--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Peptide_Sequence_Analysis/PDAUG_Peptide_Sequence_Analysis.py	Wed Oct 28 01:47:48 2020 +0000
@@ -0,0 +1,231 @@
+import  modlamp
+from modlamp.analysis import *
+
+from plotly.subplots import make_subplots
+import plotly.graph_objects as go
+from modlamp.analysis import GlobalAnalysis
+from modlamp.analysis import *
+
+import pandas as pd
+import os, sys
+import argparse
+
+parser = argparse.ArgumentParser(description='Deployment tool')
+subparsers = parser.add_subparsers()
+
+CalcAAFreq = subparsers.add_parser('CalcAAFreq')
+CalcAAFreq.add_argument("-I","--InFile", required=True, default=None, help="")
+CalcAAFreq.add_argument("-T","--PlotFile", required=False, default='out.pdf', help="out.pdf")
+CalcAAFreq.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv")
+
+H = subparsers.add_parser('H')
+H.add_argument("-I","--InFile", required=True, default=None, help="")
+H.add_argument("-S","--Scale", required=False, default='eisenberg', help="hydrophobicity scale to use. For available scales, see modlamp.descriptors.PeptideDescriptor.")
+H.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv")
+
+uH = subparsers.add_parser('uH')
+uH.add_argument("-I","--InFile", required=True, default=None, help="")
+uH.add_argument("-S","--Scale", required=False, default='eisenberg', help="hydrophobicity scale to use. For available scales, see modlamp.descriptors.PeptideDescriptor.")
+uH.add_argument("-W", "--Window", required=False, default=1000, help="")
+uH.add_argument("-A", "--Angle", required=False, default=100, help="")
+uH.add_argument("-M", "--Modality", required=False, default='max', help="")
+uH.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv")
+
+charge = subparsers.add_parser('charge')
+charge.add_argument("-I","--InFile", required=True, default=None, help="")
+charge.add_argument("-p", "--ph", required=False, default=7.0, help="")
+charge.add_argument("-A", "--Amide", required=False, default=True, help="")
+charge.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv")
+
+Len = subparsers.add_parser('Len')
+Len.add_argument("-I","--InFile", required=True, default=None, help="")
+Len.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv")
+
+PlotSaummary = subparsers.add_parser('PlotSummary')
+PlotSaummary.add_argument("-I1","--InFile