82
+GSILGFLQIATVLTVLLLLLK
+>non-ACP84
+AARQIGSCLMRCRTLDTTSP
+>non-ACP86
+WGCRGRRWAFARVDGGSCHRRGAPTGSTSNQIR
+>non-ACP88
+YAKPGAVRSPAQILQWQVLPNTVPAKS
+>non-ACP90
+RMAGPWLSLHEARLLGTRGAAAPKAV
+>non-ACP92
+SISNRAAVPEHGVAPDAERL
+>non-ACP94
+PNFSMETWLLLV
+>non-ACP96
+PRPPSKTYRGAFQN
+>non-ACP98
+SVLVKGCQPFLSAPRECPGHPRVGT
+>non-ACP100
+LVTPPKALLKPLSIPNQ
+>non-ACP102
+KMQGSRMDEQRCS
+>non-ACP104
+VIADDLPPTCIRP
+>non-ACP106
+LPGGLRVLVQTGH
+>non-ACP108
+GWIWRWGWGRRCLGRPGLPGPGPGPATPLFLLLL
+>non-ACP110
+RGIRGSSAARPSGRRRDPAGRTTETGFNIFTQHD
+>non-ACP112
+QQEKEFLESYPQNCPPDALPGTPGNLD
+>non-ACP114
+APARRVLQVKRVMQESSLSPAHL
+>non-ACP116
+KVAPGGPTGYPGNLTAEQEQKLGELKMILL
+>non-ACP118
+FLASYPQKCPAGSLPGTPGNTDE
+>non-ACP120
+MDAKARNCLLQHREALEKDIKTSY
+>non-ACP122
+ASRQLLVAPPEAL
+>non-ACP124
+MISNGIGTVTTGKRSMCLFPLLLIGLWGC
+>non-ACP126
+MTLRNFGMGKRSIEDRVQEEARCLVEELRKTNASPC
+>non-ACP128
+AVFGLGGVGLSVIMGCKAAGASRIIAVDIN
+>non-ACP130
+PNAKQSILQKNPDDVVIVAAYRTA
+>non-ACP132
+AMELLLTATIFYLVLWVVKAFRLQVPKGLKSPPGP
+>non-ACP134
+LLAAGFCPAVLCH
+>non-ACP136
+AASVNDEQHQRIIKYGRALVLDIVEQ
+>non-ACP138
+IARLREDGIQKRVIQEGRGELPDFQDG
+>non-ACP140
+FIVVMNILALTLPFLAAEVQN
+>non-ACP142
+CQNGRRANRTVRFARTA
+>non-ACP144
+WVTVRSQQRGLFPAI
+>non-ACP146
+LLRSCPLQGSPGRPRSV
+>non-ACP148
+LNDGHFMPVLGFGTYAPPEVPRNRAVEV
+>non-ACP150
+HLGRPSAPTIVAQPVSGLASPASFQPEQFQYTLDNNVLT
+>non-ACP152
+RPEPGGCCCRRTVRANGC
+>non-ACP154
+SWVEENRASFQPPVCNKLMHR
+>non-ACP156
+VFHRVRWAPELGASLG
+>non-ACP158
+RAKVLTLDGMNPRVRRVEYAVRGPIVQRALELEQELRQ
+>non-ACP160
+LLQRARLAEQAERYDDMASAMKAVTELNEPLS
+>non-ACP162
+ALIQKLNSDPQFVLAQNVGTTHDLLDICLKRATVQRA
+>non-ACP164
+AALPMLWTGLVLLGLLGFPQTPAQGHDTVQPNFQQ
+>non-ACP166
+QRRQNDSSVFLAIMVAAAVES
+>non-ACP168
+CNAPGCGQRFTNEDHLAVHKHKHEMTLKFGPARTDS
+>non-ACP170
+LVLLTVQNSALILTLNYSRIMPGYD
+>non-ACP172
+TVLSPPQRFKRILQAMMLAVAVV
+>non-ACP174
+ISRGLLLLAALCCLAPSFL
+>non-ACP176
+VAGTESAQGPPGPAASLELWLNKATDPS
+>non-ACP178
+QYLRIRTVQPEPDYGAAV
+>non-ACP180
+ASPTQTPPTTSTIRVARRSRVALVAM
+>non-ACP182
+TIWRNQHTYKMATSASANLSKIVKKNYMELPQDGKVQ
+>non-ACP184
+LSITRGLLLLAALCCLAPIS
+>non-ACP186
+ILLSIWRQSSGRGKLPPGPIPLPIIGNIFQ
+>non-ACP188
+LLLLSWVALGPRSLEGADPGTPGEAEGPACP
+>non-ACP190
+LRVKRAMQEASFMPPLLPPAAHQRFSTVPAVP
+>non-ACP192
+GLLLLAGLCCLVFGIMAEDAQVAQGPSQQI
+>non-ACP194
+RHVGLLCATGPQRWRF
+>non-ACP196
+AAVALARPKPPLRHQEHLQNEPDS
+>non-ACP198
+SRVNDQSQASRNGLKGKVLTLDTMNPCV
+>non-ACP200
+AAALGPGVLQATRAFHTGQPRLAPLPPLPEYGGK
+>non-ACP202
+LCTSGLWTAQASTNESSNSHRGLAPTNV
+>non-ACP204
+PAIQPVLSGLSRIVNGEEA
+>non-ACP206
+GCQASLSTAQERLGHPGVPTREGVR
+>non-ACP208
+RKVLILTLVVAACGFVLWSSNGR
+>non-ACP210
+GRVRSRCPGPALLLLLALAARPALAGPPAAALQ
+>non-ACP212
+CRITKPALLVLNQETAKVVQT
+>non-ACP214
+KAEVCMAVPWLSLQ
+>non-ACP216
+SHLELNNGTKMPTLGLGT
+>non-ACP218
+LLLPEAAAERDAREKLALWDRRPDTTAPL
+>non-ACP220
+LLALSLVLLYRYATYSHGFFKKLGIPGPKPLPLFGNVLS
+>non-ACP222
+LLSLWRQSSGRGKLPPGPTPLPVIGNILQIGIKD
+>non-ACP224
+AFKSMEVANFYYEADCLAAAYGGKAAPAAPPADRPGPR
+>non-ACP226
+SLFWAARPLQRCGQLVRMAIRAQH
+>non-ACP228
+MRPPRTLTSTATMSALSTSMPMEIDDVMDEDAVNGQA
+>non-ACP230
+LLSLIGFCWAQYDP
+>non-ACP232
+LWARSKNDQLRISFPPGLCWG
+>non-ACP234
+PQGFDVDRDAKKLNKACKGMGTNEAAIIEILSG
+>non-ACP236
+IFCLILWVVKAWQPRLPKGLKSPPGPWGWPLLG
+>non-ACP238
+LDAASPGPLALLGLLFAATLLLSALFLL
+>non-ACP240
+VTLLFKLYCLA
+>non-ACP242
+ATRAAAARLVGTAASRTPAAARH
+>non-ACP244
+RNKLDLETLTDILEHQIR
+>non-ACP246
+RRLVLQARTYAQAAASPAPAAGPGQMSFTFASPTQVFF
+>non-ACP248
+PGRSRSAADDINPAPANM
+>non-ACP250
+LLSALTLETWVLLAVILVLLYRLG
+>non-ACP252
+VMGHGLCPQGARAKAAIPAALRDHEST
+>non-ACP254
+FLVSIAGLLYALVQLGQPCDCLPPLRAAA
+>non-ACP256
+VRSVRAAVGGLRAISAPSAPCLPRPWGLRAG
+>non-ACP258
+RGGCWPRGLQQLLVPGG
+>non-ACP260
+APATPPRPLKRKKLQFTDVTPESSP
+>non-ACP262
+EQAERYDDMAAAMKAVTEQGHELSNEERNL
+>non-ACP264
+MPNDPSDNQLK
+>non-ACP266
+TELLLAITVFCLGFWVVRALRTQVP
+>non-ACP268
+LTADLLGAPFFTLPKELQLALLERQTVFL
+>non-ACP270
+GHGRLVEIQGRLGVRIER
+>non-ACP272
+LPFKLLLFVLLDGWTRLTH
+>non-ACP274
+QALWLVLVLSMPPVLVAAVVGTLVSLVQ
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Global_Descriptors/.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Global_Descriptors/.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+""
+0
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Global_Descriptors/PDAUG_Peptide_Global_Descriptors.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Global_Descriptors/PDAUG_Peptide_Global_Descriptors.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,117 @@
+from modlamp.descriptors import *
+import os
+import pandas as pd

+def Descriptor_calcultor(DesType, inputfile, ph, amide,OutFile ):
+
+    list_pep_name = []
+    f = open(inputfile)
+    lines = f.readlines()
+    
+    for line in lines:
+        if ">" in line:
+            pass
+        else:
+            list_pep_name.append(line.strip('\n'))
+
+    desc = GlobalDescriptor(list_pep_name)
+
+    if DesType == "Length":
+        desc.length()
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "Weight":
+
+        desc.calculate_MW()
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "Charge":
+        desc.calculate_charge(ph=int(ph), amide=amide)
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "ChargeDensity":
+        desc.charge_density(ph=int(ph), amide=amide)
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "IsoelectricPoint":
+        desc.isoelectric_point(amide=amide)
+        df = desc.descriptor
+        dfN = desc.featurenames

+    elif DesType == "InstabilityIndex":
+        desc.instability_index()
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "Aromaticity":
+        desc.aromaticity()
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "AliphaticIndex":
+        desc.aliphatic_index()
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "BomanIndex":
+        desc.boman_index()
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "HydrophobicRatio":
+        desc.hydrophobic_ratio()
+        df = desc.descriptor
+        dfN = desc.featurenames
+
+    elif DesType == "All":
+        desc.calculate_all(ph=int(ph), amide=amide)
+        df = desc.descriptor
+        dfN = desc.featurenames
+    else:
+        pass
+
+    df = desc.descriptor
+    dfN = desc.featurenames
+    dfOut = pd.DataFrame(df,columns=dfN)
+
+    dfOut.to_csv(OutFile, index=False, sep='\t')
+
+if __name__=="__main__":
+
+    import argparse
+    
+    parser = argparse.ArgumentParser()
+    
+    parser.add_argument("-t", "--DesType",
+                        required=True,
+                        default=None,
+                        help="Descriptors Type")
+                        
+    parser.add_argument("-i", "--InFile",
+                        required=True,
+                        default=None,
+                        help="Peptide File")   
+
+    parser.add_argument("-p", "--Ph",
+                        required=False,
+                        default=7.0,
+                        help="Ph 0-14") 
+
+    parser.add_argument("-a", "--Amide",
+                        required=False,
+                        default="True",
+                        help="True or False")   
+
+    parser.add_argument("-O", "--OutFile",
+                        required=False,
+                        default="out.tsv",
+                        help="True or False") 
+
+                          
+    args = parser.parse_args()
+
+    Descriptor_calcultor(args.DesType, args.InFile, args.Ph, args.Amide, args.OutFile)
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Global_Descriptors/test-data/out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Global_Descriptors/test-data/out.tsv Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,139 @@\n+Length\tMW\tCharge\tChargeDensity\tpI\tInstabilityInd\tAromaticity\tAliphaticInd\tBomanInd\tHydrophRatio\n+33.0\t3833.74\t3.795\t0.0009898949850537595\t10.03125\t63.451515151515146\t0.09090909090909091\t115.15151515151516\t0.5603030303030305\t0.5454545454545454\n+34.0\t3727.11\t-1.001\t-0.0002685727011008529\t4.43505859375\t43.670588235294126\t0.08823529411764706\t43.23529411764706\t1.9917647058823529\t0.3235294117647059\n+18.0\t1788.15\t2.996\t0.0016754746525738892\t13.55859375\t40.550000000000004\t0.05555555555555555\t108.33333333333331\t-0.5277777777777778\t0.4444444444444444\n+28.0\t3036.42\t1.094\t0.00036029271312927727\t9.43701171875\t49.610714285714295\t0.07142857142857142\t70.0\t1.4278571428571425\t0.35714285714285715\n+21.0\t2199.45\t-1.07\t-0.00048648525767805596\t3.9296875\t29.85714285714286\t0.0\t111.42857142857142\t1.0095238095238097\t0.42857142857142855\n+34.0\t3689.37\t3.864\t0.0010473332845445157\t9.955322265625\t20.40882352941177\t0.029411764705882353\t97.3529411764706\t1.4858823529411767\t0.35294117647058826\n+13.0\t1401.6\t-0.069\t-4.922945205479453e-05\t6.28125\t93.56923076923078\t0.0\t97.6923076923077\t1.6992307692307689\t0.38461538461538464\n+26.0\t2978.24\t-1.0\t-0.0003357687761899646\t4.58935546875\t51.846153846153854\t0.11538461538461539\t68.07692307692308\t2.5303846153846155\t0.38461538461538464\n+21.0\t2531.74\t-0.999\t-0.00039459028178248954\t4.666015625\t24.804761904761904\t0.047619047619047616\t79.04761904761904\t4.30047619047619\t0.3333333333333333\n+30.0\t3671.28\t5.025\t0.0013687324311956594\t11.23828125\t89.66033333333333\t0.2\t74.66666666666666\t1.4336666666666662\t0.36666666666666664\n+18.0\t1797.22\t1.929\t0.0010733243565061595\t10.03125\t1.8055555555555547\t0.0\t168.33333333333331\t-0.7383333333333333\t0.6111111111111112\n+37.0\t4489.59\t3.96\t0.0008820404535826211\t10.2333984375\t44.878378378378386\t0.16216216216216217\t142.43243243243245\t-0.7545945945945945\t0.5675675675675675\n+25.0\t2504.82\t1.028\t0.0004104087319647719\t8.76171875\t90.01199999999999\t0.04\t51.2\t0.8763999999999998\t0.36\n+24.0\t2793.81\t1.194\t0.00042737337184704755\t9.7275390625\t64.35000000000001\t0.041666666666666664\t20.416666666666664\t5.572083333333334\t0.08333333333333333\n+37.0\t4180.030000000001\t2.996\t0.0007167412674071716\t11.2880859375\t42.77297297297297\t0.10810810810810811\t128.91891891891893\t-0.05243243243243245\t0.4594594594594595\n+24.0\t2705.2599999999998\t3.86\t0.0014268499146107953\t10.68359375\t56.52083333333335\t0.125\t101.66666666666666\t0.3158333333333334\t0.4583333333333333\n+13.0\t1428.75\t1.996\t0.0013970253718285214\t13.55078125\t63.938461538461546\t0.0\t164.6153846153846\t0.21999999999999995\t0.6153846153846154\n+20.0\t2481.99\t4.996\t0.0020129009383599455\t12.58203125\t27.415000000000003\t0.1\t126.5\t2.55\t0.5\n+38.0\t3846.5\t3.928\t0.0010211880930716235\t11.572265625\t67.88157894736841\t0.05263157894736842\t97.63157894736841\t0.15473684210526317\t0.42105263157894735\n+34.0\t3297.91\t4.997\t0.0015152020522088232\t12.58203125\t84.26764705882351\t0.0\t100.88235294117648\t0.6679411764705883\t0.47058823529411764\n+13.0\t1319.59\t1.095\t0.0008298031964473814\t12.25\t138.72307692307695\t0.0\t30.0\t-0.010769230769230812\t0.23076923076923078\n+19.0\t2324.8\t4.929\t0.00212018238128011\t11.94287109375\t140.16315789473683\t0.05263157894736842\t107.89473684210525\t3.7010526315789476\t0.42105263157894735\n+33.0\t3845.8\t6.996\t0.001819127359717094\t12.7998046875\t53.71212121212121\t0.06060606060606061\t174.54545454545456\t0.8466666666666666\t0.5757575757575758\n+13.0\t1523.62\t0.998\t0.0006550189679841431\t10.58203125\t52.04615384615385\t0.15384615384615385\t7.6923076923076925\t4.195384615384616\t0.23076923076923078\n+34.0\t3496.1\t1.996\t0.000570921884385458\t12.1005859375\t44.17941176470589\t0.058823529411764705\t123.23529411764706\t-0.060000000000000095\t0.47058823529411764\n+18.0\t2142.54\t4.996\t0.0023318117748093387\t13.80078125\t39.522222222222226\t0.05555555555555555\t81.1111111111111\t2.7783333333333338\t0.2777777777777778\n+28.0\t3162.91\t3.793\t0.0011992121179546684\t10.529296875\t88.95357142857144\t0.07142857142857142\t136.07142857142856\t-0.03678571428571437\t0.5714285714285714\n+17.0\t1756.0\t-1.001\t-0.0005700455580865603\t4.150390625\t87.4294'..b'34482758620689655\t101.37931034482759\t2.560344827586206\t0.41379310344827586\n+39.0\t4304.1900000000005\t5.092\t0.0011830332768767175\t10.71923828125\t-1.2307692307692295\t0.15384615384615385\t130.0\t-0.5758974358974357\t0.46153846153846156\n+34.0\t3621.3\t3.996\t0.0011034711291525142\t12.1552734375\t76.77647058823528\t0.029411764705882353\t123.23529411764707\t0.5847058823529411\t0.3235294117647059\n+38.0\t3944.43\t0.929\t0.00023552198923545357\t8.60546875\t37.489736842105266\t0.13157894736842105\t46.8421052631579\t1.0836842105263156\t0.4473684210526316\n+24.0\t2808.35\t5.027\t0.0017900190503320457\t12.5751953125\t30.070833333333336\t0.08333333333333333\t93.74999999999997\t1.8133333333333332\t0.5\n+37.0\t3970.48\t-2.999\t-0.0007553242932844392\t3.85400390625\t44.127027027027026\t0.0\t58.10810810810811\t2.005405405405405\t0.3783783783783784\n+14.0\t1624.91\t-0.072\t-4.431014640810875e-05\t5.90625\t26.992857142857144\t0.21428571428571427\t118.57142857142856\t-0.8014285714285715\t0.5\n+21.0\t2443.84\t2.929\t0.0011985236349351838\t11.2216796875\t68.41904761904762\t0.14285714285714285\t79.04761904761904\t1.4666666666666668\t0.3333333333333333\n+33.0\t3489.99\t0.932\t0.0002670494757864636\t8.7001953125\t45.63939393939393\t0.030303030303030304\t80.0\t1.6799999999999993\t0.3939393939393939\n+33.0\t3753.61\t4.928\t0.001312869477649516\t11.6767578125\t48.21818181818182\t0.15151515151515152\t115.15151515151516\t-0.79030303030303\t0.3939393939393939\n+28.0\t2794.43\t-0.004\t-1.4314189297996373e-06\t6.5\t25.335714285714285\t0.07142857142857142\t188.57142857142856\t-2.130357142857143\t0.7142857142857143\n+11.0\t1282.6399999999999\t1.927\t0.001502370111644733\t9.6748046875\t-2.499999999999997\t0.18181818181818182\t177.2727272727273\t-1.957272727272727\t0.7272727272727273\n+23.0\t2246.54\t5.095\t0.002267932019906167\t13.86328125\t27.30434782608696\t0.0\t73.04347826086956\t2.0630434782608695\t0.5217391304347826\n+18.0\t2206.5099999999998\t0.098\t4.4414029394836193e-05\t7.703125\t31.249999999999996\t0.0\t129.99999999999997\t3.2727777777777773\t0.3333333333333333\n+38.0\t4012.57\t3.995\t0.0009956212601898533\t12.4033203125\t88.79473684210524\t0.13157894736842105\t59.473684210526315\t0.9107894736842105\t0.47368421052631576\n+18.0\t1839.01\t0.997\t0.0005421395207203876\t10.58203125\t94.75\t0.0\t43.888888888888886\t2.883888888888888\t0.3333333333333333\n+24.0\t2682.34\t0.996\t0.00037131758091815356\t9.7353515625\t0.7625000000000008\t0.08333333333333333\t223.33333333333331\t-1.78\t0.6666666666666666\n+27.0\t2757.17\t2.128\t0.0007718058734136814\t10.0205078125\t37.24444444444445\t0.0\t76.29629629629629\t1.32\t0.4444444444444444\n+29.0\t3012.65\t0.86\t0.00028546296449969295\t8.0888671875\t55.06896551724138\t0.06896551724137931\t144.82758620689654\t-0.8844827586206897\t0.6206896551724138\n+31.0\t3141.71\t5.928\t0.0018868705259237803\t12.69970703125\t65.65806451612903\t0.03225806451612903\t97.74193548387098\t1.1216129032258066\t0.45161290322580644\n+17.0\t1793.12\t2.928\t0.0016329080039261176\t12.1005859375\t65.27058823529413\t0.058823529411764705\t85.88235294117648\t0.8123529411764705\t0.29411764705882354\n+25.0\t2761.2\t3.997\t0.001447559032304795\t11.4951171875\t90.212\t0.04\t50.8\t2.4636\t0.24\n+30.0\t3435.68\t-3.897\t-0.0011342732734131234\t4.270751953125\t50.57\t0.03333333333333333\t52.33333333333333\t3.3416666666666663\t0.3333333333333333\n+11.0\t1257.3799999999999\t-0.003\t-2.385913566304538e-06\t6.6875\t51.97272727272727\t0.0\t35.45454545454546\t3.4490909090909088\t0.18181818181818182\n+25.0\t2845.46\t1.93\t0.0006782734601786705\t10.59765625\t30.988000000000007\t0.12\t148.0\t-0.3963999999999999\t0.6\n+29.0\t3257.87\t-0.001\t-3.069490188374613e-07\t6.9375\t41.60689655172414\t0.10344827586206896\t141.3793103448276\t-0.07000000000000005\t0.5517241379310345\n+18.0\t2044.3799999999999\t3.097\t0.0015148847083223276\t12.10009765625\t38.794444444444444\t0.0\t118.88888888888889\t2.8877777777777776\t0.3333333333333333\n+19.0\t2281.79\t2.095\t0.0009181388296030749\t11.400390625\t15.952631578947368\t0.15789473684210525\t158.94736842105263\t-0.45894736842105277\t0.5263157894736842\n+28.0\t2915.63\t0.996\t0.0003416071312203537\t12.25\t45.892857142857146\t0.03571428571428571\t191.07142857142856\t-2.048571428571429\t0.6785714285714286\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Global_Descriptors/test-data/test.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Global_Descriptors/test-data/test.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>non-ACP0
+MTISLIWGIAMVVCCCIWVIFDRRRRKAGEPPL
+>non-ACP2
+MFATPLRQPTNASGARPAVSMDGQETPFQYEITD
+>non-ACP4
+LLWRKVAGATVGPGPVPA
+>non-ACP6
+DSPDPMNGASSNALIAKMNSAKLLYQHY
+>non-ACP8
+NNQEVIDAISQAISQTPGCVL
+>non-ACP10
+KKVVEKNADPETTLLVYLRRKLGLCGTKLGCGEG
+>non-ACP12
+CSRLLPSLAQEEG
+>non-ACP14
+KNDFAALQAKLDADAAEIEKWWSDSR
+>non-ACP16
+VDREQLVQKARLAEQAERYDD
+>non-ACP18
+RPLRRVVLFYQGKLCSMAGNFWQSSHYLQW
+>non-ACP20
+GAAGERKLCLLSLLLIGA
+>non-ACP22
+MFRKLLKMWILLRPTHWLILIALCAVTCAGYWLLWSE
+>non-ACP24
+HLRGPADSGWMPQAAPCLSGAPQAS
+>non-ACP26
+NNPNNSNSHLRPHAYNNSRRDDSD
+>non-ACP28
+VVILASLSVMFLVSLWQQKIRERLPPGPTPLPFIGNY
+>non-ACP30
+ICLSCLISFFLWNQNRAKGKLPPG
+>non-ACP32
+VVMNSLRVILQAS
+>non-ACP34
+ARPRLDLQLVQRFVRIQKVF
+>non-ACP36
+MLAKGLSLRSVLAKGCQPFLSPTWQSSVLATGGGANIS
+>non-ACP38
+AAGLPGAALPLRKRPLRAPSPEPAAPRGAAGLVV
+>non-ACP40
+PPMPSAPPVHPPP
+>non-ACP42
+SCPIDKRRPLIAFLRRLRD
+>non-ACP44
+RLGLWASGLILILGFLKLLRLLLRRQRLARAMD
+>non-ACP46
+FSPQRDRFQAEGS
+>non-ACP48
+GTLWALVFLGILVGMVVPSPAGTRANNTLLDSRG
+>non-ACP50
+MNRLLQKGTSLVPSWRTR
+>non-ACP52
+MTTSLIWGIAIAACCCLWLILGIRRRQT
+>non-ACP54
+ATLANGMSLQPPLEEVS
+>non-ACP56
+PLTATNSGLAVNN
+>non-ACP58
+VRACHKVCRCLLSGFGGRVDAGQPELLTER
+>non-ACP60
+TAGILLLLLLGTLEGS
+>non-ACP62
+MEPSILLLLALLVGFLLLLVRGH
+>non-ACP64
+MKNCFQLLCNLKVPAAGFKNTVKS
+>non-ACP66
+SVIHTQAHASGLQQVPQLVPAGPGGGGKAVAPSKQSK
+>non-ACP68
+KPLGLLKPSSLMKVSGRFKAHQDA
+>non-ACP70
+ARTLNNKLSLSKPKFSGFT
+>non-ACP72
+LLLVIIWTLFGPSGLGEELLSLSLASLLPAPASPGPP
+>non-ACP74
+WPGILVGGARVASCRYPALGPRLA
+>non-ACP76
+RSVKGLVALITGGASGL
+>non-ACP78
+AAAALRARILQVSSKVN
+>non-ACP80
+TGCCIAGRLANLDDQNLTVAL
+>non-ACP82
+GSILGFLQIATVLTVLLLLLK
+>non-ACP84
+AARQIGSCLMRCRTLDTTSP
+>non-ACP86
+WGCRGRRWAFARVDGGSCHRRGAPTGSTSNQIR
+>non-ACP88
+YAKPGAVRSPAQILQWQVLPNTVPAKS
+>non-ACP90
+RMAGPWLSLHEARLLGTRGAAAPKAV
+>non-ACP92
+SISNRAAVPEHGVAPDAERL
+>non-ACP94
+PNFSMETWLLLV
+>non-ACP96
+PRPPSKTYRGAFQN
+>non-ACP98
+SVLVKGCQPFLSAPRECPGHPRVGT
+>non-ACP100
+LVTPPKALLKPLSIPNQ
+>non-ACP102
+KMQGSRMDEQRCS
+>non-ACP104
+VIADDLPPTCIRP
+>non-ACP106
+LPGGLRVLVQTGH
+>non-ACP108
+GWIWRWGWGRRCLGRPGLPGPGPGPATPLFLLLL
+>non-ACP110
+RGIRGSSAARPSGRRRDPAGRTTETGFNIFTQHD
+>non-ACP112
+QQEKEFLESYPQNCPPDALPGTPGNLD
+>non-ACP114
+APARRVLQVKRVMQESSLSPAHL
+>non-ACP116
+KVAPGGPTGYPGNLTAEQEQKLGELKMILL
+>non-ACP118
+FLASYPQKCPAGSLPGTPGNTDE
+>non-ACP120
+MDAKARNCLLQHREALEKDIKTSY
+>non-ACP122
+ASRQLLVAPPEAL
+>non-ACP124
+MISNGIGTVTTGKRSMCLFPLLLIGLWGC
+>non-ACP126
+MTLRNFGMGKRSIEDRVQEEARCLVEELRKTNASPC
+>non-ACP128
+AVFGLGGVGLSVIMGCKAAGASRIIAVDIN
+>non-ACP130
+PNAKQSILQKNPDDVVIVAAYRTA
+>non-ACP132
+AMELLLTATIFYLVLWVVKAFRLQVPKGLKSPPGP
+>non-ACP134
+LLAAGFCPAVLCH
+>non-ACP136
+AASVNDEQHQRIIKYGRALVLDIVEQ
+>non-ACP138
+IARLREDGIQKRVIQEGRGELPDFQDG
+>non-ACP140
+FIVVMNILALTLPFLAAEVQN
+>non-ACP142
+CQNGRRANRTVRFARTA
+>non-ACP144
+WVTVRSQQRGLFPAI
+>non-ACP146
+LLRSCPLQGSPGRPRSV
+>non-ACP148
+LNDGHFMPVLGFGTYAPPEVPRNRAVEV
+>non-ACP150
+HLGRPSAPTIVAQPVSGLASPASFQPEQFQYTLDNNVLT
+>non-ACP152
+RPEPGGCCCRRTVRANGC
+>non-ACP154
+SWVEENRASFQPPVCNKLMHR
+>non-ACP156
+VFHRVRWAPELGASLG
+>non-ACP158
+RAKVLTLDGMNPRVRRVEYAVRGPIVQRALELEQELRQ
+>non-ACP160
+LLQRARLAEQAERYDDMASAMKAVTELNEPLS
+>non-ACP162
+ALIQKLNSDPQFVLAQNVGTTHDLLDICLKRATVQRA
+>non-ACP164
+AALPMLWTGLVLLGLLGFPQTPAQGHDTVQPNFQQ
+>non-ACP166
+QRRQNDSSVFLAIMVAAAVES
+>non-ACP168
+CNAPGCGQRFTNEDHLAVHKHKHEMTLKFGPARTDS
+>non-ACP170
+LVLLTVQNSALILTLNYSRIMPGYD
+>non-ACP172
+TVLSPPQRFKRILQAMMLAVAVV
+>non-ACP174
+ISRGLLLLAALCCLAPSFL
+>non-ACP176
+VAGTESAQGPPGPAASLELWLNKATDPS
+>non-ACP178
+QYLRIRTVQPEPDYGAAV
+>non-ACP180
+ASPTQTPPTTSTIRVARRSRVALVAM
+>non-ACP182
+TIWRNQHTYKMATSASANLSKIVKKNYMELPQDGKVQ
+>non-ACP184
+LSITRGLLLLAALCCLAPIS
+>non-ACP186
+ILLSIWRQSSGRGKLPPGPIPLPIIGNIFQ
+>non-ACP188
+LLLLSWVALGPRSLEGADPGTPGEAEGPACP
+>non-ACP190
+LRVKRAMQEASFMPPLLPPAAHQRFSTVPAVP
+>non-ACP192
+GLLLLAGLCCLVFGIMAEDAQVAQGPSQQI
+>non-ACP194
+RHVGLLCATGPQRWRF
+>non-ACP196
+AAVALARPKPPLRHQEHLQNEPDS
+>non-ACP198
+SRVNDQSQASRNGLKGKVLTLDTMNPCV
+>non-ACP200
+AAALGPGVLQATRAFHTGQPRLAPLPPLPEYGGK
+>non-ACP202
+LCTSGLWTAQASTNESSNSHRGLAPTNV
+>non-ACP204
+PAIQPVLSGLSRIVNGEEA
+>non-ACP206
+GCQASLSTAQERLGHPGVPTREGVR
+>non-ACP208
+RKVLILTLVVAACGFVLWSSNGR
+>non-ACP210
+GRVRSRCPGPALLLLLALAARPALAGPPAAALQ
+>non-ACP212
+CRITKPALLVLNQETAKVVQT
+>non-ACP214
+KAEVCMAVPWLSLQ
+>non-ACP216
+SHLELNNGTKMPTLGLGT
+>non-ACP218
+LLLPEAAAERDAREKLALWDRRPDTTAPL
+>non-ACP220
+LLALSLVLLYRYATYSHGFFKKLGIPGPKPLPLFGNVLS
+>non-ACP222
+LLSLWRQSSGRGKLPPGPTPLPVIGNILQIGIKD
+>non-ACP224
+AFKSMEVANFYYEADCLAAAYGGKAAPAAPPADRPGPR
+>non-ACP226
+SLFWAARPLQRCGQLVRMAIRAQH
+>non-ACP228
+MRPPRTLTSTATMSALSTSMPMEIDDVMDEDAVNGQA
+>non-ACP230
+LLSLIGFCWAQYDP
+>non-ACP232
+LWARSKNDQLRISFPPGLCWG
+>non-ACP234
+PQGFDVDRDAKKLNKACKGMGTNEAAIIEILSG
+>non-ACP236
+IFCLILWVVKAWQPRLPKGLKSPPGPWGWPLLG
+>non-ACP238
+LDAASPGPLALLGLLFAATLLLSALFLL
+>non-ACP240
+VTLLFKLYCLA
+>non-ACP242
+ATRAAAARLVGTAASRTPAAARH
+>non-ACP244
+RNKLDLETLTDILEHQIR
+>non-ACP246
+RRLVLQARTYAQAAASPAPAAGPGQMSFTFASPTQVFF
+>non-ACP248
+PGRSRSAADDINPAPANM
+>non-ACP250
+LLSALTLETWVLLAVILVLLYRLG
+>non-ACP252
+VMGHGLCPQGARAKAAIPAALRDHEST
+>non-ACP254
+FLVSIAGLLYALVQLGQPCDCLPPLRAAA
+>non-ACP256
+VRSVRAAVGGLRAISAPSAPCLPRPWGLRAG
+>non-ACP258
+RGGCWPRGLQQLLVPGG
+>non-ACP260
+APATPPRPLKRKKLQFTDVTPESSP
+>non-ACP262
+EQAERYDDMAAAMKAVTEQGHELSNEERNL
+>non-ACP264
+MPNDPSDNQLK
+>non-ACP266
+TELLLAITVFCLGFWVVRALRTQVP
+>non-ACP268
+LTADLLGAPFFTLPKELQLALLERQTVFL
+>non-ACP270
+GHGRLVEIQGRLGVRIER
+>non-ACP272
+LPFKLLLFVLLDGWTRLTH
+>non-ACP274
+QALWLVLVLSMPPVLVAAVVGTLVSLVQ
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Length_Distribution/PDAUG_Peptide_Length_Distribution.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Length_Distribution/PDAUG_Peptide_Length_Distribution.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,31 @@
+import matplotlib.pyplot as plt
+import Bio
+from Bio import SeqIO
+import os
+
+
+def LegnthDestribution(InFile, OutFile):
+
+
+    sizes = [len(rec.seq) for rec in SeqIO.parse(InFile, "fasta")]
+
+    plt.hist(sizes, bins=20)
+    plt.title("%i Negative bacteriocin sequences\nLengths %i to %i" \
+                % (len(sizes),min(sizes),max(sizes)))
+    plt.xlabel("Sequence length (bp)")
+    plt.ylabel("Count")
+
+    plt.savefig(OutFile)
+
+
+
+if __name__=="__main__":
+
+    import argparse
+    
+    parser = argparse.ArgumentParser()
+    
+    parser.add_argument("-I", "--InFile", required=True, default=None, help="Input file name")
+    parser.add_argument("-O", "--OutFile", required=False, default="Out.png", help="Input file name")
+    args = parser.parse_args()
+    LegnthDestribution(args.InFile, args.OutFile)
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Length_Distribution/test-data/out.png
b
Binary file PDAUG_Peptide_Length_Distribution/test-data/out.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Length_Distribution/test-data/positive.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Length_Distribution/test-data/positive.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLFDIIKKIAESI
+>ACP4
+GLLDIVKKVVGAFGSL
+>ACP6
+GLFDIVKKVVGALGSL
+>ACP8
+GLFDIVKKVVGTLAGL
+>ACP10
+GLFDIAKKVIGVIGSL
+>ACP12
+GLFDIVKKIAGHIAGSI
+>ACP14
+GLFDIVKKIAGHIVSSI
+>ACP16
+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF
+>ACP18
+HGVSGHGQHGVHG
+>ACP20
+FKCRRWQWRMKKLGAPSITCVRRAF
+>ACP22
+KWKLFKKIKFLHSAKKF
+>ACP24
+KSSAYSLQMGATAIKQVKKLFKKWGW
+>ACP26
+GIGTKILGGVKTALKGALKELASTYAN
+>ACP28
+GIGGKILSGLKTALKGAAKELASTYLH
+>ACP30
+GIGGVLLSAGKAALKGLAKVLAEKYAN
+>ACP32
+SIGAKILGGVKTFFKGALKELASTYLQ
+>ACP34
+FLPLLAGLAANFLPTIICKISYKC
+>ACP36
+FVQWFSKFLGRIL
+>ACP38
+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL
+>ACP40
+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK
+>ACP42
+KWKLFKKIEKVGQNIRDGIIKAGPAVAVVGQATQIAK
+>ACP44
+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK
+>ACP46
+GIGKFLHSAKKFGKAFVGEIMNS
+>ACP48
+GIGAVLKVLTTGLPALISWIKRKRQQ
+>ACP50
+ALWKNMLKGIGKLAGQAALGAVKTLVGAE
+>ACP52
+ACYCRIPACIAGERRYGTCIYQGRLWAFCC
+>ACP54
+ECRRLCYKQRCVTYCRGR
+>ACP56
+LKLKSIVSWAKKVL
+>ACP58
+KWCFRVCYRGICYRRCR
+>ACP60
+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK
+>ACP62
+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP64
+GLLSVLGSVVKHVIPHVVPVIAEHL
+>ACP66
+GLFKVLGSVAKHLLPHVAPVIAEK
+>ACP68
+GLFGVLGSIAKHVLPHVVPVIAEK
+>ACP70
+GLFVGVLAKVAAHVVPAIAEHF
+>ACP72
+GLFVGLAKVAAHNNPAIAEHFQA
+>ACP74
+GFVDFLKKVAGTIANVVT
+>ACP76
+GLLQTIKEKLESLESLAKGIVSGIQA
+>ACP78
+TRSSRAGLQFPVGRVHRLLRK
+>ACP80
+FFGWLIKGAIHAGKAIHGLIHRRRH
+>ACP82
+GLFDVIKKVASVIGGL
+>ACP84
+GLFDIIKKVASVVGGL
+>ACP86
+GRFKRFRKKFKKLFKKLSPVIPLLHLG
+>ACP88
+GGLRSLGRKILRAWKKYGPIIVPIIRIG
+>ACP90
+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP
+>ACP92
+GLLGPLLKIAAKVGSNLL
+>ACP94
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP96
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP98
+FFHHIFRGIVHVGKTIHRLVTG
+>ACP100
+KLAKLAKKLAKLAK
+>ACP102
+KTCENLADTFRGPCFATSNC
+>ACP104
+IDWKKLLDAAKQIL
+>ACP106
+FLIGMTQGLICLITRKC
+>ACP108
+ILPILSLIGGLLGK
+>ACP110
+GLLGLLGSVVSHVVPAIVGHF
+>ACP112
+GLLGLLGSVVSHVLPAITQHL
+>ACP114
+GIKCRFCCGCCTPGICGVCCRF
+>ACP116
+QSHLSLCRWCCNCCRSNKGC
+>ACP118
+ILGPVISTIGGVLGGLLKNL
+>ACP120
+FLPILASLAAKFGPKLFCLVTKKC
+>ACP122
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP124
+LLGMIPLAISAISALSKL
+>ACP126
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP128
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP130
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP132
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP134
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP136
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP138
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP140
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP142
+GFKDLLKGAAKALVKTVLF
+>ACP144
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP146
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP148
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP150
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP152
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP154
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP156
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP158
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP160
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP162
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP164
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP166
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP168
+VNWKKVLGKIIKVAK
+>ACP170
+VNWKKILGKIIKVAK
+>ACP172
+FFSLLPSLIGGLVSAIK
+>ACP174
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP176
+KWKLFKKIPKFLHLAKKF
+>ACP178
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
+>ACP180
+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP182
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP184
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP186
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP188
+FVDLKKIANIINSIFGK
+>ACP190
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP192
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP194
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP196
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP198
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP200
+GMWSKILGHLIR
+>ACP202
+GKWMSLLKHILK
+>ACP204
+GFGMALKLLKKVL
+>ACP206
+GTGLPMSERRKIMLMMR
+>ACP208
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP210
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP212
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP214
+GDACGETCFTGICFTAGCSCNPWPTCTRN
+>ACP216
+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP218
+IPCGESCVWIPCITAIAGCSCKNKVCYT
+>ACP220
+AIPCGESCVWIPCISTVIGCSCSNKVCYR
+>ACP222
+GEYCGESCYLIPCFTPGCYCVSRQCVNKN
+>ACP224
+IPCGESCVWIPCISGMFGCSCKDKVCYS
+>ACP226
+FLGWLFKWASK
+>ACP228
+FLKWLFKWAKK
+>ACP230
+KWKSFLKTFKSAKKTVLHTALKAISS
+>ACP232
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP234
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP236
+KWKLFKKIGAVLKVL
+>ACP238
+GACFSIAHECGA
+>ACP240
+TCCATGACGTTCCTGACGTT
+>ACP242
+KRFKQDGGASHASPASS
+>ACP244
+KRAKAAGGWSHWSPWSSC
+>ACP246
+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
+>ACP248
+FLGALFKVASKVLPSVKCAITKKC
+>ACP250
+GIGKFLKKAKKFGKAFVKILKK
+>ACP252
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP254
+VECYGPNRPQF
+>ACP256
+KRFKQDGGWSHWSPWSSC
+>ACP258
+RQVFQVAYIIIKA
+>ACP260
+KAFDITYVRLKF
+>ACP262
+DFKLFAVTIKYR
+>ACP264
+DFKLFAVYIKYR
+>ACP266
+WHSDMEWWYLLG
+>ACP268
+HTMYYHHYQHHL
+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Ngrams/PDAUG_Peptide_Ngrams.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Ngrams/PDAUG_Peptide_Ngrams.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,82 @@
+import matplotlib
+matplotlib.use('Agg')
+import os
+import sys
+sys.path.insert(0, os.path.abspath('..'))
+import quantiprot 
+from quantiprot.utils.io import load_fasta_file
+from quantiprot.utils.feature import Feature, FeatureSet
+from quantiprot.metrics.aaindex import get_aa2hydropathy
+from quantiprot.metrics.basic import identity
+from quantiprot.metrics.ngram import pattern_match, pattern_count
+from quantiprot.analysis.ngram import ngram_count
+from quantiprot.analysis.ngram import zipf_law_fit
+from matplotlib import pyplot as plt
+
+
+def Run_ngrams(fasta1, fasta2, OutFile ):
+
+    alphasyn_seq = load_fasta_file(fasta1)
+    amyload_pos_seq = load_fasta_file(fasta2)
+
+    fs_aa = FeatureSet("aa patterns")
+    fs_aa.add(identity)
+    fs_aa.add(pattern_match, pattern='VT', padded=True)
+    fs_aa.add(pattern_count, pattern='VT')
+
+    result_seq = fs_aa(alphasyn_seq)
+
+    fs_hp = FeatureSet("hydropathy patterns")
+    fs_hp.add(Feature(get_aa2hydropathy()))
+    fs_hp.add(Feature(get_aa2hydropathy()).then(pattern_match, pattern=[0.0, 2.0],
+                                                metric='taxi', radius=1.0))
+    result_seq2 = fs_hp(alphasyn_seq)
+    result_freq = ngram_count(alphasyn_seq, n=2)
+    result_fit = zipf_law_fit(amyload_pos_seq, n=3, verbose=True)
+
+    counts = sorted(result_fit["ngram_counts"], reverse=True)
+    ranks = range(1, len(counts)+1)
+
+    slope = result_fit["slope"]
+    harmonic_num = sum([rank**-slope for rank in ranks])
+    fitted_counts = [(rank**-slope) / harmonic_num * sum(counts) for rank in ranks]
+
+    plt.plot(ranks, counts, 'k', label="empirical")
+    plt.plot(ranks, fitted_counts, 'k--',
+             label="Zipf's law\nslope: {:.2f}".format((slope)))
+    plt.xlabel('rank')
+    plt.ylabel('count')
+    plt.xscale('log')
+    plt.yscale('log')
+    plt.legend()
+
+    plt.savefig(OutFile)
+
+if __name__=="__main__":
+    
+    
+    import argparse
+    
+    parser = argparse.ArgumentParser()
+    
+    parser.add_argument("-f1", "--Fasta1",
+                        required=True,
+                        default=None,
+                        help="First fasta file")
+                        
+    parser.add_argument("-f2", "--Fasta2",
+                        required=True,
+                        default=None,
+                        help="Second fasta file")   
+
+
+    parser.add_argument("--OutFile", 
+                        required=True, 
+                        help="HTML out file", 
+                        default="report.html")
+
+
+    args = parser.parse_args()        
+                                               
+    Run_ngrams(args.Fasta1, args.Fasta2, args.OutFile)
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Ngrams/test-data/out.png
b
Binary file PDAUG_Peptide_Ngrams/test-data/out.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Ngrams/test-data/test1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Ngrams/test-data/test1.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLFDIIKKIAESI
+>ACP4
+GLLDIVKKVVGAFGSL
+>ACP6
+GLFDIVKKVVGALGSL
+>ACP8
+GLFDIVKKVVGTLAGL
+>ACP10
+GLFDIAKKVIGVIGSL
+>ACP12
+GLFDIVKKIAGHIAGSI
+>ACP14
+GLFDIVKKIAGHIVSSI
+>ACP16
+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF
+>ACP18
+HGVSGHGQHGVHG
+>ACP20
+FKCRRWQWRMKKLGAPSITCVRRAF
+>ACP22
+KWKLFKKIKFLHSAKKF
+>ACP24
+KSSAYSLQMGATAIKQVKKLFKKWGW
+>ACP26
+GIGTKILGGVKTALKGALKELASTYAN
+>ACP28
+GIGGKILSGLKTALKGAAKELASTYLH
+>ACP30
+GIGGVLLSAGKAALKGLAKVLAEKYAN
+>ACP32
+SIGAKILGGVKTFFKGALKELASTYLQ
+>ACP34
+FLPLLAGLAANFLPTIICKISYKC
+>ACP36
+FVQWFSKFLGRIL
+>ACP38
+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL
+>ACP40
+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK
+>ACP42
+KWKLFKKIEKVGQNIRDGIIKAGPAVAVVGQATQIAK
+>ACP44
+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK
+>ACP46
+GIGKFLHSAKKFGKAFVGEIMNS
+>ACP48
+GIGAVLKVLTTGLPALISWIKRKRQQ
+>ACP50
+ALWKNMLKGIGKLAGQAALGAVKTLVGAE
+>ACP52
+ACYCRIPACIAGERRYGTCIYQGRLWAFCC
+>ACP54
+ECRRLCYKQRCVTYCRGR
+>ACP56
+LKLKSIVSWAKKVL
+>ACP58
+KWCFRVCYRGICYRRCR
+>ACP60
+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK
+>ACP62
+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP64
+GLLSVLGSVVKHVIPHVVPVIAEHL
+>ACP66
+GLFKVLGSVAKHLLPHVAPVIAEK
+>ACP68
+GLFGVLGSIAKHVLPHVVPVIAEK
+>ACP70
+GLFVGVLAKVAAHVVPAIAEHF
+>ACP72
+GLFVGLAKVAAHNNPAIAEHFQA
+>ACP74
+GFVDFLKKVAGTIANVVT
+>ACP76
+GLLQTIKEKLESLESLAKGIVSGIQA
+>ACP78
+TRSSRAGLQFPVGRVHRLLRK
+>ACP80
+FFGWLIKGAIHAGKAIHGLIHRRRH
+>ACP82
+GLFDVIKKVASVIGGL
+>ACP84
+GLFDIIKKVASVVGGL
+>ACP86
+GRFKRFRKKFKKLFKKLSPVIPLLHLG
+>ACP88
+GGLRSLGRKILRAWKKYGPIIVPIIRIG
+>ACP90
+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP
+>ACP92
+GLLGPLLKIAAKVGSNLL
+>ACP94
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP96
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP98
+FFHHIFRGIVHVGKTIHRLVTG
+>ACP100
+KLAKLAKKLAKLAK
+>ACP102
+KTCENLADTFRGPCFATSNC
+>ACP104
+IDWKKLLDAAKQIL
+>ACP106
+FLIGMTQGLICLITRKC
+>ACP108
+ILPILSLIGGLLGK
+>ACP110
+GLLGLLGSVVSHVVPAIVGHF
+>ACP112
+GLLGLLGSVVSHVLPAITQHL
+>ACP114
+GIKCRFCCGCCTPGICGVCCRF
+>ACP116
+QSHLSLCRWCCNCCRSNKGC
+>ACP118
+ILGPVISTIGGVLGGLLKNL
+>ACP120
+FLPILASLAAKFGPKLFCLVTKKC
+>ACP122
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP124
+LLGMIPLAISAISALSKL
+>ACP126
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP128
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP130
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP132
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP134
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP136
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP138
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP140
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP142
+GFKDLLKGAAKALVKTVLF
+>ACP144
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP146
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP148
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP150
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP152
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP154
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP156
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP158
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP160
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP162
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP164
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP166
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP168
+VNWKKVLGKIIKVAK
+>ACP170
+VNWKKILGKIIKVAK
+>ACP172
+FFSLLPSLIGGLVSAIK
+>ACP174
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP176
+KWKLFKKIPKFLHLAKKF
+>ACP178
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
+>ACP180
+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP182
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP184
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP186
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP188
+FVDLKKIANIINSIFGK
+>ACP190
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP192
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP194
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP196
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP198
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP200
+GMWSKILGHLIR
+>ACP202
+GKWMSLLKHILK
+>ACP204
+GFGMALKLLKKVL
+>ACP206
+GTGLPMSERRKIMLMMR
+>ACP208
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP210
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP212
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP214
+GDACGETCFTGICFTAGCSCNPWPTCTRN
+>ACP216
+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP218
+IPCGESCVWIPCITAIAGCSCKNKVCYT
+>ACP220
+AIPCGESCVWIPCISTVIGCSCSNKVCYR
+>ACP222
+GEYCGESCYLIPCFTPGCYCVSRQCVNKN
+>ACP224
+IPCGESCVWIPCISGMFGCSCKDKVCYS
+>ACP226
+FLGWLFKWASK
+>ACP228
+FLKWLFKWAKK
+>ACP230
+KWKSFLKTFKSAKKTVLHTALKAISS
+>ACP232
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP234
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP236
+KWKLFKKIGAVLKVL
+>ACP238
+GACFSIAHECGA
+>ACP240
+TCCATGACGTTCCTGACGTT
+>ACP242
+KRFKQDGGASHASPASS
+>ACP244
+KRAKAAGGWSHWSPWSSC
+>ACP246
+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
+>ACP248
+FLGALFKVASKVLPSVKCAITKKC
+>ACP250
+GIGKFLKKAKKFGKAFVKILKK
+>ACP252
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP254
+VECYGPNRPQF
+>ACP256
+KRFKQDGGWSHWSPWSSC
+>ACP258
+RQVFQVAYIIIKA
+>ACP260
+KAFDITYVRLKF
+>ACP262
+DFKLFAVTIKYR
+>ACP264
+DFKLFAVYIKYR
+>ACP266
+WHSDMEWWYLLG
+>ACP268
+HTMYYHHYQHHL
+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Ngrams/test-data/test2.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Ngrams/test-data/test2.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>non-ACP0
+MTISLIWGIAMVVCCCIWVIFDRRRRKAGEPPL
+>non-ACP2
+MFATPLRQPTNASGARPAVSMDGQETPFQYEITD
+>non-ACP4
+LLWRKVAGATVGPGPVPA
+>non-ACP6
+DSPDPMNGASSNALIAKMNSAKLLYQHY
+>non-ACP8
+NNQEVIDAISQAISQTPGCVL
+>non-ACP10
+KKVVEKNADPETTLLVYLRRKLGLCGTKLGCGEG
+>non-ACP12
+CSRLLPSLAQEEG
+>non-ACP14
+KNDFAALQAKLDADAAEIEKWWSDSR
+>non-ACP16
+VDREQLVQKARLAEQAERYDD
+>non-ACP18
+RPLRRVVLFYQGKLCSMAGNFWQSSHYLQW
+>non-ACP20
+GAAGERKLCLLSLLLIGA
+>non-ACP22
+MFRKLLKMWILLRPTHWLILIALCAVTCAGYWLLWSE
+>non-ACP24
+HLRGPADSGWMPQAAPCLSGAPQAS
+>non-ACP26
+NNPNNSNSHLRPHAYNNSRRDDSD
+>non-ACP28
+VVILASLSVMFLVSLWQQKIRERLPPGPTPLPFIGNY
+>non-ACP30
+ICLSCLISFFLWNQNRAKGKLPPG
+>non-ACP32
+VVMNSLRVILQAS
+>non-ACP34
+ARPRLDLQLVQRFVRIQKVF
+>non-ACP36
+MLAKGLSLRSVLAKGCQPFLSPTWQSSVLATGGGANIS
+>non-ACP38
+AAGLPGAALPLRKRPLRAPSPEPAAPRGAAGLVV
+>non-ACP40
+PPMPSAPPVHPPP
+>non-ACP42
+SCPIDKRRPLIAFLRRLRD
+>non-ACP44
+RLGLWASGLILILGFLKLLRLLLRRQRLARAMD
+>non-ACP46
+FSPQRDRFQAEGS
+>non-ACP48
+GTLWALVFLGILVGMVVPSPAGTRANNTLLDSRG
+>non-ACP50
+MNRLLQKGTSLVPSWRTR
+>non-ACP52
+MTTSLIWGIAIAACCCLWLILGIRRRQT
+>non-ACP54
+ATLANGMSLQPPLEEVS
+>non-ACP56
+PLTATNSGLAVNN
+>non-ACP58
+VRACHKVCRCLLSGFGGRVDAGQPELLTER
+>non-ACP60
+TAGILLLLLLGTLEGS
+>non-ACP62
+MEPSILLLLALLVGFLLLLVRGH
+>non-ACP64
+MKNCFQLLCNLKVPAAGFKNTVKS
+>non-ACP66
+SVIHTQAHASGLQQVPQLVPAGPGGGGKAVAPSKQSK
+>non-ACP68
+KPLGLLKPSSLMKVSGRFKAHQDA
+>non-ACP70
+ARTLNNKLSLSKPKFSGFT
+>non-ACP72
+LLLVIIWTLFGPSGLGEELLSLSLASLLPAPASPGPP
+>non-ACP74
+WPGILVGGARVASCRYPALGPRLA
+>non-ACP76
+RSVKGLVALITGGASGL
+>non-ACP78
+AAAALRARILQVSSKVN
+>non-ACP80
+TGCCIAGRLANLDDQNLTVAL
+>non-ACP82
+GSILGFLQIATVLTVLLLLLK
+>non-ACP84
+AARQIGSCLMRCRTLDTTSP
+>non-ACP86
+WGCRGRRWAFARVDGGSCHRRGAPTGSTSNQIR
+>non-ACP88
+YAKPGAVRSPAQILQWQVLPNTVPAKS
+>non-ACP90
+RMAGPWLSLHEARLLGTRGAAAPKAV
+>non-ACP92
+SISNRAAVPEHGVAPDAERL
+>non-ACP94
+PNFSMETWLLLV
+>non-ACP96
+PRPPSKTYRGAFQN
+>non-ACP98
+SVLVKGCQPFLSAPRECPGHPRVGT
+>non-ACP100
+LVTPPKALLKPLSIPNQ
+>non-ACP102
+KMQGSRMDEQRCS
+>non-ACP104
+VIADDLPPTCIRP
+>non-ACP106
+LPGGLRVLVQTGH
+>non-ACP108
+GWIWRWGWGRRCLGRPGLPGPGPGPATPLFLLLL
+>non-ACP110
+RGIRGSSAARPSGRRRDPAGRTTETGFNIFTQHD
+>non-ACP112
+QQEKEFLESYPQNCPPDALPGTPGNLD
+>non-ACP114
+APARRVLQVKRVMQESSLSPAHL
+>non-ACP116
+KVAPGGPTGYPGNLTAEQEQKLGELKMILL
+>non-ACP118
+FLASYPQKCPAGSLPGTPGNTDE
+>non-ACP120
+MDAKARNCLLQHREALEKDIKTSY
+>non-ACP122
+ASRQLLVAPPEAL
+>non-ACP124
+MISNGIGTVTTGKRSMCLFPLLLIGLWGC
+>non-ACP126
+MTLRNFGMGKRSIEDRVQEEARCLVEELRKTNASPC
+>non-ACP128
+AVFGLGGVGLSVIMGCKAAGASRIIAVDIN
+>non-ACP130
+PNAKQSILQKNPDDVVIVAAYRTA
+>non-ACP132
+AMELLLTATIFYLVLWVVKAFRLQVPKGLKSPPGP
+>non-ACP134
+LLAAGFCPAVLCH
+>non-ACP136
+AASVNDEQHQRIIKYGRALVLDIVEQ
+>non-ACP138
+IARLREDGIQKRVIQEGRGELPDFQDG
+>non-ACP140
+FIVVMNILALTLPFLAAEVQN
+>non-ACP142
+CQNGRRANRTVRFARTA
+>non-ACP144
+WVTVRSQQRGLFPAI
+>non-ACP146
+LLRSCPLQGSPGRPRSV
+>non-ACP148
+LNDGHFMPVLGFGTYAPPEVPRNRAVEV
+>non-ACP150
+HLGRPSAPTIVAQPVSGLASPASFQPEQFQYTLDNNVLT
+>non-ACP152
+RPEPGGCCCRRTVRANGC
+>non-ACP154
+SWVEENRASFQPPVCNKLMHR
+>non-ACP156
+VFHRVRWAPELGASLG
+>non-ACP158
+RAKVLTLDGMNPRVRRVEYAVRGPIVQRALELEQELRQ
+>non-ACP160
+LLQRARLAEQAERYDDMASAMKAVTELNEPLS
+>non-ACP162
+ALIQKLNSDPQFVLAQNVGTTHDLLDICLKRATVQRA
+>non-ACP164
+AALPMLWTGLVLLGLLGFPQTPAQGHDTVQPNFQQ
+>non-ACP166
+QRRQNDSSVFLAIMVAAAVES
+>non-ACP168
+CNAPGCGQRFTNEDHLAVHKHKHEMTLKFGPARTDS
+>non-ACP170
+LVLLTVQNSALILTLNYSRIMPGYD
+>non-ACP172
+TVLSPPQRFKRILQAMMLAVAVV
+>non-ACP174
+ISRGLLLLAALCCLAPSFL
+>non-ACP176
+VAGTESAQGPPGPAASLELWLNKATDPS
+>non-ACP178
+QYLRIRTVQPEPDYGAAV
+>non-ACP180
+ASPTQTPPTTSTIRVARRSRVALVAM
+>non-ACP182
+TIWRNQHTYKMATSASANLSKIVKKNYMELPQDGKVQ
+>non-ACP184
+LSITRGLLLLAALCCLAPIS
+>non-ACP186
+ILLSIWRQSSGRGKLPPGPIPLPIIGNIFQ
+>non-ACP188
+LLLLSWVALGPRSLEGADPGTPGEAEGPACP
+>non-ACP190
+LRVKRAMQEASFMPPLLPPAAHQRFSTVPAVP
+>non-ACP192
+GLLLLAGLCCLVFGIMAEDAQVAQGPSQQI
+>non-ACP194
+RHVGLLCATGPQRWRF
+>non-ACP196
+AAVALARPKPPLRHQEHLQNEPDS
+>non-ACP198
+SRVNDQSQASRNGLKGKVLTLDTMNPCV
+>non-ACP200
+AAALGPGVLQATRAFHTGQPRLAPLPPLPEYGGK
+>non-ACP202
+LCTSGLWTAQASTNESSNSHRGLAPTNV
+>non-ACP204
+PAIQPVLSGLSRIVNGEEA
+>non-ACP206
+GCQASLSTAQERLGHPGVPTREGVR
+>non-ACP208
+RKVLILTLVVAACGFVLWSSNGR
+>non-ACP210
+GRVRSRCPGPALLLLLALAARPALAGPPAAALQ
+>non-ACP212
+CRITKPALLVLNQETAKVVQT
+>non-ACP214
+KAEVCMAVPWLSLQ
+>non-ACP216
+SHLELNNGTKMPTLGLGT
+>non-ACP218
+LLLPEAAAERDAREKLALWDRRPDTTAPL
+>non-ACP220
+LLALSLVLLYRYATYSHGFFKKLGIPGPKPLPLFGNVLS
+>non-ACP222
+LLSLWRQSSGRGKLPPGPTPLPVIGNILQIGIKD
+>non-ACP224
+AFKSMEVANFYYEADCLAAAYGGKAAPAAPPADRPGPR
+>non-ACP226
+SLFWAARPLQRCGQLVRMAIRAQH
+>non-ACP228
+MRPPRTLTSTATMSALSTSMPMEIDDVMDEDAVNGQA
+>non-ACP230
+LLSLIGFCWAQYDP
+>non-ACP232
+LWARSKNDQLRISFPPGLCWG
+>non-ACP234
+PQGFDVDRDAKKLNKACKGMGTNEAAIIEILSG
+>non-ACP236
+IFCLILWVVKAWQPRLPKGLKSPPGPWGWPLLG
+>non-ACP238
+LDAASPGPLALLGLLFAATLLLSALFLL
+>non-ACP240
+VTLLFKLYCLA
+>non-ACP242
+ATRAAAARLVGTAASRTPAAARH
+>non-ACP244
+RNKLDLETLTDILEHQIR
+>non-ACP246
+RRLVLQARTYAQAAASPAPAAGPGQMSFTFASPTQVFF
+>non-ACP248
+PGRSRSAADDINPAPANM
+>non-ACP250
+LLSALTLETWVLLAVILVLLYRLG
+>non-ACP252
+VMGHGLCPQGARAKAAIPAALRDHEST
+>non-ACP254
+FLVSIAGLLYALVQLGQPCDCLPPLRAAA
+>non-ACP256
+VRSVRAAVGGLRAISAPSAPCLPRPWGLRAG
+>non-ACP258
+RGGCWPRGLQQLLVPGG
+>non-ACP260
+APATPPRPLKRKKLQFTDVTPESSP
+>non-ACP262
+EQAERYDDMAAAMKAVTEQGHELSNEERNL
+>non-ACP264
+MPNDPSDNQLK
+>non-ACP266
+TELLLAITVFCLGFWVVRALRTQVP
+>non-ACP268
+LTADLLGAPFFTLPKELQLALLERQTVFL
+>non-ACP270
+GHGRLVEIQGRLGVRIER
+>non-ACP272
+LPFKLLLFVLLDGWTRLTH
+>non-ACP274
+QALWLVLVLSMPPVLVAAVVGTLVSLVQ
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/PDAUG_Peptide_Sequence_Analysis.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/PDAUG_Peptide_Sequence_Analysis.py Wed Oct 28 02:36:27 2020 +0000
[
b'@@ -0,0 +1,231 @@\n+import  modlamp\n+from modlamp.analysis import *\n+\n+from plotly.subplots import make_subplots\n+import plotly.graph_objects as go\n+from modlamp.analysis import GlobalAnalysis\n+from modlamp.analysis import *\n+\n+import pandas as pd\n+import os, sys\n+import argparse\n+\n+parser = argparse.ArgumentParser(description=\'Deployment tool\')\n+subparsers = parser.add_subparsers()\n+\n+CalcAAFreq = subparsers.add_parser(\'CalcAAFreq\')\n+CalcAAFreq.add_argument("-I","--InFile", required=True, default=None, help="")\n+CalcAAFreq.add_argument("-T","--PlotFile", required=False, default=\'out.pdf\', help="out.pdf")\n+CalcAAFreq.add_argument("--OutFile", required=False, default=\'Out.tsv\', help="Out.tsv")\n+\n+H = subparsers.add_parser(\'H\')\n+H.add_argument("-I","--InFile", required=True, default=None, help="")\n+H.add_argument("-S","--Scale", required=False, default=\'eisenberg\', help="hydrophobicity scale to use. For available scales, see modlamp.descriptors.PeptideDescriptor.")\n+H.add_argument("--OutFile", required=False, default=\'Out.tsv\', help="Out.tsv")\n+\n+uH = subparsers.add_parser(\'uH\')\n+uH.add_argument("-I","--InFile", required=True, default=None, help="")\n+uH.add_argument("-S","--Scale", required=False, default=\'eisenberg\', help="hydrophobicity scale to use. For available scales, see modlamp.descriptors.PeptideDescriptor.")\n+uH.add_argument("-W", "--Window", required=False, default=1000, help="")\n+uH.add_argument("-A", "--Angle", required=False, default=100, help="")\n+uH.add_argument("-M", "--Modality", required=False, default=\'max\', help="")\n+uH.add_argument("--OutFile", required=False, default=\'Out.tsv\', help="Out.tsv")\n+\n+charge = subparsers.add_parser(\'charge\')\n+charge.add_argument("-I","--InFile", required=True, default=None, help="")\n+charge.add_argument("-p", "--ph", required=False, default=7.0, help="")\n+charge.add_argument("-A", "--Amide", required=False, default=True, help="")\n+charge.add_argument("--OutFile", required=False, default=\'Out.tsv\', help="Out.tsv")\n+\n+Len = subparsers.add_parser(\'Len\')\n+Len.add_argument("-I","--InFile", required=True, default=None, help="")\n+Len.add_argument("--OutFile", required=False, default=\'Out.tsv\', help="Out.tsv")\n+\n+PlotSaummary = subparsers.add_parser(\'PlotSummary\')\n+PlotSaummary.add_argument("-I1","--InFile1", required=True, default=None, help="")\n+PlotSaummary.add_argument("-I2", "--InFile2", required=True, default=None, help="Out.tsv")\n+PlotSaummary.add_argument("--PlotFile", required=False, default=\'Out.pdf\', help="out.pdf")\n+PlotSaummary.add_argument("--htmlFname", required="False", default=\'report.html\', help="Output file")\n+PlotSaummary.add_argument("-O","--htmlOutDir", required=False, default=os.path.join(os.getcwd(),\'report_dir\'),  help="HTML Out Dir")\n+PlotSaummary.add_argument("-Wp","--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")\n+PlotSaummary.add_argument("-fn", "--First_lib_name", required=True, help="Name of the fist peptide data")\n+PlotSaummary.add_argument("-sn", "--Second_lib_name", required=True, help="Name of the second peptide data")\n+\n+\n+args = parser.parse_args()\n+\n+\n+\n+def SummaryPlot(Lib_1, Lib_2, First_lib_name, Second_lib_Name, Workdirpath, htmlOutDir, htmlFname):\n+\n+    if not os.path.exists(htmlOutDir):\n+        os.makedirs(htmlOutDir)\n+\n+\n+    AA = [\'A\',\'C\',\'D\',\'E\',\'F\',\'G\',\'H\',\'I\',\'K\',\'L\',\'M\',\'N\',\'P\',\'Q\',\'R\',\'S\',\'T\',\'V\',\'W\',\'Y\']\n+\n+    Pep1, Index1 = ReturnPeptide(Lib_1)\n+    Pep2, Index2 = ReturnPeptide(Lib_2)\n+\n+    fig = make_subplots(\n+        rows=2, cols=3,\n+        specs=[[{"type": "xy"}, {"type": "histogram"},   {"type": "box"}  ],[{"type": "violin"}, {"type": "violin"}, {"type": "scatter3d"} ]],\n+    subplot_titles=(" Amino Acid Fraction", "Global Charge", "Length Distribution", "Global Hydrophobicity", "Global Hydrophobic Movement", "Scatter Plot"))\n+\n+\n+    #########################################\n+    g = GlobalAnalysis([Pep1, Pep2])\n+    df = g.calc_aa_freq(plot=False)\n+\n+    data1 = g.aafreq[0]\n+    data2 = '..b'ace(go.Violin(y=h2,box_visible=True, name=Second_lib_Name, marker_color=\'#FF7F0E\', meanline_visible=True), row=2, col=1)\n+    #################################################################\n+\n+    #####################################\n+    uH = GlobalAnalysis([Pep1, Pep2])\n+    uH.calc_uH()\n+\n+    uh1 = uH.uH[0]\n+    uh2 = uH.uH[1]\n+\n+    fig.add_trace(go.Violin( y=uh1,box_visible=True, name =First_lib_name, marker_color=\'#1F77B4\', meanline_visible=True), row=2, col=2)\n+    fig.add_trace(go.Violin(y=uh2,box_visible=True, name=Second_lib_Name, marker_color=\'#FF7F0E\', meanline_visible=True), row=2, col=2)\n+    #######################################\n+\n+\n+    ############################################\n+    fig.add_trace(go.Scatter3d(x=h1, y=uh1, z=charge1, marker_color=\'#1F77B4\', mode=\'markers\', name=First_lib_name, marker_size=3.0),row=2, col=3)\n+    fig.add_trace(go.Scatter3d(x=h2, y=uh2, z=charge2, marker_color=\'#FF7F0E\', mode=\'markers\', name=Second_lib_Name, marker_size=3.0), row=2, col=3)\n+    fig.update_layout(scene = dict(xaxis_title=\'Hydrophobicity\', yaxis_title=\'Hydrophobic Movement\', zaxis_title=\'Charge\'),uniformtext_minsize=4, font=dict(\n+            family="Times New Roman",\n+            size=12,\n+            color="black"))\n+    ###########################################\n+\n+    fig.update_xaxes(title_text="Amino Acid", row=1, col=1)\n+    fig.update_xaxes(title_text="Global Charge", row=1, col=2)\n+    fig.update_xaxes(title_text="Peptide dataset", showgrid=False, row=1, col=3)\n+    fig.update_xaxes(title_text="Peptide dataset",  row=2, col=1)\n+    fig.update_xaxes(title_text="Peptide dataset",  row=2, col=2)\n+\n+    fig.update_yaxes(title_text="Fraction", row=1, col=1)\n+    fig.update_yaxes(title_text="Fraction",  row=1, col=2)\n+    fig.update_yaxes(title_text="Length",  row=1, col=3)\n+    fig.update_yaxes(title_text="Global hydrophobicity", row=2, col=1)\n+    fig.update_yaxes(title_text="Global hydrophobic Movement", row=2, col=2)\n+    fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname))\n+    #fig.show()\n+\n+def ReturnPeptide(Infile):\n+\n+    file = open(Infile)\n+    lines = file.readlines()\n+\n+    Index = []\n+    Pep = []\n+\n+    for line in lines:\n+        if \'>\' in line:\n+            line = line.strip(\'\\n\')\n+            line = line.strip(\'\\r\')\n+            Index.append(line.strip(\'\\n\'))\n+        else:\n+            line = line.strip(\'\\n\')\n+            line = line.strip(\'\\r\')\n+            Pep.append(line)\n+    return Pep, Index\n+\n+if sys.argv[1] == \'CalcAAFreq\':\n+\n+    Pep, Index = ReturnPeptide(args.InFile)\n+    g = GlobalAnalysis(Pep)\n+    g.calc_aa_freq(plot=False, color=\'#83AF9B\')\n+    df1 =  pd.DataFrame(g.aafreq[0], columns=[\'aa_freq\'])\n+    df1.to_csv(args.OutFile,  sep=\'\\t\', index=None)\n+\n+elif sys.argv[1] == \'H\':\n+\n+    Pep, _ = ReturnPeptide(args.InFile)\n+    g = GlobalAnalysis(Pep)\n+    g.calc_H(args.Scale)\n+    df1 = pd.DataFrame(g.H[0].T, columns=[\'H\'])\n+    df1.to_csv(args.OutFile,  sep=\'\\t\', index=None)\n+\n+elif sys.argv[1] == \'uH\':\n+\n+    Pep, _ = ReturnPeptide(args.InFile)\n+\n+    g = GlobalAnalysis(Pep)\n+    g.calc_uH(int(args.Window), int(args.Angle), args.Modality)\n+    df1 = pd.DataFrame(g.uH[0].T, columns=[\'uH\'])\n+    df1.to_csv(args.OutFile,  sep=\'\\t\', index=None)\n+  \n+elif sys.argv[1] == \'charge\':\n+\n+    Pep, _ = ReturnPeptide(args.InFile)\n+\n+    g = GlobalAnalysis(Pep)\n+\n+    if args.Amide == \'true\':\n+        amide = True\n+    else:\n+      amide = False\n+\n+    g.calc_charge(float(args.ph), amide)\n+    df1 = pd.DataFrame(g.charge[0].T, columns=[\'charge\'])\n+    df1.to_csv(args.OutFile,  sep=\'\\t\', index=None)\n+\n+elif sys.argv[1] == \'Len\':\n+\n+    Pep, _ = ReturnPeptide(args.InFile)\n+    df1 = pd.DataFrame([len(x) for x in Pep], columns=[\'c\'])\n+    df1.to_csv( args.OutFile,  sep=\'\\t\', index=None)\n+\n+elif sys.argv[1] == "PlotSummary":\n+\n+    SummaryPlot(args.InFile1, args.InFile2, args.First_lib_name, args.Second_lib_name, args.Workdirpath, args.htmlOutDir, args.htmlFname)\n+\n+\n+\n+\n+\n+\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/ACPs.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/test-data/ACPs.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP_1
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP_2
+GLFDIIKKIAESI
+>ACP_3
+GLLDIVKKVVGAFGSL
+>ACP_4
+GLFDIVKKVVGALGSL
+>ACP_5
+GLFDIVKKVVGTLAGL
+>ACP_6
+GLFDIAKKVIGVIGSL
+>ACP_7
+GLFDIVKKIAGHIAGSI
+>ACP_8
+GLFDIVKKIAGHIVSSI
+>ACP_9
+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF
+>ACP_10
+HGVSGHGQHGVHG
+>ACP_11
+FKCRRWQWRMKKLGAPSITCVRRAF
+>ACP_12
+KWKLFKKIKFLHSAKKF
+>ACP_13
+KSSAYSLQMGATAIKQVKKLFKKWGW
+>ACP_14
+GIGTKILGGVKTALKGALKELASTYAN
+>ACP_15
+GIGGKILSGLKTALKGAAKELASTYLH
+>ACP_16
+GIGGVLLSAGKAALKGLAKVLAEKYAN
+>ACP_17
+SIGAKILGGVKTFFKGALKELASTYLQ
+>ACP_18
+FLPLLAGLAANFLPTIICKISYKC
+>ACP_19
+FVQWFSKFLGRIL
+>ACP_20
+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL
+>ACP_21
+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK
+>ACP_22
+KWKLFKKIEKVGQNIRDGIIKAGPAVAVVGQATQIAK
+>ACP_23
+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK
+>ACP_24
+GIGKFLHSAKKFGKAFVGEIMNS
+>ACP_25
+GIGAVLKVLTTGLPALISWIKRKRQQ
+>ACP_26
+ALWKNMLKGIGKLAGQAALGAVKTLVGAE
+>ACP_27
+ACYCRIPACIAGERRYGTCIYQGRLWAFCC
+>ACP_28
+ECRRLCYKQRCVTYCRGR
+>ACP_29
+LKLKSIVSWAKKVL
+>ACP_30
+KWCFRVCYRGICYRRCR
+>ACP_31
+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK
+>ACP_32
+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP_33
+GLLSVLGSVVKHVIPHVVPVIAEHL
+>ACP_34
+GLFKVLGSVAKHLLPHVAPVIAEK
+>ACP_35
+GLFGVLGSIAKHVLPHVVPVIAEK
+>ACP_36
+GLFVGVLAKVAAHVVPAIAEHF
+>ACP_37
+GLFVGLAKVAAHNNPAIAEHFQA
+>ACP_38
+GFVDFLKKVAGTIANVVT
+>ACP_39
+GLLQTIKEKLESLESLAKGIVSGIQA
+>ACP_40
+TRSSRAGLQFPVGRVHRLLRK
+>ACP_41
+FFGWLIKGAIHAGKAIHGLIHRRRH
+>ACP_42
+GLFDVIKKVASVIGGL
+>ACP_43
+GLFDIIKKVASVVGGL
+>ACP_44
+GRFKRFRKKFKKLFKKLSPVIPLLHLG
+>ACP_45
+GGLRSLGRKILRAWKKYGPIIVPIIRIG
+>ACP_46
+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP
+>ACP_47
+GLLGPLLKIAAKVGSNLL
+>ACP_48
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP_49
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP_50
+FFHHIFRGIVHVGKTIHRLVTG
+>ACP_51
+KLAKLAKKLAKLAK
+>ACP_52
+KTCENLADTFRGPCFATSNC
+>ACP_53
+IDWKKLLDAAKQIL
+>ACP_54
+FLIGMTQGLICLITRKC
+>ACP_55
+ILPILSLIGGLLGK
+>ACP_56
+GLLGLLGSVVSHVVPAIVGHF
+>ACP_57
+GLLGLLGSVVSHVLPAITQHL
+>ACP_58
+GIKCRFCCGCCTPGICGVCCRF
+>ACP_59
+QSHLSLCRWCCNCCRSNKGC
+>ACP_60
+ILGPVISTIGGVLGGLLKNL
+>ACP_61
+FLPILASLAAKFGPKLFCLVTKKC
+>ACP_62
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP_63
+LLGMIPLAISAISALSKL
+>ACP_64
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP_65
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP_66
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP_67
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP_68
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP_69
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP_70
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP_71
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP_72
+GFKDLLKGAAKALVKTVLF
+>ACP_73
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP_74
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP_75
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP_76
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP_77
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP_78
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP_79
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP_80
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP_81
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP_82
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP_83
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP_84
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP_85
+VNWKKVLGKIIKVAK
+>ACP_86
+VNWKKILGKIIKVAK
+>ACP_87
+FFSLLPSLIGGLVSAIK
+>ACP_88
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP_89
+KWKLFKKIPKFLHLAKKF
+>ACP_90
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
+>ACP_91
+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP_92
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP_93
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP_94
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP_95
+FVDLKKIANIINSIFGK
+>ACP_96
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP_97
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP_98
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP_99
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP_100
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP_101
+GMWSKILGHLIR
+>ACP_102
+GKWMSLLKHILK
+>ACP_103
+GFGMALKLLKKVL
+>ACP_104
+GTGLPMSERRKIMLMMR
+>ACP_105
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP_106
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP_107
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP_108
+GDACGETCFTGICFTAGCSCNPWPTCTRN
+>ACP_109
+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP_110
+IPCGESCVWIPCITAIAGCSCKNKVCYT
+>ACP_111
+AIPCGESCVWIPCISTVIGCSCSNKVCYR
+>ACP_112
+GEYCGESCYLIPCFTPGCYCVSRQCVNKN
+>ACP_113
+IPCGESCVWIPCISGMFGCSCKDKVCYS
+>ACP_114
+FLGWLFKWASK
+>ACP_115
+FLKWLFKWAKK
+>ACP_116
+KWKSFLKTFKSAKKTVLHTALKAISS
+>ACP_117
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP_118
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP_119
+KWKLFKKIGAVLKVL
+>ACP_120
+GACFSIAHECGA
+>ACP_121
+TCCATGACGTTCCTGACGTT
+>ACP_122
+KRFKQDGGASHASPASS
+>ACP_123
+KRAKAAGGWSHWSPWSSC
+>ACP_124
+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
+>ACP_125
+FLGALFKVASKVLPSVKCAITKKC
+>ACP_126
+GIGKFLKKAKKFGKAFVKILKK
+>ACP_127
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP_128
+VECYGPNRPQF
+>ACP_129
+KRFKQDGGWSHWSPWSSC
+>ACP_130
+RQVFQVAYIIIKA
+>ACP_131
+KAFDITYVRLKF
+>ACP_132
+DFKLFAVTIKYR
+>ACP_133
+DFKLFAVYIKYR
+>ACP_134
+WHSDMEWWYLLG
+>ACP_135
+HTMYYHHYQHHL
+>ACP_136
+RLVSYNGIIFFLK
+>ACP_137
+GRENYHGCTTHWGFTLC
+>ACP_138
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/non_ACPs.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/test-data/non_ACPs.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>non-ACP_1
+VIADDLPPTCIRP
+>non-ACP_2
+MAEALLLRATFYLLIGSANAAKPD
+>non-ACP_3
+LLSALTLETWVLLAVILVLLYRLG
+>non-ACP_4
+MTTSLIWGIAIAACCCLWLILGIRRRQT
+>non-ACP_5
+PQGFDVDRDAKKLNKACKGMGTNEAAIIEILSG
+>non-ACP_6
+RHVGLLCATGPQRWRF
+>non-ACP_7
+VGKSSKMLQHIDYRMRCILQDGRIFIGTFKA
+>non-ACP_8
+LPGGLRVLVQTGH
+>non-ACP_9
+RPKFALAQAQKCFALYRQAYTANNSSQVQAAMKGFEE
+>non-ACP_10
+HLGRPSAPTIVAQPVSGLASPASFQPEQFQYTLDNNVLT
+>non-ACP_11
+LHRAQDYRRELDTLQSLLTTSQSSELQAAAALLKC
+>non-ACP_12
+AAVALARPKPPLRHQEHLQNEPDS
+>non-ACP_13
+KAEVCMAVPWLSLQ
+>non-ACP_14
+KMQGSRMDEQRCS
+>non-ACP_15
+LVTPPKALLKPLSIPNQ
+>non-ACP_16
+LCTSGLWTAQASTNESSNSHRGLAPTNV
+>non-ACP_17
+AAALGPGVLQATRAFHTGQPRLAPLPPLPEYGGK
+>non-ACP_18
+ALIQKLNSDPQFVLAQNVGTTHDLLDICLKRATVQRA
+>non-ACP_19
+EWRDLKGRADINKDDVV
+>non-ACP_20
+SWVEENRASFQPPVCNKLMHR
+>non-ACP_21
+RRLVLQARTYAQAAASPAPAAGPGQMSFTFASPTQVFF
+>non-ACP_22
+LVLLTVQNSALILTLNYSRIMPGYD
+>non-ACP_23
+FYQNRAAAFEQLQKWKEVAQDCT
+>non-ACP_24
+VFHRVRWAPELGASLG
+>non-ACP_25
+MISNGIGTVTTGKRSMCLFPLLLIGLWGC
+>non-ACP_26
+RPEPGGCCCRRTVRANGC
+>non-ACP_27
+AASVNDEQHQRIIKYGRALVLDIVEQ
+>non-ACP_28
+ASRQLLVAPPEAL
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/out1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/test-data/out1.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,139 @@
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/test1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/test-data/test1.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP0
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/test1/out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/test-data/test1/out.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,21 @@
+aa_freq
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/test2/out2.tsv
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/test3/out3.tsv
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/test5/out5.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/test-data/test5/out5.tsv Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Sequence_Analysis/test-data/test6/out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/test-data/test6/out.tsv Wed Oct 28 02:36:27 2020 +0000
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diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Structure_Builder/PDAUG_Peptide_Structure_Builder.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Structure_Builder/PDAUG_Peptide_Structure_Builder.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,73 @@
+import tempfile
+import pandas as pd
+import shutil
+import sys
+import glob
+import fragbuilder
+import openbabel
+from fragbuilder import peptide
+
+import os
+
+
+def read_pep_file(pep_infile):
+    
+    file = open(pep_infile)
+    lines = file.readlines()
+
+    Index = []
+    list_pep_name = []
+
+    for line in lines:
+        if '>' in line:
+            Index.append(line.strip('\n'))
+        else:
+            line = line.strip('\n')
+            line = line.strip('\r')
+            list_pep_name.append(line.strip('\n'))
+
+    return list_pep_name
+
+def structure_gen(pep_seq, out_dir):
+
+    if not os.path.exists(os.path.join(out_dir, 'DataFile')):
+        os.makedirs(os.path.join(out_dir, 'DataFile'))
+
+    b = len(pep_seq)
+
+    for seq in pep_seq:
+
+        pep = peptide.Peptide(seq, nterm = "charged", cterm = "neutral")
+        pep.regularize()
+        pep.write_pdb(os.path.join(out_dir, 'DataFile', seq+".pdb"))
+
+        obConversion = openbabel.OBConversion()
+        obConversion.SetInAndOutFormats("pdb", "sdf")
+        mol = openbabel.OBMol()
+        obConversion.ReadFile(mol,  os.path.join(out_dir, 'DataFile', seq+".pdb")) 
+
+        mol.AddHydrogens()       
+
+    
+def main_process(str_pep_file, out_dir):
+      
+    my_pep = read_pep_file(str_pep_file) 
+    structure_gen(my_pep, out_dir)
+    
+    
+if __name__=="__main__":
+    
+    
+    import argparse
+    parser = argparse.ArgumentParser()
+    
+    parser.add_argument("-p", "--pep", required=True, default=None, help="pep file")                    
+    parser.add_argument("-o", "--OutDir", required=None, default=os.getcwd(), help="Path to out file")  
+                                               
+    args = parser.parse_args()
+    main_process(args.pep, args.OutDir)
+   
+    
+    
+   
+    
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Structure_Builder/test-data/DataFile/GLF.pdb
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Structure_Builder/test-data/DataFile/GLF.pdb Wed Oct 28 02:36:27 2020 +0000
b
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+COMPND    532b43383ef54805b372df2052770b55.xyz 
+AUTHOR    GENERATED BY OPEN BABEL 2.4.1
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+ATOM      3  N   GLY A   1      -0.621  -3.315   0.040  1.00  0.00           N  
+ATOM      4  H3  GLY A   1       0.386  -3.137   0.204  1.00  0.00           H  
+ATOM      5  CA  GLY A   1      -1.319  -1.994  -0.077  1.00  0.00           C  
+ATOM      6  C   GLY A   1      -0.309  -0.872   0.134  1.00  0.00           C  
+ATOM      7  HA1 GLY A   1      -1.785  -1.954  -1.064  1.00  0.00           H  
+ATOM      8  HA2 GLY A   1      -2.074  -1.955   0.712  1.00  0.00           H  
+ATOM      9  O   GLY A   1       0.593  -1.038   0.954  1.00  0.00           O  
+ATOM     10  N   LEU A   2      -0.429   0.219  -0.671  1.00  0.00           N  
+ATOM     11  H   LEU A   2      -1.117   0.254  -1.426  1.00  0.00           H  
+ATOM     12  CA  LEU A   2       0.459   1.393  -0.605  1.00  0.00           C  
+ATOM     13  HA  LEU A   2       0.332   1.829   0.390  1.00  0.00           H  
+ATOM     14  CB  LEU A   2       1.922   1.033  -0.902  1.00  0.00           C  
+ATOM     15  C   LEU A   2      -0.074   2.337  -1.694  1.00  0.00           C  
+ATOM     16  HB1 LEU A   2       2.267   0.267  -0.198  1.00  0.00           H  
+ATOM     17  HB2 LEU A   2       1.979   0.568  -1.897  1.00  0.00           H  
+ATOM     18  CG  LEU A   2       2.914   2.212  -0.852  1.00  0.00           C  
+ATOM     19  O   LEU A   2      -0.481   1.887  -2.764  1.00  0.00           O  
+ATOM     20  HG  LEU A   2       2.626   2.959  -1.601  1.00  0.00           H  
+ATOM     21  CD2 LEU A   2       2.950   2.886   0.520  1.00  0.00           C  
+ATOM     22  CD1 LEU A   2       4.316   1.715  -1.216  1.00  0.00           C  
+ATOM     23 HD21 LEU A   2       3.225   2.174   1.305  1.00  0.00           H  
+ATOM     24 HD22 LEU A   2       3.682   3.701   0.530  1.00  0.00           H  
+ATOM     25 HD23 LEU A   2       1.983   3.322   0.784  1.00  0.00           H  
+ATOM     26 HD11 LEU A   2       4.319   1.250  -2.208  1.00  0.00           H  
+ATOM     27 HD12 LEU A   2       5.030   2.544  -1.232  1.00  0.00           H  
+ATOM     28 HD13 LEU A   2       4.674   0.973  -0.493  1.00  0.00           H  
+ATOM     29  N   PHE A   3      -0.097   3.669  -1.378  1.00  0.00           N  
+ATOM     30  H   PHE A   3       0.245   4.000  -0.480  1.00  0.00           H  
+ATOM     31  CA  PHE A   3      -0.582   4.687  -2.325  1.00  0.00           C  
+ATOM     32  HA  PHE A   3       0.142   4.669  -3.141  1.00  0.00           H  
+ATOM     33  CB  PHE A   3      -2.047   4.467  -2.753  1.00  0.00           C  
+ATOM     34  C   PHE A   3      -0.462   6.046  -1.641  1.00  0.00           C  
+ATOM     35  HB1 PHE A   3      -2.452   3.593  -2.222  1.00  0.00           H  
+ATOM     36  HB2 PHE A   3      -2.657   5.319  -2.420  1.00  0.00           H  
+ATOM     37  CG  PHE A   3      -2.358   4.263  -4.224  1.00  0.00           C  
+ATOM     38  O   PHE A   3      -0.686   6.268  -0.459  1.00  0.00           O  
+ATOM     39  CD2 PHE A   3      -3.706   4.066  -4.576  1.00  0.00           C  
+ATOM     40  CD1 PHE A   3      -1.405   4.261  -5.249  1.00  0.00           C  
+ATOM     41  HD2 PHE A   3      -4.477   4.061  -3.809  1.00  0.00           H  
+ATOM     42  CE2 PHE A   3      -4.083   3.880  -5.907  1.00  0.00           C  
+ATOM     43  CE1 PHE A   3      -1.784   4.075  -6.582  1.00  0.00           C  
+ATOM     44  HD1 PHE A   3      -0.345   4.400  -5.059  1.00  0.00           H  
+ATOM     45  HE2 PHE A   3      -5.130   3.733  -6.160  1.00  0.00           H  
+ATOM     46  CZ  PHE A   3      -3.121   3.887  -6.910  1.00  0.00           C  
+ATOM     47  HE1 PHE A   3      -1.027   4.082  -7.363  1.00  0.00           H  
+ATOM     48  HZ  PHE A   3      -3.412   3.745  -7.949  1.00  0.00           H  
+ATOM     49  OXT PHE A   3      -0.036   7.020  -2.465  1.00  0.00           O  
+ATOM     50  HXT PHE A   3       0.006   7.834  -1.917  1.00  0.00           H  
+CONECT    1    3                                                      
+CONECT    2    3                                                      
+CONECT    3    2    5    4    1                                       
+CONECT    4    3                                                      
+CONECT    5    7    3    6    8                                       
+CONECT    6    9    5   10                                            
+CONECT    7    5                                                      
+CONECT    8    5                                                      
+CONECT    9    6                                                      
+CONECT   10   11    6   12                                            
+CONECT   11   10                                                      
+CONECT   12   14   15   10   13                                       
+CONECT   13   12                                                      
+CONECT   14   17   16   18   12                                       
+CONECT   15   19   29   12                                            
+CONECT   16   14                                                      
+CONECT   17   14                                                      
+CONECT   18   22   14   20   21                                       
+CONECT   19   15                                                      
+CONECT   20   18                                                      
+CONECT   21   18   23   24   25                                       
+CONECT   22   26   28   27   18                                       
+CONECT   23   21                                                      
+CONECT   24   21                                                      
+CONECT   25   21                                                      
+CONECT   26   22                                                      
+CONECT   27   22                                                      
+CONECT   28   22                                                      
+CONECT   29   15   31   30                                            
+CONECT   30   29                                                      
+CONECT   31   32   29   34   33                                       
+CONECT   32   31                                                      
+CONECT   33   31   37   36   35                                       
+CONECT   34   38   31   49                                            
+CONECT   35   33                                                      
+CONECT   36   33                                                      
+CONECT   37   40   33   39                                            
+CONECT   38   34                                                      
+CONECT   39   37   42   41                                            
+CONECT   40   44   43   37                                            
+CONECT   41   39                                                      
+CONECT   42   46   39   45                                            
+CONECT   43   47   40   46                                            
+CONECT   44   40                                                      
+CONECT   45   42                                                      
+CONECT   46   43   48   42                                            
+CONECT   47   43                                                      
+CONECT   48   46                                                      
+CONECT   49   34   50                                                 
+CONECT   50   49                                                      
+MASTER        0    0    0    0    0    0    0    0   50    0   50    0
+END
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Peptide_Structure_Builder/test-data/test.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Structure_Builder/test-data/test.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,2 @@
+>sequences_0
+GLF
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Based_Peptide_Generation/PDAUG_Sequence_Based_Peptide_Generation.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Based_Peptide_Generation/PDAUG_Sequence_Based_Peptide_Generation.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,154 @@
+import sys
+import itertools
+import pandas as pd
+import random
+import os
+from itertools import permutations
+from random import shuffle
+import argparse, sys
+import pandas as pd
+
+
+def MutatedPeptides(input_file, index_list, AA, outputFile):
+
+
+    index_list = [int(x) for x in index_list.split(',')]
+    out_put = []
+    AA = AA.split(',')
+    l = len(index_list)
+
+    replacements = [x for x in itertools.permutations(AA,l)]
+
+
+    counter = 0
+    to_modify = [x for x in input_file]
+
+    for replacement in replacements:
+        for i,index in enumerate(index_list):
+            to_modify[index_list[i]-1] = replacement[i]
+
+        counter = counter + 1
+        out_put.append("".join(to_modify).upper())
+
+    w = open(outputFile, 'w')
+
+    for i, f in enumerate(out_put):
+
+
+        w.write(">sequence_"+str(i)+'\n')
+        w.write(f+'\n')
+
+def RandomPeptides(AAs, pep_length, out_pep_num, outputFile):
+
+
+    if int(pep_length) > 20:
+        print ("Max peptide lenth 20")
+        exit()
+    else:
+        pass
+
+    if int(out_pep_num) > 10000:
+        print ("Max peptide library 10000")
+        exit()
+    else:
+        pass
+
+    out_pep_lib = []
+    raw = AAs.split(',')
+
+    for x in range(int(out_pep_num)):
+        un_seq = []
+        for i in range(int(pep_length)):
+            un_seq.append(random.choice(raw))
+        out_pep_lib.append("".join(un_seq))
+
+
+    w = open(outputFile, 'w')
+
+
+    for i, f in enumerate(out_pep_lib):
+
+        w.write(">sequence_"+str(i)+'\n')
+        w.write(f+'\n')
+
+def SlidingWindowPeptide(infile, window_size, frag_size, outputFile):
+
+
+    if int(window_size) > 10:
+        print ("Max window_size 10")
+        exit()
+    else:
+        pass
+    if int(frag_size) >  20:
+        print ("Max frag size is 20")
+        exit()
+    else:
+        pass
+
+
+    pep_list = []
+
+    f = open(infile)
+
+    lines = f.readlines()
+
+    flines = []
+
+    for line in lines:
+        if '>' in line:
+            pass
+        else:
+            flines.append(line.strip('\n'))
+    sequence = "".join(flines)
+
+    for i in range(int(frag_size)):
+        if int(frag_size) == len(sequence[i*int(window_size):i*int(window_size)+int(frag_size)]):
+            pep_list.append(sequence[i*int(window_size):i*int(window_size)+int(frag_size)])
+        else:
+            break
+
+    w = open(outputFile, 'w')
+
+
+    for i, f in enumerate(pep_list):
+
+        w.write(">sequence_"+str(i)+'\n')
+        w.write(f+'\n')
+
+if __name__=='__main__':
+
+    parser = argparse.ArgumentParser(description='Deployment tool')
+    subparsers = parser.add_subparsers()
+
+    Mp = subparsers.add_parser('MutatedPeptides')
+    Mp.add_argument("-s","--sequence")
+    Mp.add_argument("-m","--mutation_site_list")
+    Mp.add_argument("-a","--AA_list")
+    Mp.add_argument("-d", "--outputFile", required=None, default='out.fasta',   help="Path to out file")
+
+    Rp = subparsers.add_parser('RandomPeptides')
+    Rp.add_argument("-a","--AA_list")
+    Rp.add_argument("-l","--pep_length")
+    Rp.add_argument("-o","--out_pep_lenght")
+    Rp.add_argument("-d", "--outputFile", required=None, default=os.path.join(os.getcwd(),'report_dirr'),   help="Path to out file")
+
+    Sp = subparsers.add_parser('SlidingWindowPeptide')
+    Sp.add_argument("-i","--InFile")
+    Sp.add_argument("-w","--winSize")
+    Sp.add_argument("-s","--FragSize")
+    Sp.add_argument("-d", "--outputFile", required=None, default=os.path.join(os.getcwd(),'report_dirr'),   help="Path to out file")
+
+    args = parser.parse_args()
+
+    if sys.argv[1] == 'MutatedPeptides':
+        MutatedPeptides(args.sequence, args.mutation_site_list, args.AA_list, args.outputFile)
+
+    elif sys.argv[1] == 'RandomPeptides':
+        RandomPeptides(args.AA_list, args.pep_length, args.out_pep_lenght, args.outputFile)
+
+    elif sys.argv[1] == 'SlidingWindowPeptide':
+        SlidingWindowPeptide(args.InFile, args.winSize, args.FragSize, args.outputFile)
+
+    else:
+        print("In Correct Option:")
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Based_Peptide_Generation/test-data/out1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Based_Peptide_Generation/test-data/out1.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,4 @@
+>sequence_0
+KGLKLLKKKLLK
+>sequence_1
+KYLKLLKKKLLK
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Based_Peptide_Generation/test-data/out2.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Based_Peptide_Generation/test-data/out2.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,14 @@
+>sequence_0
+FKFGG
+>sequence_1
+GDDLGGV
+>sequence_2
+GVKKK
+>sequence_3
+GFDDFV
+>sequence_4
+GGLFKF
+>sequence_5
+VKDVG
+>sequence_6
+FFKDDIL
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Based_Peptide_Generation/test-data/out3.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Based_Peptide_Generation/test-data/out3.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,14 @@
+>sequence_0
+MNRLTFA
+>sequence_1
+LTFAVFL
+>sequence_2
+AVFLSAL
+>sequence_3
+LSALGFL
+>sequence_4
+LGFLVCA
+>sequence_5
+LVCAAGN
+>sequence_6
+AAGNPCC
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Based_Peptide_Generation/test-data/test1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Based_Peptide_Generation/test-data/test1.fasta Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,10 @@
+>AHC69389.1 COX-2 [Pagrus major]
+MNRLTFAVFLSALGFLVCAAGNPCCSEPCQNRGVCTALGSDNYECDCTRTGYRGQNCTTPEFLTWLKVSL
+KPSPNTVHYILTHFKDFWNIINNISFLRDAIMRYVLTSRSHMIDSPPTFNADYGYKNWEAYSNLSYYTRT
+LPPVPEDCPTPMGVEGKKELPDAKILAEKLLMRREFIPDPQGTSLMFAFFAQHFTHQFFKSDMKRGPAFT
+AAQGHGVDLSHIYGDNLVRQHKLRLFKDGKLKHQILDGEMYPPTVKEVGAEMHHPPHVPDAYRFAVGHEA
+FGLVPGLMMYATIWLREHNRVCDVLKEVHPDWDDERLFQTTRLILIGETIKIVIEDYVQHLSGYNFKLKF
+DPELLFNQRFQYQNRIASEFNTLYHWHPLMPDSFHIEEKEYSYKEFVFNTSVVTEHGISNLVESFSKQIA
+GRVAGGRNVPGPIMYVAIKSIENSRKMRYQSLNAYRKRFSLKPYSSFEDMTGEKEMAAVLEEMYGHIDAM
+ELYPGLLVEKPRENAIFGETMVEMGAPFSLKGLMGNPICSPEYWKPSTFGGTVGFDIVNTASLQRLVCNN
+ANGPCPVASFHVPDVKETGSMIINSSTSNSRSSDINPTVILKERTTEL
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Network/PDAUG_Sequence_Network.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Network/PDAUG_Sequence_Network.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,53 @@
+import Levenshtein
+import matplotlib.pyplot as plt
+import networkx as nx
+import os
+
+
+def SeqSimilarityNetwork(InFile, OutFile):
+
+    f = open(InFile)
+    lines = f.readlines()
+
+    record = []
+    seq = []
+
+    G = nx.Graph()
+
+    for line in lines:
+
+        if ">" in line:
+            record.append(line.strip('\n'))
+        else:
+            seq.append(line.strip('\n'))
+
+    for x, i in enumerate(seq):
+        for X, I in enumerate(seq):
+            L = Levenshtein.ratio(i, I )
+            if  L >= 0.4:
+                G.add_edge(record[x], record[X], weight=float(Levenshtein.ratio(i, I )))
+
+    elarge = [(u, v) for (u, v, d) in G.edges(data=True) if d['weight'] >= 0.4]
+
+    pos = nx.spring_layout(G)
+    nx.draw_networkx_nodes(G, pos, node_size=10)
+    nx.draw_networkx_edges(G, pos, edgelist=elarge,width=1)
+    plt.axis('off')
+
+    plt.savefig(OutFile)
+
+
+
+if __name__=="__main__":
+
+    import argparse
+    
+    parser = argparse.ArgumentParser()
+    
+    parser.add_argument("-I", "--InFile", required=True, default=None, help="Path to target tsv file")
+    parser.add_argument("-O","--OutFile", required=False, help="HTML out file", default="out.png")
+    args = parser.parse_args()
+
+    SeqSimilarityNetwork(args.InFile, args.OutFile)
+
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Network/test-data/out.png
b
Binary file PDAUG_Sequence_Network/test-data/out.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Network/test-data/positive.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Network/test-data/positive.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLFDIIKKIAESI
+>ACP4
+GLLDIVKKVVGAFGSL
+>ACP6
+GLFDIVKKVVGALGSL
+>ACP8
+GLFDIVKKVVGTLAGL
+>ACP10
+GLFDIAKKVIGVIGSL
+>ACP12
+GLFDIVKKIAGHIAGSI
+>ACP14
+GLFDIVKKIAGHIVSSI
+>ACP16
+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF
+>ACP18
+HGVSGHGQHGVHG
+>ACP20
+FKCRRWQWRMKKLGAPSITCVRRAF
+>ACP22
+KWKLFKKIKFLHSAKKF
+>ACP24
+KSSAYSLQMGATAIKQVKKLFKKWGW
+>ACP26
+GIGTKILGGVKTALKGALKELASTYAN
+>ACP28
+GIGGKILSGLKTALKGAAKELASTYLH
+>ACP30
+GIGGVLLSAGKAALKGLAKVLAEKYAN
+>ACP32
+SIGAKILGGVKTFFKGALKELASTYLQ
+>ACP34
+FLPLLAGLAANFLPTIICKISYKC
+>ACP36
+FVQWFSKFLGRIL
+>ACP38
+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL
+>ACP40
+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK
+>ACP42
+KWKLFKKIEKVGQNIRDGIIKAGPAVAVVGQATQIAK
+>ACP44
+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK
+>ACP46
+GIGKFLHSAKKFGKAFVGEIMNS
+>ACP48
+GIGAVLKVLTTGLPALISWIKRKRQQ
+>ACP50
+ALWKNMLKGIGKLAGQAALGAVKTLVGAE
+>ACP52
+ACYCRIPACIAGERRYGTCIYQGRLWAFCC
+>ACP54
+ECRRLCYKQRCVTYCRGR
+>ACP56
+LKLKSIVSWAKKVL
+>ACP58
+KWCFRVCYRGICYRRCR
+>ACP60
+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK
+>ACP62
+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP64
+GLLSVLGSVVKHVIPHVVPVIAEHL
+>ACP66
+GLFKVLGSVAKHLLPHVAPVIAEK
+>ACP68
+GLFGVLGSIAKHVLPHVVPVIAEK
+>ACP70
+GLFVGVLAKVAAHVVPAIAEHF
+>ACP72
+GLFVGLAKVAAHNNPAIAEHFQA
+>ACP74
+GFVDFLKKVAGTIANVVT
+>ACP76
+GLLQTIKEKLESLESLAKGIVSGIQA
+>ACP78
+TRSSRAGLQFPVGRVHRLLRK
+>ACP80
+FFGWLIKGAIHAGKAIHGLIHRRRH
+>ACP82
+GLFDVIKKVASVIGGL
+>ACP84
+GLFDIIKKVASVVGGL
+>ACP86
+GRFKRFRKKFKKLFKKLSPVIPLLHLG
+>ACP88
+GGLRSLGRKILRAWKKYGPIIVPIIRIG
+>ACP90
+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP
+>ACP92
+GLLGPLLKIAAKVGSNLL
+>ACP94
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP96
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP98
+FFHHIFRGIVHVGKTIHRLVTG
+>ACP100
+KLAKLAKKLAKLAK
+>ACP102
+KTCENLADTFRGPCFATSNC
+>ACP104
+IDWKKLLDAAKQIL
+>ACP106
+FLIGMTQGLICLITRKC
+>ACP108
+ILPILSLIGGLLGK
+>ACP110
+GLLGLLGSVVSHVVPAIVGHF
+>ACP112
+GLLGLLGSVVSHVLPAITQHL
+>ACP114
+GIKCRFCCGCCTPGICGVCCRF
+>ACP116
+QSHLSLCRWCCNCCRSNKGC
+>ACP118
+ILGPVISTIGGVLGGLLKNL
+>ACP120
+FLPILASLAAKFGPKLFCLVTKKC
+>ACP122
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP124
+LLGMIPLAISAISALSKL
+>ACP126
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP128
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP130
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP132
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP134
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP136
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP138
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP140
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP142
+GFKDLLKGAAKALVKTVLF
+>ACP144
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP146
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP148
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP150
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP152
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP154
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP156
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP158
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP160
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP162
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP164
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP166
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP168
+VNWKKVLGKIIKVAK
+>ACP170
+VNWKKILGKIIKVAK
+>ACP172
+FFSLLPSLIGGLVSAIK
+>ACP174
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP176
+KWKLFKKIPKFLHLAKKF
+>ACP178
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
+>ACP180
+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP182
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP184
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP186
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP188
+FVDLKKIANIINSIFGK
+>ACP190
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP192
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP194
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP196
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP198
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP200
+GMWSKILGHLIR
+>ACP202
+GKWMSLLKHILK
+>ACP204
+GFGMALKLLKKVL
+>ACP206
+GTGLPMSERRKIMLMMR
+>ACP208
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP210
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP212
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP214
+GDACGETCFTGICFTAGCSCNPWPTCTRN
+>ACP216
+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP218
+IPCGESCVWIPCITAIAGCSCKNKVCYT
+>ACP220
+AIPCGESCVWIPCISTVIGCSCSNKVCYR
+>ACP222
+GEYCGESCYLIPCFTPGCYCVSRQCVNKN
+>ACP224
+IPCGESCVWIPCISGMFGCSCKDKVCYS
+>ACP226
+FLGWLFKWASK
+>ACP228
+FLKWLFKWAKK
+>ACP230
+KWKSFLKTFKSAKKTVLHTALKAISS
+>ACP232
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP234
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP236
+KWKLFKKIGAVLKVL
+>ACP238
+GACFSIAHECGA
+>ACP240
+TCCATGACGTTCCTGACGTT
+>ACP242
+KRFKQDGGASHASPASS
+>ACP244
+KRAKAAGGWSHWSPWSSC
+>ACP246
+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
+>ACP248
+FLGALFKVASKVLPSVKCAITKKC
+>ACP250
+GIGKFLKKAKKFGKAFVKILKK
+>ACP252
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP254
+VECYGPNRPQF
+>ACP256
+KRFKQDGGWSHWSPWSSC
+>ACP258
+RQVFQVAYIIIKA
+>ACP260
+KAFDITYVRLKF
+>ACP262
+DFKLFAVTIKYR
+>ACP264
+DFKLFAVYIKYR
+>ACP266
+WHSDMEWWYLLG
+>ACP268
+HTMYYHHYQHHL
+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Property_Based_Descriptors/Out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Property_Based_Descriptors/Out.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,1 @@
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Property_Based_Descriptors/PDAUG_Sequence_Property_Based_Descriptors.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Property_Based_Descriptors/PDAUG_Sequence_Property_Based_Descriptors.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,158 @@
+import pandas as pd
+from pydpi.pypro import PyPro
+import os
+
+
+def BinaryDescriptor(seq):
+
+    BinaryCode = {
+
+    'A':"1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0",
+    'C':"0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0",
+    'D':"0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0",
+    'E':"0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0",
+    'F':"0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0",
+    'G':"0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0",
+    'H':"0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0",
+    'I':"0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0",
+    'K':"0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0",
+    'L':"0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0",
+    'M':"0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0",
+    'N':"0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0",
+    'P':"0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0",
+    'Q':"0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0",
+    'R':"0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0",
+    'S':"0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0",
+    'T':"0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0",
+    'V':"0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0",
+    'W':"0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0",
+    'Y':"0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1",
+    }
+
+    lines = []
+    Df = []
+     
+
+    for s in seq:
+        des = []
+        for n in s:
+            des.append(BinaryCode[n.upper()])
+        lines.append(','.join(des).split(','))
+
+    df = pd.DataFrame(lines)
+
+    return df
+
+def Decriptor_generator(InFile, Lamda, Weight, DesType, Out_file):
+
+    list_pep_name = []
+    f = open(InFile)
+    lines = f.readlines()
+    
+    for line in lines:
+        if ">" in line:
+            pass
+        else:
+            list_pep_name.append(line.strip('\n'))
+
+    out_df = pd.DataFrame()
+
+    for seq in list_pep_name:
+
+        protein = PyPro()
+        protein.ReadProteinSequence(seq)
+
+        if DesType == 'PAAC':
+            DS = protein.GetPAAC(lamda=int(Lamda), weight=float(Weight))
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'APAAC':
+            DS = protein.GetAPAAC(lamda=int(Lamda), weight=float(Weight))
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'CTD':
+            DS = protein.GetCTD()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'DPComp':
+            DS = protein.GetDPComp()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'GearyAuto':
+            DS = protein.GetGearyAuto()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'MoranAuto':
+            DS = protein.GetMoranAuto()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'MoreauBrotoAuto':
+            DS = protein.GetMoreauBrotoAuto()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'QSO':
+            DS = protein.GetQSO()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'SOCN':
+            DS = protein.GetSOCN()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'TPComp':
+            DS = protein.GetTPComp()
+            df  = pd.DataFrame(DS, index=[0])
+        elif DesType == 'All':
+            DS_1 = protein.GetPAAC(lamda=int(Lamda), weight=float(Weight))
+            DS_2 = protein.GetAPAAC(lamda=int(Lamda), weight=float(Weight))
+            DS_3 = protein.GetCTD()
+            DS_4 = protein.GetDPComp()
+            DS_5 = protein.GetGearyAuto()
+            DS_6 = protein.GetMoranAuto()
+            DS_7 = protein.GetMoreauBrotoAuto()
+            DS_8 = protein.GetQSO()
+            DS_9 = protein.GetSOCN()
+            DS_10 = protein.GetTPComp()
+
+            DS = {}
+
+            for D in (DS_1, DS_2, DS_3, DS_4, DS_5, DS_6, DS_7, DS_8, DS_9, DS_10):
+                DS.update(D)
+
+            df  = pd.DataFrame(DS, index=[0])
+
+        if DesType == 'BinaryDescriptor':
+            out_df = BinaryDescriptor(list_pep_name)
+        else:
+            out_df = pd.concat([out_df, df], axis=0)
+
+
+    out_df.to_csv(Out_file, index=False, sep='\t')
+
+
+if __name__=="__main__":
+    
+    
+    import argparse
+    
+    parser = argparse.ArgumentParser()
+    
+    parser.add_argument("-I", "--InFile",
+                        required=True,
+                        default=None,
+                        help="pep file")
+
+    parser.add_argument("-l", "--Lamda",
+                        required=False,
+                        default=50,
+                        help="pep file")
+
+    parser.add_argument("-w", "--Weight",
+                        required=False,
+                        default=0.5,
+                        help="pep file")
+                        
+    parser.add_argument("-t", "--DesType",
+                        required=True,
+                        default=None,
+                        help="out put file name for str Descriptors")   
+
+    parser.add_argument("-O", "--Out_file",
+                        required=False,  
+                        default="Out.tsv",
+                        help="Path to target tsv file")  
+                              
+    args = parser.parse_args()
+    Decriptor_generator(args.InFile, args.Lamda, args.Weight, args.DesType, args.Out_file)
+
+   
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Property_Based_Descriptors/test-data/Out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Property_Based_Descriptors/test-data/Out.tsv Wed Oct 28 02:36:27 2020 +0000
b
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Property_Based_Descriptors/test-data/Out1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Property_Based_Descriptors/test-data/Out1.tsv Wed Oct 28 02:36:27 2020 +0000
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\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\n+0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t'..b'\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n+0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n+0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n+0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n+0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Sequence_Property_Based_Descriptors/test-data/positive.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Property_Based_Descriptors/test-data/positive.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,16 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLFDIIKKIAESI
+>ACP4
+GLLDIVKKVVGAFGSL
+>ACP6
+GLFDIVKKVVGALGSL
+>ACP8
+GLFDIVKKVVGTLAGL
+>ACP10
+GLFDIAKKVIGVIGSL
+>ACP12
+GLFDIVKKIAGHIAGSI
+>ACP14
+GLFDIVKKIAGHIVSSI
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,57 @@
+import os
+import argparse
+
+
+def TSVtoFASTA(InFile, Method, Positive, Negative, OutFile):
+
+    if Method == 'WithClassLabel':
+
+        f = open(InFile)
+        lines = f.readlines()
+
+        of1 = open(Positive,'w')
+        of2 = open(Negative,'w')
+
+        n = 0
+        m = 0
+
+        for line in lines:
+
+            if '1' in line.split('\t')[1].strip('\n'):
+                n= n+1
+                of1.write('>peptide_'+str(n)+'\n')
+                of1.write(line.split('\t')[0]+'\n')
+
+            if '0' in line.split('\t')[1].strip('\n'):
+                m= m+1
+                of2.write('>peptide_'+str(m)+'\n')
+                of2.write(line.split('\t')[0]+'\n')
+
+    elif Method == 'NoClassLabel':
+
+        f = open(InFile)
+        lines = f.readlines()
+        of1 = open(OutFile,'w')
+
+        for i, line in enumerate(lines[1:]):
+            of1.write('>peptide_'+str(i)+'\n')
+            of1.write(line.split('\t')[0]+'\n')
+
+    else:
+        pass
+
+if __name__=="__main__":
+
+    import argparse
+
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("-I", "--InFile", required=True, default=None, help=".fasta or .tsv")
+    parser.add_argument("-P", "--Postvs", required=False, default='Positive.fasta', help="Path to target tsv file")
+    parser.add_argument("-N", "--Negtvs", required=False, default='Negative.fasta', help="Path to target tsv file")
+    parser.add_argument("-O", "--OutFile", required=False, default='OutFile.fasta', help="Path to target tsv file")
+    parser.add_argument("-M", "--Method", required=True, default=None, help="Path to target tsv file")
+    args = parser.parse_args()
+
+    TSVtoFASTA(args.InFile, args.Method, args.Postvs, args.Negtvs, args.OutFile)
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_TSVtoFASTA/test-data/test1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_TSVtoFASTA/test-data/test1.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,24 @@
+Peptides Class_label
+GLFDIVKKVVGALG 0
+KLLKLLKKKLLK 0
+KLLLLKLLK 0
+GLFDIVKKVVGALG 0
+GLFDIVKKVVGALG 0
+KLLKLLKKKLLK 0
+KLLLLKLLK 0
+GLFDIVKKVVGALG 0
+GLFDIVKKVVGALG 0
+KLLKLLKKKLLK 0
+KLLLLKLLK 0
+GLFDIVKKVVGALG 0
+GLFDIVKKVVGALG 1
+KLLKLLKKKLLK 1
+KLLLLKLLK 1
+GLFDIVKKVVGALG 1
+GLFDIVKKVVGALG 1
+KLLKLLKKKLLK 1
+KLLLLKLLK 1
+GLFDIVKKVVGALG 1
+KLLKLLKKKLLK 1
+KLLLLKLLK 1
+GLFDIVKKVVGALG 1
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_TSVtoFASTA/test-data/test1/Negative.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_TSVtoFASTA/test-data/test1/Negative.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,24 @@
+>peptide_1
+GLFDIVKKVVGALG
+>peptide_2
+KLLKLLKKKLLK
+>peptide_3
+KLLLLKLLK
+>peptide_4
+GLFDIVKKVVGALG
+>peptide_5
+GLFDIVKKVVGALG
+>peptide_6
+KLLKLLKKKLLK
+>peptide_7
+KLLLLKLLK
+>peptide_8
+GLFDIVKKVVGALG
+>peptide_9
+GLFDIVKKVVGALG
+>peptide_10
+KLLKLLKKKLLK
+>peptide_11
+KLLLLKLLK
+>peptide_12
+GLFDIVKKVVGALG
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_TSVtoFASTA/test-data/test1/Positive.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_TSVtoFASTA/test-data/test1/Positive.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,22 @@
+>peptide_1
+GLFDIVKKVVGALG
+>peptide_2
+KLLKLLKKKLLK
+>peptide_3
+KLLLLKLLK
+>peptide_4
+GLFDIVKKVVGALG
+>peptide_5
+GLFDIVKKVVGALG
+>peptide_6
+KLLKLLKKKLLK
+>peptide_7
+KLLLLKLLK
+>peptide_8
+GLFDIVKKVVGALG
+>peptide_9
+KLLKLLKKKLLK
+>peptide_10
+KLLLLKLLK
+>peptide_11
+GLFDIVKKVVGALG
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_TSVtoFASTA/test-data/test2.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_TSVtoFASTA/test-data/test2.tsv Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,24 @@
+Peptides
+GLFDIVKKVVGALG
+KLLKLLKKKLLK
+KLLLLKLLK
+GLFDIVKKVVGALG
+GLFDIVKKVVGALG
+KLLKLLKKKLLK
+KLLLLKLLK
+GLFDIVKKVVGALG
+GLFDIVKKVVGALG
+KLLKLLKKKLLK
+KLLLLKLLK
+GLFDIVKKVVGALG
+GLFDIVKKVVGALG
+KLLKLLKKKLLK
+KLLLLKLLK
+GLFDIVKKVVGALG
+GLFDIVKKVVGALG
+KLLKLLKKKLLK
+KLLLLKLLK
+GLFDIVKKVVGALG
+KLLKLLKKKLLK
+KLLLLKLLK
+GLFDIVKKVVGALG
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_TSVtoFASTA/test-data/test2/Out.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_TSVtoFASTA/test-data/test2/Out.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,69 @@
+>peptide_0
+GLFDIVKKVVGALG
+
+>peptide_1
+KLLKLLKKKLLK
+
+>peptide_2
+KLLLLKLLK
+
+>peptide_3
+GLFDIVKKVVGALG
+
+>peptide_4
+GLFDIVKKVVGALG
+
+>peptide_5
+KLLKLLKKKLLK
+
+>peptide_6
+KLLLLKLLK
+
+>peptide_7
+GLFDIVKKVVGALG
+
+>peptide_8
+GLFDIVKKVVGALG
+
+>peptide_9
+KLLKLLKKKLLK
+
+>peptide_10
+KLLLLKLLK
+
+>peptide_11
+GLFDIVKKVVGALG
+
+>peptide_12
+GLFDIVKKVVGALG
+
+>peptide_13
+KLLKLLKKKLLK
+
+>peptide_14
+KLLLLKLLK
+
+>peptide_15
+GLFDIVKKVVGALG
+
+>peptide_16
+GLFDIVKKVVGALG
+
+>peptide_17
+KLLKLLKKKLLK
+
+>peptide_18
+KLLLLKLLK
+
+>peptide_19
+GLFDIVKKVVGALG
+
+>peptide_20
+KLLKLLKKKLLK
+
+>peptide_21
+KLLLLKLLK
+
+>peptide_22
+GLFDIVKKVVGALG
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Uversky_Plot/PDAUG_Uversky_Plot.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Uversky_Plot/PDAUG_Uversky_Plot.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,61 @@
+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)
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Uversky_Plot/test-data/out.png
b
Binary file PDAUG_Uversky_Plot/test-data/out.png has changed
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Uversky_Plot/test-data/test1.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Uversky_Plot/test-data/test1.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>ACP0
+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV
+>ACP2
+GLFDIIKKIAESI
+>ACP4
+GLLDIVKKVVGAFGSL
+>ACP6
+GLFDIVKKVVGALGSL
+>ACP8
+GLFDIVKKVVGTLAGL
+>ACP10
+GLFDIAKKVIGVIGSL
+>ACP12
+GLFDIVKKIAGHIAGSI
+>ACP14
+GLFDIVKKIAGHIVSSI
+>ACP16
+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF
+>ACP18
+HGVSGHGQHGVHG
+>ACP20
+FKCRRWQWRMKKLGAPSITCVRRAF
+>ACP22
+KWKLFKKIKFLHSAKKF
+>ACP24
+KSSAYSLQMGATAIKQVKKLFKKWGW
+>ACP26
+GIGTKILGGVKTALKGALKELASTYAN
+>ACP28
+GIGGKILSGLKTALKGAAKELASTYLH
+>ACP30
+GIGGVLLSAGKAALKGLAKVLAEKYAN
+>ACP32
+SIGAKILGGVKTFFKGALKELASTYLQ
+>ACP34
+FLPLLAGLAANFLPTIICKISYKC
+>ACP36
+FVQWFSKFLGRIL
+>ACP38
+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL
+>ACP40
+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK
+>ACP42
+KWKLFKKIEKVGQNIRDGIIKAGPAVAVVGQATQIAK
+>ACP44
+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK
+>ACP46
+GIGKFLHSAKKFGKAFVGEIMNS
+>ACP48
+GIGAVLKVLTTGLPALISWIKRKRQQ
+>ACP50
+ALWKNMLKGIGKLAGQAALGAVKTLVGAE
+>ACP52
+ACYCRIPACIAGERRYGTCIYQGRLWAFCC
+>ACP54
+ECRRLCYKQRCVTYCRGR
+>ACP56
+LKLKSIVSWAKKVL
+>ACP58
+KWCFRVCYRGICYRRCR
+>ACP60
+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK
+>ACP62
+GLLSVLGSVAKHVLPHVVPVIAEHL
+>ACP64
+GLLSVLGSVVKHVIPHVVPVIAEHL
+>ACP66
+GLFKVLGSVAKHLLPHVAPVIAEK
+>ACP68
+GLFGVLGSIAKHVLPHVVPVIAEK
+>ACP70
+GLFVGVLAKVAAHVVPAIAEHF
+>ACP72
+GLFVGLAKVAAHNNPAIAEHFQA
+>ACP74
+GFVDFLKKVAGTIANVVT
+>ACP76
+GLLQTIKEKLESLESLAKGIVSGIQA
+>ACP78
+TRSSRAGLQFPVGRVHRLLRK
+>ACP80
+FFGWLIKGAIHAGKAIHGLIHRRRH
+>ACP82
+GLFDVIKKVASVIGGL
+>ACP84
+GLFDIIKKVASVVGGL
+>ACP86
+GRFKRFRKKFKKLFKKLSPVIPLLHLG
+>ACP88
+GGLRSLGRKILRAWKKYGPIIVPIIRIG
+>ACP90
+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP
+>ACP92
+GLLGPLLKIAAKVGSNLL
+>ACP94
+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI
+>ACP96
+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK
+>ACP98
+FFHHIFRGIVHVGKTIHRLVTG
+>ACP100
+KLAKLAKKLAKLAK
+>ACP102
+KTCENLADTFRGPCFATSNC
+>ACP104
+IDWKKLLDAAKQIL
+>ACP106
+FLIGMTQGLICLITRKC
+>ACP108
+ILPILSLIGGLLGK
+>ACP110
+GLLGLLGSVVSHVVPAIVGHF
+>ACP112
+GLLGLLGSVVSHVLPAITQHL
+>ACP114
+GIKCRFCCGCCTPGICGVCCRF
+>ACP116
+QSHLSLCRWCCNCCRSNKGC
+>ACP118
+ILGPVISTIGGVLGGLLKNL
+>ACP120
+FLPILASLAAKFGPKLFCLVTKKC
+>ACP122
+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS
+>ACP124
+LLGMIPLAISAISALSKL
+>ACP126
+GLPVCGETCVGGTCNTPGCSCSWPVCTRN
+>ACP128
+GVPICGETCTLGTCYTAGCSCSWPVCTRN
+>ACP130
+GIPCGESCVWIPCISSAIGCSCKSKVCYRN
+>ACP132
+GIPCAESCVWIPCTVTALIGCGCSNKVCYN
+>ACP134
+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN
+>ACP136
+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN
+>ACP138
+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL
+>ACP140
+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS
+>ACP142
+GFKDLLKGAAKALVKTVLF
+>ACP144
+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK
+>ACP146
+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK
+>ACP148
+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK
+>ACP150
+MRKEFHNVLSSGQLLADKRPARDYNRK
+>ACP152
+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK
+>ACP154
+FIFHIIKGLFHAGKMIHGLVTRRRH
+>ACP156
+FLPAIVGAAAKFLPKIFCAISKKC
+>ACP158
+FLPIIAGVAAKVLPKIFCAISKKC
+>ACP160
+FLPIIAGIAAKFLPKIFCTISKKC
+>ACP162
+FLPVIAGVAANFLPKLFCAISKKC
+>ACP164
+FLPIIAGAAAKVVQKIFCAISKKC
+>ACP166
+GLMDTIKGVAKTVAASWLDKLKCKITGC
+>ACP168
+VNWKKVLGKIIKVAK
+>ACP170
+VNWKKILGKIIKVAK
+>ACP172
+FFSLLPSLIGGLVSAIK
+>ACP174
+RFRLPFRRPPIRIHPPPFYPPFRRFL
+>ACP176
+KWKLFKKIPKFLHLAKKF
+>ACP178
+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG
+>ACP180
+GIPCGESCVFIPCITGAIGCSCKSKVCYRN
+>ACP182
+GEFLKCGESCVQGECYTPGCSCDWPICKKN
+>ACP184
+GLPTCGETCTLGTCYVPDCSCSWPICMKN
+>ACP186
+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN
+>ACP188
+FVDLKKIANIINSIFGK
+>ACP190
+GSIPCGESCVFIPCISSVIGCACKSKVCYKN
+>ACP192
+GIPCGESCVFIPCISSVIGCSCSSKVCYRN
+>ACP194
+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN
+>ACP196
+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN
+>ACP198
+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN
+>ACP200
+GMWSKILGHLIR
+>ACP202
+GKWMSLLKHILK
+>ACP204
+GFGMALKLLKKVL
+>ACP206
+GTGLPMSERRKIMLMMR
+>ACP208
+GIACGESCVFLGCFIPGCSCKSKVCYFN
+>ACP210
+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD
+>ACP212
+KLCGETCFKFKCYTPGCSCSYPFCK
+>ACP214
+GDACGETCFTGICFTAGCSCNPWPTCTRN
+>ACP216
+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN
+>ACP218
+IPCGESCVWIPCITAIAGCSCKNKVCYT
+>ACP220
+AIPCGESCVWIPCISTVIGCSCSNKVCYR
+>ACP222
+GEYCGESCYLIPCFTPGCYCVSRQCVNKN
+>ACP224
+IPCGESCVWIPCISGMFGCSCKDKVCYS
+>ACP226
+FLGWLFKWASK
+>ACP228
+FLKWLFKWAKK
+>ACP230
+KWKSFLKTFKSAKKTVLHTALKAISS
+>ACP232
+KWKSFLKTFKSLKKTVLHTLLKAISS
+>ACP234
+MPFLFCNVNDVCNFASRNDYSCNYYSNSYSFWLASLNPER
+>ACP236
+KWKLFKKIGAVLKVL
+>ACP238
+GACFSIAHECGA
+>ACP240
+TCCATGACGTTCCTGACGTT
+>ACP242
+KRFKQDGGASHASPASS
+>ACP244
+KRAKAAGGWSHWSPWSSC
+>ACP246
+LLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES
+>ACP248
+FLGALFKVASKVLPSVKCAITKKC
+>ACP250
+GIGKFLKKAKKFGKAFVKILKK
+>ACP252
+GIGKFLKKAKKGIGAVLKVLTTGL
+>ACP254
+VECYGPNRPQF
+>ACP256
+KRFKQDGGWSHWSPWSSC
+>ACP258
+RQVFQVAYIIIKA
+>ACP260
+KAFDITYVRLKF
+>ACP262
+DFKLFAVTIKYR
+>ACP264
+DFKLFAVYIKYR
+>ACP266
+WHSDMEWWYLLG
+>ACP268
+HTMYYHHYQHHL
+>ACP270
+RLVSYNGIIFFLK
+>ACP272
+GRENYHGCTTHWGFTLC
+>ACP274
+ASSSYPLIHWRPWAR
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Uversky_Plot/test-data/test2.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Uversky_Plot/test-data/test2.fasta Wed Oct 28 02:36:27 2020 +0000
b
@@ -0,0 +1,276 @@
+>non-ACP0
+MTISLIWGIAMVVCCCIWVIFDRRRRKAGEPPL
+>non-ACP2
+MFATPLRQPTNASGARPAVSMDGQETPFQYEITD
+>non-ACP4
+LLWRKVAGATVGPGPVPA
+>non-ACP6
+DSPDPMNGASSNALIAKMNSAKLLYQHY
+>non-ACP8
+NNQEVIDAISQAISQTPGCVL
+>non-ACP10
+KKVVEKNADPETTLLVYLRRKLGLCGTKLGCGEG
+>non-ACP12
+CSRLLPSLAQEEG
+>non-ACP14
+KNDFAALQAKLDADAAEIEKWWSDSR
+>non-ACP16
+VDREQLVQKARLAEQAERYDD
+>non-ACP18
+RPLRRVVLFYQGKLCSMAGNFWQSSHYLQW
+>non-ACP20
+GAAGERKLCLLSLLLIGA
+>non-ACP22
+MFRKLLKMWILLRPTHWLILIALCAVTCAGYWLLWSE
+>non-ACP24
+HLRGPADSGWMPQAAPCLSGAPQAS
+>non-ACP26
+NNPNNSNSHLRPHAYNNSRRDDSD
+>non-ACP28
+VVILASLSVMFLVSLWQQKIRERLPPGPTPLPFIGNY
+>non-ACP30
+ICLSCLISFFLWNQNRAKGKLPPG
+>non-ACP32
+VVMNSLRVILQAS
+>non-ACP34
+ARPRLDLQLVQRFVRIQKVF
+>non-ACP36
+MLAKGLSLRSVLAKGCQPFLSPTWQSSVLATGGGANIS
+>non-ACP38
+AAGLPGAALPLRKRPLRAPSPEPAAPRGAAGLVV
+>non-ACP40
+PPMPSAPPVHPPP
+>non-ACP42
+SCPIDKRRPLIAFLRRLRD
+>non-ACP44
+RLGLWASGLILILGFLKLLRLLLRRQRLARAMD
+>non-ACP46
+FSPQRDRFQAEGS
+>non-ACP48
+GTLWALVFLGILVGMVVPSPAGTRANNTLLDSRG
+>non-ACP50
+MNRLLQKGTSLVPSWRTR
+>non-ACP52
+MTTSLIWGIAIAACCCLWLILGIRRRQT
+>non-ACP54
+ATLANGMSLQPPLEEVS
+>non-ACP56
+PLTATNSGLAVNN
+>non-ACP58
+VRACHKVCRCLLSGFGGRVDAGQPELLTER
+>non-ACP60
+TAGILLLLLLGTLEGS
+>non-ACP62
+MEPSILLLLALLVGFLLLLVRGH
+>non-ACP64
+MKNCFQLLCNLKVPAAGFKNTVKS
+>non-ACP66
+SVIHTQAHASGLQQVPQLVPAGPGGGGKAVAPSKQSK
+>non-ACP68
+KPLGLLKPSSLMKVSGRFKAHQDA
+>non-ACP70
+ARTLNNKLSLSKPKFSGFT
+>non-ACP72
+LLLVIIWTLFGPSGLGEELLSLSLASLLPAPASPGPP
+>non-ACP74
+WPGILVGGARVASCRYPALGPRLA
+>non-ACP76
+RSVKGLVALITGGASGL
+>non-ACP78
+AAAALRARILQVSSKVN
+>non-ACP80
+TGCCIAGRLANLDDQNLTVAL
+>non-ACP82
+GSILGFLQIATVLTVLLLLLK
+>non-ACP84
+AARQIGSCLMRCRTLDTTSP
+>non-ACP86
+WGCRGRRWAFARVDGGSCHRRGAPTGSTSNQIR
+>non-ACP88
+YAKPGAVRSPAQILQWQVLPNTVPAKS
+>non-ACP90
+RMAGPWLSLHEARLLGTRGAAAPKAV
+>non-ACP92
+SISNRAAVPEHGVAPDAERL
+>non-ACP94
+PNFSMETWLLLV
+>non-ACP96
+PRPPSKTYRGAFQN
+>non-ACP98
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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Word_Vector_Descriptor/PDAUG_Word_Vector_Descriptor.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Word_Vector_Descriptor/PDAUG_Word_Vector_Descriptor.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,59 @@
+import numpy as np
+import os
+import pandas as pd
+from Bio import SeqIO
+from nltk import bigrams
+from nltk import trigrams
+import gensim
+import argparse
+
+parser = argparse.ArgumentParser()
+
+parser.add_argument("-M", "--ModelInput", required=True, default=None, help="Path to target tsv file")
+parser.add_argument("-R", "--row", required=True, default=None, help="Path to target tsv file")
+parser.add_argument("-I", "--InputFasta", required=True, default=6, help="Path to target tsv file")
+parser.add_argument("-O", "--OutFile", required=False, default='model.txt', help="Path to target tsv file")
+parser.add_argument("-P", "--positive", required=True, help="Path to target tsv file")
+parser.add_argument("-N", "--negative", required=True, help="Path to target tsv file")
+
+args = parser.parse_args()
+
+seed = 42
+np.random.seed(seed)
+
+new_model = gensim.models.KeyedVectors.load_word2vec_format(args.ModelInput, binary=False)
+
+import time
+t0 = time.time()
+
+temp_word = np.zeros(shape=(int(args.row), 200))
+
+for index, seqs in enumerate(SeqIO.parse(args.InputFasta, 'fasta')):
+    seq_sum = 0
+    tri_seq = trigrams(seqs.seq)
+    for item in ((tri_seq)):
+        tri_str = item[0] + item[1] + item[2]
+        if tri_str not in list(new_model.wv.vocab):
+            continue
+        seq_sum = seq_sum + new_model[tri_str]
+
+    temp_word[index] = seq_sum
+
+t1 = time.time()
+
+
+temp_word = temp_word
+
+
+clm = [x for x in range(0,temp_word.shape[1])]
+y_temp_word = np.vstack((np.ones((int(args.positive), 1)), np.zeros((int(args.negative),1))))
+
+c, r = y_temp_word.shape
+y_temp_word = y_temp_word.reshape(c,)
+
+class_label = pd.DataFrame(y_temp_word, columns=["Class_label"])
+
+df = pd.DataFrame(temp_word, columns=clm)
+df = pd.concat([df,class_label], axis=1)
+
+df.to_csv(args.OutFile, index=None, sep="\t")
\ No newline at end of file
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Word_Vector_Descriptor/test-data/Out.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Word_Vector_Descriptor/test-data/Out.tsv Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,277 @@\n+0\t1\t2\t3\t4\t5\t6\t7\t8\t9\t10\t11\t12\t13\t14\t15\t16\t17\t18\t19\t20\t21\t22\t23\t24\t25\t26\t27\t28\t29\t30\t31\t32\t33\t34\t35\t36\t37\t38\t39\t40\t41\t42\t43\t44\t45\t46\t47\t48\t49\t50\t51\t52\t53\t54\t55\t56\t57\t58\t59\t60\t61\t62\t63\t64\t65\t66\t67\t68\t69\t70\t71\t72\t73\t74\t75\t76\t77\t78\t79\t80\t81\t82\t83\t84\t85\t86\t87\t88\t89\t90\t91\t92\t93\t94\t95\t96\t97\t98\t99\t100\t101\t102\t103\t104\t105\t106\t107\t108\t109\t110\t111\t112\t113\t114\t115\t116\t117\t118\t119\t120\t121\t122\t123\t124\t125\t126\t127\t128\t129\t130\t131\t132\t133\t134\t135\t136\t137\t138\t139\t140\t141\t142\t143\t144\t145\t146\t147\t148\t149\t150\t151\t152\t153\t154\t155\t156\t157\t158\t159\t160\t161\t162\t163\t164\t165\t166\t167\t168\t169\t170\t171\t172\t173\t174\t175\t176\t177\t178\t179\t180\t181\t182\t183\t184\t185\t186\t187\t188\t189\t190\t191\t192\t193\t194\t195\t196\t197\t198\t199\tClass_label\n+0.002876069862395525\t0.002013152465224266\t-0.0005238864105194807\t0.0017881660023704171\t0.000319159182254225\t-0.0071934545412659645\t0.0039251516573131084\t-0.000510123441927135\t-0.0010993408504873514\t-0.0002281799679622054\t0.0014749051770195365\t-0.004189853556454182\t0.0018875706009566784\t-0.0007796559948474169\t-0.003969023935496807\t0.001283580670133233\t-0.0017550631891936064\t0.0013466394739225507\t-3.155902959406376e-06\t-0.0033632917329669\t0.001160646672360599\t-0.0004998227814212441\t0.003861493431031704\t0.00011926196748390794\t-0.0016997053753584623\t0.005056729074567556\t0.005311000160872936\t-0.0008090301416814327\t0.00044636079110205173\t-0.0045272731222212315\t0.004110256675630808\t-0.0015549850650131702\t-0.0007750039803795516\t0.00042370252776890993\t-0.0017250602832064033\t0.001877370523288846\t-0.003908749204128981\t-0.0010796056594699621\t-0.003010125830769539\t-0.0028565460816025734\t0.002224354073405266\t-0.0004807154182344675\t0.003372298553586006\t-0.00043598588672466576\t0.0031427869107574224\t-0.004692027345299721\t0.001822689431719482\t0.002597606973722577\t-0.004055988974869251\t-0.0029732491821050644\t-0.0010350901866331697\t-0.006303225643932819\t-0.002266238210722804\t-0.0005199923180043697\t0.0019003931665793061\t-0.0008069402538239956\t-0.0037824236787855625\t0.004136097617447376\t-0.0016465353546664119\t-0.0023379067424684763\t0.004037674516439438\t0.002427662257105112\t0.0011565430322661996\t0.004617234691977501\t0.0019813119433820248\t0.0052543869242072105\t-0.002208664081990719\t-0.0004645588924176991\t-0.00480070011690259\t-0.0032663242891430855\t-0.0023334191646426916\t-0.0005391393206082284\t0.0021192007698118687\t0.007203095592558384\t0.0042351591400802135\t-0.001509595662355423\t0.0014238443691283464\t-0.0014259959571063519\t-0.00013511617726180702\t0.0014671704266220331\t-0.0005564049351960421\t-5.0973379984498024e-05\t0.0009148565586656332\t-0.007398918271064758\t0.001923304982483387\t-0.0008495715446770191\t0.0021623754873871803\t-0.0013175734784454107\t0.00027500116266310215\t0.004394028801470995\t0.00329958857037127\t0.0021894993260502815\t0.005145960953086615\t0.004010985139757395\t0.003553807269781828\t0.0032821199856698513\t-0.001331946114078164\t0.0019571897573769093\t-0.006515602581202984\t0.0001817885786294937\t-0.004057625774294138\t0.0036399890668690205\t-0.0022683748975396156\t0.0024700951762497425\t-0.002987832296639681\t-0.0006394851952791214\t0.0017209271900355816\t-0.004949362017214298\t0.0019073416478931904\t0.002606908557936549\t0.0011787557741627097\t-0.002450707368552685\t0.0057587577030062675\t-0.0026086405850946903\t0.0022303923033177853\t0.0007399451569654047\t-0.0032068295404314995\t0.0020249306689947844\t0.001498427358455956\t-0.0031375070102512836\t-0.0006856690160930157\t0.0009135162690654397\t0.005077754147350788\t0.0023851783480495214\t-0.0016735880635678768\t-0.003467921633273363\t-0.001806486165151\t-0.002326409798115492\t-0.003571863751858473\t0.0016521911602467299\t0.005409293808043003\t0.0008614042308181524\t-0.0018883243901655078\t-0.004356382414698601\t0.0009951991960406303\t0.0013880426995456219\t0.0006064275512471795\t-0.001376464730128646\t0.00035494938492774963\t-0.0025893808342516422\t0.0025832278188318014\t0.003092242404818535\t0.0008804391254670918\t-0.0013823560439050198\t0.0044525726698338985\t0.0003783945576287806\t-0.004836831241846085\t0.00022665434516966343\t0.00'..b'3\t0.002033377531915903\t-0.0026495899073779583\t0.002146740909665823\t-0.005084071774035692\t-0.0010867954697459936\t0.0017109132604673505\t0.0019064857624471188\t-0.003993979189544916\t0.00200260104611516\t0.0022234623320400715\t0.0028521092608571053\t0.0021870594937354326\t0.0027028180193156004\t-0.0045691849663853645\t0.0034677640069276094\t0.001078806002624333\t-0.0010664219735190272\t-0.0010229990584775805\t-0.0020179725252091885\t0.003001515520736575\t0.0009787147864699364\t-0.0018394901417195797\t-0.0015334836207330227\t0.0012183168437331915\t0.005557340569794178\t-0.0017923970008268952\t0.002285949420183897\t0.00306733185425400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b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Word_Vector_Descriptor/test-data/model.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Word_Vector_Descriptor/test-data/model.txt Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,567 @@\n+566 200\n+SLK 0.001365332 -0.0017459366 -0.00080282777 0.0011080382 -0.0020799749 0.0023665277 0.00064222724 -0.00020277791 -0.0024961173 0.0017166281 0.0016223168 -0.00068261253 -0.0018985914 0.002186477 -0.001368902 -0.0022669677 -0.0009672694 0.0020265202 -0.00024468428 -0.0013020429 -0.0017395875 0.0016356348 -0.00079645164 0.0023032813 0.0024860792 -0.002388357 -0.0014398484 0.00140585 -0.0003748012 -0.0018963028 -0.00017838413 -0.00024190723 0.00024986145 0.002378538 -0.0017191146 0.0023616562 0.001670377 -0.0006269774 -0.0010054546 -0.0011329858 -0.002181357 -0.0020793916 0.002035759 -0.0010104823 0.001482032 -0.0010092463 0.001162038 -0.0023821024 0.00028114635 9.705908e-05 0.0016195059 -0.00094875274 0.0009430515 -0.002029896 0.0018548059 0.0015280207 -0.00028816742 -6.1781415e-05 -0.00077087915 0.0020475688 8.588983e-05 0.00056099205 6.22821e-05 -0.0013446079 -0.0014237356 0.00075389433 -0.00020252455 -0.00095345493 -0.0007824703 -6.162045e-05 0.0013330202 0.0012728372 0.00080652465 0.0008436353 -0.00021207609 -0.00042457427 0.0024297654 -0.0019191144 0.0012694756 -0.001921155 -0.002058659 -0.0018455927 -0.00024249138 0.0005863274 0.001842689 0.0017758207 0.0018838848 0.00086066633 0.0009819923 0.0008530649 0.002333635 -0.00085565896 0.0010997982 0.00025894376 0.0006055406 0.0023264794 -0.0022238959 -0.0010392709 -0.0014932489 -0.00032574497 0.0016898713 6.475457e-05 -0.00020890188 -0.0020446135 0.001034813 0.0024149076 0.00049705803 0.00037050515 -0.0010721524 0.0014172499 4.999024e-05 -0.0023446355 -0.0006348178 -0.0012540983 0.0018404622 -0.0003905339 0.00080044504 -0.0023580764 -0.0022149365 0.0020088993 -0.0017798219 -0.0015909666 0.001320036 0.0014704384 0.0014685178 0.001332087 0.0014647129 0.00032574587 0.0011028486 -0.0016243214 -0.0009946597 -0.00050526607 -0.00020703339 -0.00022913209 0.0010527589 -0.0023309358 0.0007664553 -5.982858e-05 -0.00026066264 -0.0006642904 -0.0017259198 -0.0019114831 -0.0002447919 -0.000932948 0.0011330452 0.00060474453 -0.00040816146 0.0024577135 0.0020908166 -0.00016210739 -0.0013720029 0.0022247606 -0.0004630553 -0.002023366 0.0010714133 0.0010599708 0.0024086582 1.5625536e-05 -0.00033240227 0.0007969802 0.0024127767 -0.0005245974 0.0023930564 -0.002065922 -0.00049742655 0.00075228175 0.0012057236 -0.0021796646 -0.0017681125 0.002240387 -0.0015084597 2.8815777e-05 0.00062441436 0.0017449431 -0.00060599134 -0.00016037462 -0.0019211516 -0.00083369436 -0.0017688617 -0.0012831012 0.0018926467 -0.00082292286 0.00015296093 -0.00056383596 -0.000414889 -0.0004348078 -0.0021617427 -0.0022588358 -0.0018406851 -0.00062651787 0.0017154918 0.0023480973 -0.0023299463 0.00028671883 0.0012787611 -0.0020714088 0.0011408264 -0.0013465516 0.0015014345 -0.0017432373\n+LVC -1.2101434e-05 -0.0022298675 0.001447321 -0.0013246932 0.00057933765 -0.002318466 0.001946672 -0.0009749499 -0.0020036546 -0.00085358316 -0.0008264022 -0.0002964486 0.000796339 0.0021234967 0.0016650832 0.0008551463 -0.0019276019 0.0011267059 2.823315e-05 -0.0015146568 -0.001965077 0.0006863515 -0.0015384579 0.0024484461 0.0018394345 -0.00084675086 -6.0793493e-05 0.002531608 0.0024579482 0.00036317756 0.00021481325 -0.0014953372 -0.0010072981 -0.0020482857 -0.0017800514 -0.0012966199 0.0017186782 0.0011799947 0.0007498256 -0.0021813198 0.0006652456 0.0021067823 -2.0717955e-05 0.002445156 -0.002240867 0.00045164707 0.0018858616 -0.0023328154 0.0011247616 -0.0003575369 0.0011778875 -0.0008954814 -0.0017944037 0.0015972335 0.0008786754 0.000983835 -0.00030637544 0.0005728325 0.002248167 0.0008306682 0.00105836 0.0018650618 0.0022743535 0.00028581268 0.00071605446 -0.00024169416 0.0011736357 0.0006689531 -0.0018869323 -0.00023115014 0.0009952596 -0.0015211194 0.0015442141 -0.000500582 -0.0014211049 -0.0018496842 -0.000335584 -0.0007210559 0.00015120191 0.00039644202 0.0010430668 -0.00044082105 -0.0017261596 0.0001878975 -6.498627e-06 -0.00041374264 -0.0022203664 0.0018215046 0.00023135482 0.00062350027 0.0021234509'..b'9329166 0.00083683885 -0.0012966121 -0.000420821 0.0012175398 -0.0014267633 0.001252249 0.0016301421 -0.0019441452 -0.0007565895 0.0023559122 -7.5507046e-06 -0.0013640765 -0.0014484831 0.0013146921 -0.00070724834 0.0006098803 0.001090075 0.0017408988 -0.001816694 0.00065133127 0.0014607466 -0.0019121281 -0.0019158301 0.00092410535 0.0023605211 0.0004920717 0.00088350684 0.0010997092 3.324904e-06 0.0021491952 0.0011182296 -9.8608805e-05 0.0020175215 0.0016764243 1.0548103e-05 -0.0017188648 -0.00072903285 0.0024229095 -0.0010821237 0.0009385571 -0.0013538856 -0.0016275204 -0.0018933859 0.000107686 0.0013027365 -0.0019094732 -0.00116395 0.0007673889 0.0023619593 0.0007082056 0.00045266104 -0.0020115129 0.002031747 -0.0019755852 0.00026481098 0.0003243022 -0.0020673268 0.0014138616 0.00065170706 -0.0011964287 -0.002201478 -0.0012715297 -0.0010389787 -0.0014538697 -0.0018862948 0.0010369697 0.0020708728 0.000986399 1.6503946e-05 -0.00059497467 0.0005850068 -0.0005638295 -0.002096313 0.002155895 -0.0017137764 0.0019099646 0.00109993 -0.0009016919 -0.00026621978 0.0011989886 -0.00095179136 3.3868637e-05 0.001603786 0.0006490003 0.000836424 0.0014219693 0.0015205769 0.0006233736 -0.0026071914 -0.0017951333 0.0010369756 -7.279905e-06 -0.00030341622 0.0020297645\n+RTT 0.0008749674 0.00096788583 0.00046035784 0.0016080411 -0.0014414618 0.0014620025 -4.0255152e-05 0.00045544843 0.001784968 0.0023198745 -4.6789242e-05 -0.0008355484 0.000529331 -0.0012765506 0.00095468503 0.0014647499 -0.00076876057 0.0010658011 0.0016611569 0.0013699844 0.0023904063 0.0012192386 0.0011243214 -0.0012805273 -0.0006703495 -0.0012319596 0.00051839405 0.001952754 0.0008436256 -0.0015916091 -0.0011713775 0.000609642 -0.0014617583 0.0022987772 -0.0008756762 -0.0002850732 -9.186468e-05 0.0015565944 0.0021467975 0.001879534 -0.0009571439 0.0025193726 0.00070011965 0.00014257328 -0.0012639355 -0.0017070648 0.00011292961 0.001955303 -0.0023525355 -0.0024229723 0.0016758887 -0.001555089 -0.0012256737 -0.0014706277 -0.0011813928 -0.0008920257 -0.00070989813 0.0016142618 6.2340194e-05 -0.0013028994 -0.00041547752 0.0017577651 -0.0013958853 0.00019386491 -0.0011342029 0.0009555548 0.0015859862 0.0010165847 0.0023251616 0.0024807346 -0.0001621106 0.0009780871 -0.0021544576 -0.0016797123 -0.0019976767 0.0023287062 -0.0005807063 -0.0010508454 -0.0011735009 0.0009913616 -0.0023642706 0.0010660653 -0.0011858979 0.00059610215 0.0008311239 -0.00092363905 0.0013755945 0.00037625633 0.002422985 -0.0016978119 -0.0013139286 0.000529977 -0.0011911308 -0.0023673559 0.00020641256 -0.0015232897 -0.0002883984 -0.0012487182 -0.00046426966 -0.0009833992 0.0018450054 0.0002375337 0.001846433 -0.0017698813 -0.002041315 -0.0008291253 -0.0005597482 0.0011917122 0.00015343283 -0.0011826177 0.002399056 0.0006649859 -0.0017162617 -0.00086710486 0.00016337876 -0.0008963979 -0.0014059466 -0.0023056318 -0.00063665456 0.0013866306 0.001834191 0.0024510582 -0.0008367855 9.572251e-07 0.0019129917 -0.00024920254 -0.002109615 0.0014992991 0.002470077 -0.0015247426 0.0021252346 0.0003277864 -0.00013354525 0.00068446604 0.0024241658 -0.001372545 0.0012075508 -0.0018025833 -0.00038149007 0.00037644224 0.0018547113 0.0018578246 -0.0020145597 -1.42324225e-05 0.0021410969 0.00025578332 8.691112e-05 -0.0017239064 -0.0012059687 -0.0019051972 0.00064171746 0.0024287626 0.0007367608 0.0012890009 0.0012271192 0.00032794752 0.0010868037 -0.0010993943 0.00021350925 0.001333526 -5.4828255e-05 0.0011917402 0.0011615263 0.001149004 0.00055940665 0.00021172808 0.0007953479 -0.00045935702 -0.0015195387 0.0016530926 0.0018495353 0.0010670543 0.00029422963 -0.0010919494 0.0010870786 -0.0021665462 -0.0007957788 -0.002275716 -0.0012395901 -0.001598635 0.00031872877 -0.00020240767 -0.0020836846 -0.00056924846 -0.0019875302 -0.0013354532 -0.0006294266 0.0022098403 -0.0008797699 -0.00035938426 -0.0023506682 0.0018134243 0.0018999709 0.0014204925 -0.00048301555 -0.001929654 0.0013711938 0.00044136978 -0.00092774484 0.0009801525\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Word_Vector_Descriptor/test-data/test.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Word_Vector_Descriptor/test-data/test.fasta Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,552 @@\n+>ACP\n+GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV\n+>ACP\n+GLFDIIKKIAESI\n+>ACP\n+GLLDIVKKVVGAFGSL\n+>ACP\n+GLFDIVKKVVGALGSL\n+>ACP\n+GLFDIVKKVVGTLAGL\n+>ACP\n+GLFDIAKKVIGVIGSL\n+>ACP\n+GLFDIVKKIAGHIAGSI\n+>ACP\n+GLFDIVKKIAGHIVSSI\n+>ACP\n+AACARFIDDFCDTLTPNIYRPRDNGQRCYAVNGHRCDFTVFNTNNGGNPIRASTPNCKTVLRTAANRCPTGGRGKINPNAPFLFAIDPNDGDCSTNF\n+>ACP\n+HGVSGHGQHGVHG\n+>ACP\n+FKCRRWQWRMKKLGAPSITCVRRAF\n+>ACP\n+KWKLFKKIKFLHSAKKF\n+>ACP\n+KSSAYSLQMGATAIKQVKKLFKKWGW\n+>ACP\n+GIGTKILGGVKTALKGALKELASTYAN\n+>ACP\n+GIGGKILSGLKTALKGAAKELASTYLH\n+>ACP\n+GIGGVLLSAGKAALKGLAKVLAEKYAN\n+>ACP\n+SIGAKILGGVKTFFKGALKELASTYLQ\n+>ACP\n+FLPLLAGLAANFLPTIICKISYKC\n+>ACP\n+FVQWFSKFLGRIL\n+>ACP\n+KWKIFKKIEKVGRNIRNGIIKAGPAVAVLGEAKAL\n+>ACP\n+GWLKKIGKKIERVGQHTRDATIQTIGVAQQAANVAATLK\n+>ACP\n+KWKLFKKIEKVGQNIRDGIIKAGPAVAVVGQATQIAK\n+>ACP\n+SQLGDLGSGAGQGGGGGGSIRAAGGAFGKLEAAREEEFFYKKQKEQLERLKNDQIHQAEFHHQQIKEHEEAIQRHKDFLNNLHK\n+>ACP\n+GIGKFLHSAKKFGKAFVGEIMNS\n+>ACP\n+GIGAVLKVLTTGLPALISWIKRKRQQ\n+>ACP\n+ALWKNMLKGIGKLAGQAALGAVKTLVGAE\n+>ACP\n+ACYCRIPACIAGERRYGTCIYQGRLWAFCC\n+>ACP\n+ECRRLCYKQRCVTYCRGR\n+>ACP\n+LKLKSIVSWAKKVL\n+>ACP\n+KWCFRVCYRGICYRRCR\n+>ACP\n+KSCCRNTWARNCYNVCRLPGTISREICAKKCDCKIISGTTCPSDYPK\n+>ACP\n+GLLSVLGSVAKHVLPHVVPVIAEHL\n+>ACP\n+GLLSVLGSVVKHVIPHVVPVIAEHL\n+>ACP\n+GLFKVLGSVAKHLLPHVAPVIAEK\n+>ACP\n+GLFGVLGSIAKHVLPHVVPVIAEK\n+>ACP\n+GLFVGVLAKVAAHVVPAIAEHF\n+>ACP\n+GLFVGLAKVAAHNNPAIAEHFQA\n+>ACP\n+GFVDFLKKVAGTIANVVT\n+>ACP\n+GLLQTIKEKLESLESLAKGIVSGIQA\n+>ACP\n+TRSSRAGLQFPVGRVHRLLRK\n+>ACP\n+FFGWLIKGAIHAGKAIHGLIHRRRH\n+>ACP\n+GLFDVIKKVASVIGGL\n+>ACP\n+GLFDIIKKVASVVGGL\n+>ACP\n+GRFKRFRKKFKKLFKKLSPVIPLLHLG\n+>ACP\n+GGLRSLGRKILRAWKKYGPIIVPIIRIG\n+>ACP\n+RRRPRPPYLPRPRPPPFFPPRLPPRIPPGFPPRFPPRFP\n+>ACP\n+GLLGPLLKIAAKVGSNLL\n+>ACP\n+GLICESCRKIIQKLEDMVGPQPNEDTVTQAASQVCDKLKILRGLCKKIMRSFLRRISWDILTGKKPQAICVDIKICKEKTGLI\n+>ACP\n+DHYNCVSSGGQCLYSACPIFTKIQGTCYRGKAKCCK\n+>ACP\n+FFHHIFRGIVHVGKTIHRLVTG\n+>ACP\n+KLAKLAKKLAKLAK\n+>ACP\n+KTCENLADTFRGPCFATSNC\n+>ACP\n+IDWKKLLDAAKQIL\n+>ACP\n+FLIGMTQGLICLITRKC\n+>ACP\n+ILPILSLIGGLLGK\n+>ACP\n+GLLGLLGSVVSHVVPAIVGHF\n+>ACP\n+GLLGLLGSVVSHVLPAITQHL\n+>ACP\n+GIKCRFCCGCCTPGICGVCCRF\n+>ACP\n+QSHLSLCRWCCNCCRSNKGC\n+>ACP\n+ILGPVISTIGGVLGGLLKNL\n+>ACP\n+FLPILASLAAKFGPKLFCLVTKKC\n+>ACP\n+GLWSKIKEAAKAAGKAALNAVTGLVNQGDQPS\n+>ACP\n+LLGMIPLAISAISALSKL\n+>ACP\n+GLPVCGETCVGGTCNTPGCSCSWPVCTRN\n+>ACP\n+GVPICGETCTLGTCYTAGCSCSWPVCTRN\n+>ACP\n+GIPCGESCVWIPCISSAIGCSCKSKVCYRN\n+>ACP\n+GIPCAESCVWIPCTVTALIGCGCSNKVCYN\n+>ACP\n+GTFPCGESCVFIPCLTSAIGCSCKSKVCYKN\n+>ACP\n+GLLPCAESCVYIPCLTTVIGCSCKSKVCYKN\n+>ACP\n+GRDYRTCLTIVQKLKKMVDKPTQRSVSNAATRVCRTGRSRWRDVCRNFMRRYQSRVTQGLVAGETAQQICEDLRLCIPSTGPL\n+>ACP\n+GETDPNTQLLNDLGNNMAWGAALGAPGGLGSAALGAAGGALQTVGQGLIDHGPVNVFIPVLIGPSWNGSGSGYNSATSSSGSGS\n+>ACP\n+GFKDLLKGAAKALVKTVLF\n+>ACP\n+KSCCPNTTGRNIYNACRLTGAPRPTCAKLSGCKIISGSTCPSDYPK\n+>ACP\n+KSCCPNTTGRNIYNTCRFGGGSREVCARISGCKIISASTCPSDYPK\n+>ACP\n+KSCCPNTTGRNIYNTCRLTGSSRETCAKLSGCKIISASTCPSNYPK\n+>ACP\n+MRKEFHNVLSSGQLLADKRPARDYNRK\n+>ACP\n+KSCCKNTTGRNIYNTCRFAGGSRERCAKLSGCKIISASTCPSDYPK\n+>ACP\n+FIFHIIKGLFHAGKMIHGLVTRRRH\n+>ACP\n+FLPAIVGAAAKFLPKIFCAISKKC\n+>ACP\n+FLPIIAGVAAKVLPKIFCAISKKC\n+>ACP\n+FLPIIAGIAAKFLPKIFCTISKKC\n+>ACP\n+FLPVIAGVAANFLPKLFCAISKKC\n+>ACP\n+FLPIIAGAAAKVVQKIFCAISKKC\n+>ACP\n+GLMDTIKGVAKTVAASWLDKLKCKITGC\n+>ACP\n+VNWKKVLGKIIKVAK\n+>ACP\n+VNWKKILGKIIKVAK\n+>ACP\n+FFSLLPSLIGGLVSAIK\n+>ACP\n+RFRLPFRRPPIRIHPPPFYPPFRRFL\n+>ACP\n+KWKLFKKIPKFLHLAKKF\n+>ACP\n+YKQCHKKGGHCFPKEKICLPPSSDFGKMDCRWRWKCCKKGSG\n+>ACP\n+GIPCGESCVFIPCITGAIGCSCKSKVCYRN\n+>ACP\n+GEFLKCGESCVQGECYTPGCSCDWPICKKN\n+>ACP\n+GLPTCGETCTLGTCYVPDCSCSWPICMKN\n+>ACP\n+GLPVCGETCFGGTCNTPGCTCDPWPVCTRN\n+>ACP\n+FVDLKKIANIINSIFGK\n+>ACP\n+GSIPCGESCVFIPCISSVIGCACKSKVCYKN\n+>ACP\n+GIPCGESCVFIPCISSVIGCSCSSKVCYRN\n+>ACP\n+GSIPCGESCVFIPCISAVIGCSCSNKVCYKN\n+>ACP\n+GSIPCEGSCVFIPCISAIIGCSCSNKVCYKN\n+>ACP\n+GIPCGESCVFIPCLTSAIDCSCKSKVCYRN\n+>ACP\n+GMWSKILGHLIR\n+>ACP\n+GKWMSLLKHILK\n+>ACP\n+GFGMALKLLKKVL\n+>ACP\n+GTGLPMSERRKIMLMMR\n+>ACP\n+GIACGESCVFLGCFIPGCSCKSKVCYFN\n+>ACP\n+GVIPCGESCVFIPCISSVLGCSCKNKVCYRD\n+>ACP\n+KLCGETCFKFKCYTPGCSCSYPFCK\n+>ACP\n+GDACGETCFTGICFTAGCSCNPWPTCTRN\n+>ACP\n+GIPCAESCVWIPPCTITALMGCSCKNNVCYNN\n+>ACP\n+IPCGESCVWIPCITAIAGCSCKNKVCYT\n+>ACP\n+AIPCGESCVWIPCISTVIGCSCSNKVCYR\n+>ACP\n+GEYCGESCYLIPCFTPG'..b'GFGGRVDAGQPELLTER\n+>non-ACP\n+TAGILLLLLLGTLEGS\n+>non-ACP\n+MEPSILLLLALLVGFLLLLVRGH\n+>non-ACP\n+MKNCFQLLCNLKVPAAGFKNTVKS\n+>non-ACP\n+SVIHTQAHASGLQQVPQLVPAGPGGGGKAVAPSKQSK\n+>non-ACP\n+KPLGLLKPSSLMKVSGRFKAHQDA\n+>non-ACP\n+ARTLNNKLSLSKPKFSGFT\n+>non-ACP\n+LLLVIIWTLFGPSGLGEELLSLSLASLLPAPASPGPP\n+>non-ACP\n+WPGILVGGARVASCRYPALGPRLA\n+>non-ACP\n+RSVKGLVALITGGASGL\n+>non-ACP\n+AAAALRARILQVSSKVN\n+>non-ACP\n+TGCCIAGRLANLDDQNLTVAL\n+>non-ACP\n+GSILGFLQIATVLTVLLLLLK\n+>non-ACP\n+AARQIGSCLMRCRTLDTTSP\n+>non-ACP\n+WGCRGRRWAFARVDGGSCHRRGAPTGSTSNQIR\n+>non-ACP\n+YAKPGAVRSPAQILQWQVLPNTVPAKS\n+>non-ACP\n+RMAGPWLSLHEARLLGTRGAAAPKAV\n+>non-ACP\n+SISNRAAVPEHGVAPDAERL\n+>non-ACP\n+PNFSMETWLLLV\n+>non-ACP\n+PRPPSKTYRGAFQN\n+>non-ACP\n+SVLVKGCQPFLSAPRECPGHPRVGT\n+>non-ACP\n+LVTPPKALLKPLSIPNQ\n+>non-ACP\n+KMQGSRMDEQRCS\n+>non-ACP\n+VIADDLPPTCIRP\n+>non-ACP\n+LPGGLRVLVQTGH\n+>non-ACP\n+GWIWRWGWGRRCLGRPGLPGPGPGPATPLFLLLL\n+>non-ACP\n+RGIRGSSAARPSGRRRDPAGRTTETGFNIFTQHD\n+>non-ACP\n+QQEKEFLESYPQNCPPDALPGTPGNLD\n+>non-ACP\n+APARRVLQVKRVMQESSLSPAHL\n+>non-ACP\n+KVAPGGPTGYPGNLTAEQEQKLGELKMILL\n+>non-ACP\n+FLASYPQKCPAGSLPGTPGNTDE\n+>non-ACP\n+MDAKARNCLLQHREALEKDIKTSY\n+>non-ACP\n+ASRQLLVAPPEAL\n+>non-ACP\n+MISNGIGTVTTGKRSMCLFPLLLIGLWGC\n+>non-ACP\n+MTLRNFGMGKRSIEDRVQEEARCLVEELRKTNASPC\n+>non-ACP\n+AVFGLGGVGLSVIMGCKAAGASRIIAVDIN\n+>non-ACP\n+PNAKQSILQKNPDDVVIVAAYRTA\n+>non-ACP\n+AMELLLTATIFYLVLWVVKAFRLQVPKGLKSPPGP\n+>non-ACP\n+LLAAGFCPAVLCH\n+>non-ACP\n+AASVNDEQHQRIIKYGRALVLDIVEQ\n+>non-ACP\n+IARLREDGIQKRVIQEGRGELPDFQDG\n+>non-ACP\n+FIVVMNILALTLPFLAAEVQN\n+>non-ACP\n+CQNGRRANRTVRFARTA\n+>non-ACP\n+WVTVRSQQRGLFPAI\n+>non-ACP\n+LLRSCPLQGSPGRPRSV\n+>non-ACP\n+LNDGHFMPVLGFGTYAPPEVPRNRAVEV\n+>non-ACP\n+HLGRPSAPTIVAQPVSGLASPASFQPEQFQYTLDNNVLT\n+>non-ACP\n+RPEPGGCCCRRTVRANGC\n+>non-ACP\n+SWVEENRASFQPPVCNKLMHR\n+>non-ACP\n+VFHRVRWAPELGASLG\n+>non-ACP\n+RAKVLTLDGMNPRVRRVEYAVRGPIVQRALELEQELRQ\n+>non-ACP\n+LLQRARLAEQAERYDDMASAMKAVTELNEPLS\n+>non-ACP\n+ALIQKLNSDPQFVLAQNVGTTHDLLDICLKRATVQRA\n+>non-ACP\n+AALPMLWTGLVLLGLLGFPQTPAQGHDTVQPNFQQ\n+>non-ACP\n+QRRQNDSSVFLAIMVAAAVES\n+>non-ACP\n+CNAPGCGQRFTNEDHLAVHKHKHEMTLKFGPARTDS\n+>non-ACP\n+LVLLTVQNSALILTLNYSRIMPGYD\n+>non-ACP\n+TVLSPPQRFKRILQAMMLAVAVV\n+>non-ACP\n+ISRGLLLLAALCCLAPSFL\n+>non-ACP\n+VAGTESAQGPPGPAASLELWLNKATDPS\n+>non-ACP\n+QYLRIRTVQPEPDYGAAV\n+>non-ACP\n+ASPTQTPPTTSTIRVARRSRVALVAM\n+>non-ACP\n+TIWRNQHTYKMATSASANLSKIVKKNYMELPQDGKVQ\n+>non-ACP\n+LSITRGLLLLAALCCLAPIS\n+>non-ACP\n+ILLSIWRQSSGRGKLPPGPIPLPIIGNIFQ\n+>non-ACP\n+LLLLSWVALGPRSLEGADPGTPGEAEGPACP\n+>non-ACP\n+LRVKRAMQEASFMPPLLPPAAHQRFSTVPAVP\n+>non-ACP\n+GLLLLAGLCCLVFGIMAEDAQVAQGPSQQI\n+>non-ACP\n+RHVGLLCATGPQRWRF\n+>non-ACP\n+AAVALARPKPPLRHQEHLQNEPDS\n+>non-ACP\n+SRVNDQSQASRNGLKGKVLTLDTMNPCV\n+>non-ACP\n+AAALGPGVLQATRAFHTGQPRLAPLPPLPEYGGK\n+>non-ACP\n+LCTSGLWTAQASTNESSNSHRGLAPTNV\n+>non-ACP\n+PAIQPVLSGLSRIVNGEEA\n+>non-ACP\n+GCQASLSTAQERLGHPGVPTREGVR\n+>non-ACP\n+RKVLILTLVVAACGFVLWSSNGR\n+>non-ACP\n+GRVRSRCPGPALLLLLALAARPALAGPPAAALQ\n+>non-ACP\n+CRITKPALLVLNQETAKVVQT\n+>non-ACP\n+KAEVCMAVPWLSLQ\n+>non-ACP\n+SHLELNNGTKMPTLGLGT\n+>non-ACP\n+LLLPEAAAERDAREKLALWDRRPDTTAPL\n+>non-ACP\n+LLALSLVLLYRYATYSHGFFKKLGIPGPKPLPLFGNVLS\n+>non-ACP\n+LLSLWRQSSGRGKLPPGPTPLPVIGNILQIGIKD\n+>non-ACP\n+AFKSMEVANFYYEADCLAAAYGGKAAPAAPPADRPGPR\n+>non-ACP\n+SLFWAARPLQRCGQLVRMAIRAQH\n+>non-ACP\n+MRPPRTLTSTATMSALSTSMPMEIDDVMDEDAVNGQA\n+>non-ACP\n+LLSLIGFCWAQYDP\n+>non-ACP\n+LWARSKNDQLRISFPPGLCWG\n+>non-ACP\n+PQGFDVDRDAKKLNKACKGMGTNEAAIIEILSG\n+>non-ACP\n+IFCLILWVVKAWQPRLPKGLKSPPGPWGWPLLG\n+>non-ACP\n+LDAASPGPLALLGLLFAATLLLSALFLL\n+>non-ACP\n+VTLLFKLYCLA\n+>non-ACP\n+ATRAAAARLVGTAASRTPAAARH\n+>non-ACP\n+RNKLDLETLTDILEHQIR\n+>non-ACP\n+RRLVLQARTYAQAAASPAPAAGPGQMSFTFASPTQVFF\n+>non-ACP\n+PGRSRSAADDINPAPANM\n+>non-ACP\n+LLSALTLETWVLLAVILVLLYRLG\n+>non-ACP\n+VMGHGLCPQGARAKAAIPAALRDHEST\n+>non-ACP\n+FLVSIAGLLYALVQLGQPCDCLPPLRAAA\n+>non-ACP\n+VRSVRAAVGGLRAISAPSAPCLPRPWGLRAG\n+>non-ACP\n+RGGCWPRGLQQLLVPGG\n+>non-ACP\n+APATPPRPLKRKKLQFTDVTPESSP\n+>non-ACP\n+EQAERYDDMAAAMKAVTEQGHELSNEERNL\n+>non-ACP\n+MPNDPSDNQLK\n+>non-ACP\n+TELLLAITVFCLGFWVVRALRTQVP\n+>non-ACP\n+LTADLLGAPFFTLPKELQLALLERQTVFL\n+>non-ACP\n+GHGRLVEIQGRLGVRIER\n+>non-ACP\n+LPFKLLLFVLLDGWTRLTH\n+>non-ACP\n+QALWLVLVLSMPPVLVAAVVGTLVSLVQ\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Word_Vector_Model/PDAUG_Word_Vector_Model.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Word_Vector_Model/PDAUG_Word_Vector_Model.py Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,38 @@
+import nltk
+from nltk import trigrams
+import pandas as pd
+from Bio import SeqIO
+import gensim, logging
+import argparse
+
+parser = argparse.ArgumentParser()
+
+parser.add_argument("-I", "--Input", required=True, default=None, help="Path to target fasta file")
+parser.add_argument("-M", "--min_count", required=False, default=0, help="Path to target tsv file")
+parser.add_argument("-W", "--window", required=False, default=5, help="Path to target tsv file")
+parser.add_argument("-O", "--OutFile", required=False, default='model.txt', help="Path to target tsv file")
+
+args = parser.parse_args()
+
+class ProteinSeq(object):
+    def __init__(self):
+        pass
+    def __iter__(self):
+        for index, record in enumerate(SeqIO.parse(args.Input, 'fasta')):
+            for loop_num in range(0, 3):
+                Ngram_list = []
+                tri_tokens = trigrams(record.seq)
+                for index1, item in enumerate(tri_tokens):
+                    if index1 % 3 == loop_num:
+                        tri_pep = item[0] + item[1] + item[2]
+                        Ngram_list.append(tri_pep)
+                yield Ngram_list
+#min_count = 0
+size = 200
+#window = 5
+sg = 1
+
+sentences = ProteinSeq() 
+model = gensim.models.Word2Vec(sentences, min_count=int(args.min_count), size=size, window=int(args.window), sg = sg, workers = 10)
+model.wv.save_word2vec_format(args.OutFile, binary=False)
+
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Word_Vector_Model/test-data/model.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Word_Vector_Model/test-data/model.txt Wed Oct 28 02:36:27 2020 +0000
b
b'@@ -0,0 +1,567 @@\n+566 200\n+SLK -0.0010030628 0.000100835154 -0.0019347421 -0.00076493184 0.0014542947 0.0014068135 0.00084618153 0.0020921843 -0.0019026415 -0.0006590894 0.0022805685 -0.00096782576 -0.0024763828 0.0007323335 0.00061047205 -0.0022421663 -0.000654532 -0.0011798553 -0.00060771394 -0.00050038786 -0.0007698266 0.00084362755 -0.0011791416 -0.0016665208 -0.0005201962 0.0019055296 -1.512186e-05 -0.0019836018 -0.0012254894 -0.0022825655 0.0010594992 0.0018288207 -0.0006668121 0.0021907832 0.00094542024 -0.00170071 0.00183659 -0.0005609948 -0.0008470077 0.0024044297 -0.0006272259 -0.0015420591 -0.0015622115 0.0022688601 0.00055790844 0.00022420083 0.0021307333 -0.002215041 -9.6654316e-05 0.0014316123 0.0010925673 0.0023748777 0.0017993941 -0.0010667549 -0.0010471892 0.001276248 -0.0010441451 -0.0013733016 -0.0017143694 0.0008117987 -0.002100952 0.0005481462 0.0012565582 -0.00027537628 0.00060161017 0.0005101376 -0.00082007336 0.0009339486 -0.0017269732 -0.00015142813 0.00080418744 0.0013757494 -0.0009887083 8.432536e-05 0.002368311 0.00069492083 -0.0023838778 0.0010613009 4.0552673e-06 -0.0012329626 -0.0020130351 -0.0019470055 -0.0023918888 -0.0016396545 -0.0009881324 -0.0011715402 0.001962593 -0.00018947676 0.0022470367 0.0016972214 -0.001412244 0.002093491 0.0007775214 -0.0022779112 0.00067085406 -0.0020114318 0.00066405896 -0.002079473 0.0007314552 0.00023783054 0.00052206067 -0.00213498 -0.0011686112 0.00062618905 -0.0006196545 -0.00065055385 0.0016532214 -1.8988281e-05 -0.0014523834 0.0022160858 -0.00019177794 0.0021167719 -0.0020362854 -0.00040376265 0.0007045411 0.0006447945 -6.798684e-05 0.0010527554 0.0020198557 0.0006721824 4.0404648e-05 -0.0011978751 0.00034359843 -0.001697562 -0.002398286 0.0023275372 -0.000497055 0.0011098448 -0.0021362582 -0.0006785072 0.0005731353 -0.0021288977 0.0024249821 -0.0019835131 -0.0010200157 -0.001747614 -0.0021896977 0.0007778393 -0.0014301152 0.0004458818 0.0013275212 0.0012406965 -0.0007275597 0.0022300016 0.0020351794 0.0007773101 0.0010185415 0.00054066326 -0.00065416447 -0.001602047 -0.0009327506 -0.0015748533 -0.0017828726 -0.0016216517 -0.00064577936 0.00032859002 -0.0020514058 -0.0020315524 2.8936416e-05 -0.0016045409 -0.0020136943 -0.001464344 -0.0009834922 0.00060522277 0.0021689925 0.00021460328 0.00028584892 -0.001936293 0.0014174379 0.00021913492 -0.0014197932 -0.0024451527 -0.0018287416 0.0020558643 -0.0011970316 0.0025154531 -0.00033851096 0.0002898627 0.0022417586 0.0015096798 0.0020330683 -5.9363232e-05 0.0016878136 0.0015900587 0.00081262534 -0.00079336023 0.0020084986 0.0015118823 0.001884626 0.002055723 -0.0019471188 0.0005348844 -0.0013935537 -0.002366717 0.0012977426 -0.00059789 -0.0020364467 -0.00046651036 -0.000643891 -0.0013259477\n+LVC -0.0014843112 0.002325912 0.00041341965 -0.000457389 -0.0012172903 0.00088795676 -0.0017862645 0.0020845444 0.00040228703 9.997711e-05 0.0016066885 -0.0019978404 0.0006969608 0.0009175631 0.0023191834 0.0004208282 0.0008670355 0.00038776512 -0.0025192345 -9.802296e-05 0.00043508506 -0.0006363904 -0.0008578444 -0.0024026074 -0.0023426889 -0.0024238671 -0.0021346405 -0.00149934 -0.00090742245 0.0024012309 0.0017329991 -0.0018813327 0.00025454137 0.0005085536 0.0024462014 0.0014462607 -0.0010761742 0.0011953603 0.0008221692 -0.0022875224 -0.0012190182 1.1843196e-05 -0.00017557543 -0.0012803815 0.0018995996 -0.0019943821 -0.0014854127 0.002213123 -0.001961487 0.00042818586 0.0010908546 -5.6944273e-06 -1.9310939e-05 -0.0018969487 -0.0021200387 -0.0015931877 0.001627026 -0.0006712538 0.0012969036 0.0007962202 -0.00017555853 0.0022312454 0.0011899339 0.00038646816 -0.00037665278 -0.00056664605 0.0017358738 0.001199929 -0.000121993726 0.0016059761 -0.0015569519 -0.001968228 0.0005684576 -0.0025150208 -0.0016744407 -0.001195666 -0.0021972128 -0.0024457898 0.0007898712 -0.0013959116 -0.0014921167 -0.00026803298 -0.0017856187 0.00052666117 -0.0010324508 -0.002182621 0.00084328605 0.002562451 -8.9075715e-05 -0.0006066804 0.00245605'..b'924 0.0021821025 -0.0014032001 -0.0009744811 0.0010769261 -0.00034137678 0.000214921 0.0024331359 -0.0020255684 0.0020676758 0.0017541476 0.0018737108 0.0015129836 0.0010686504 0.002332911 0.0001992582 0.0011322168 0.0003263395 -0.0009947193 0.0022501221 -0.0023565881 -0.00039700672 0.0021902514 0.0018467497 -0.0018980933 0.0003773999 -0.0011028886 -0.0024948912 0.00058945455 -0.0011515784 0.0015930029 -0.0005651209 4.1423882e-05 0.0017315708 6.154556e-05 0.00067807746 -0.0007624985 0.0014497186 -0.0011262009 -0.00094811886 0.0007234749 0.0002620769 -0.0007772993 0.0017874188 -0.0015540041 -0.0023920804 0.0006855838 -0.0010742402 -0.00021710082 0.0011857314 -0.0023305858 0.0023731578 0.0012189841 -0.00069491967 -0.0010127571 0.0005580876 0.001036492 -0.0021085378 -0.0003845184 -0.0019605139 0.0022725107 0.0018582217 -0.00018812898 0.0006322817 -0.0024015135 0.002275918 -0.0012636826 -0.0023785608 0.0020010332 -0.002370117 -0.00044299682 -0.00078391156 0.0023472942 -0.0018125535 0.0020114002 -0.002014159 0.0012666982 0.0021298465 -0.0011994458 0.002128024 -0.001189568 0.0019846351 -0.0021721057 -0.0020807649 -8.474351e-05 0.0020009486 -0.0002868331 -0.0011943501 0.0020324918 -0.0020747124 0.00047011115 -0.0021956079 0.00034764616 -0.0018886229 0.0018471953 0.00047610325\n+RTT 0.000800459 0.0022807189 0.000614407 0.00043291523 0.0013266976 0.0016516823 -0.00017887352 0.0001774865 0.0022674256 0.0007991084 -0.0017937184 -0.0012809283 0.00034525068 0.0010474691 -0.0011773593 -0.00020316518 0.00071664935 0.0004490933 0.0005864967 0.0023711638 0.0012197499 -0.0009967296 0.0012682456 0.0015518359 0.000651693 0.0008096255 0.0004684565 -0.001262113 -0.0011209914 0.00018294278 -0.00013294513 0.00014597994 0.00041009023 -0.0013152343 -0.00050766 0.00033145904 0.00056744565 0.0008613704 0.0007503846 -0.001847496 -0.0016863405 0.0022872342 0.0009217861 -0.0011331631 0.0013246123 -0.002163321 0.0023381775 -0.0013936638 0.0022097866 -0.0023730479 0.0014418369 -0.0015951154 -0.0017479687 -1.1758027e-05 0.0012897338 0.0007854197 0.00087452476 -0.0019004125 0.0017956524 0.0019462679 0.0014046035 0.0014048805 -0.001382155 -0.0015547818 0.0009136546 0.0013969156 -0.002408568 -0.00095783925 -0.0012149756 0.0013561236 0.00081642164 -0.0005703783 -0.0020031298 0.00029171846 -0.0018983197 0.0008232627 -0.00067786424 0.0015696628 0.0005483555 -0.0008685772 -0.0004985128 0.0015814694 -0.0019487073 -0.00022380968 -0.0024199411 -0.0018035958 -0.001738709 -0.001768671 0.0023001665 0.0011826147 0.0013505309 -0.001520888 -0.0022249857 0.0015392177 8.096851e-05 0.00019641909 -0.00217602 -0.0008343077 0.00033551097 -0.00075170374 -0.0019082596 0.0015030898 -0.0021043406 -0.00062664493 0.0012989572 -0.0019294041 0.00089970586 -0.0021291745 0.00081388105 -0.0014019778 0.002488779 -0.00050189596 -2.1637376e-05 0.0010064129 -0.000278038 0.0019295008 0.00056200475 0.0023637 -0.0021872418 -0.0007958102 -0.0016448909 0.0002751693 0.0017254049 0.0006061145 -0.00071685784 0.0024198801 -0.0014178854 0.0017153893 0.0022203254 0.0025270556 -0.00053209305 0.0022114152 0.0022816851 -0.0013134214 0.0017226143 0.002457915 0.0014352301 -0.00053877925 0.0018859431 0.001810429 -0.0024067212 -0.0019813501 -0.002387521 -0.00020712892 0.0013106425 0.0007510423 -0.0016320832 0.0011793209 0.00049539725 0.0010422879 0.0012776309 0.0008611337 -0.0022205974 -0.00247682 0.0006492324 -0.0011322489 -0.0010332862 -0.0014822948 6.4873646e-05 0.0014633074 -0.00056768797 -0.0018850511 -0.00024886813 -0.0012680636 0.0023715075 0.0012950113 -2.916198e-06 -0.0024495733 -0.0020298546 0.0012903305 0.00018515662 0.0012265041 0.0001239143 -0.00017969421 -0.0018547528 0.0004504478 0.0021181984 -0.0017624114 -0.00014107149 0.0016415552 -0.00047895184 0.00086379354 0.002456045 -0.00063980406 0.001173198 -0.0021613056 0.0022272768 0.0012139239 0.00215961 0.0012713169 6.230853e-05 -0.00018173548 -0.0012579496 -0.0013567571 0.00051431364 -0.0023164214 0.0014994337 0.0011433125 0.00029282333 -0.0015467361\n'
b
diff -r 000000000000 -r 2df11ea23f10 PDAUG_Word_Vector_Model/test-data/test.fasta
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Word_Vector_Model/test-data/test.fasta Wed Oct 28 02:36:27 2020 +0000
[
@@ -0,0 +1,11 @@
+>AHC69389.1 COX-2 [Pagrus major]
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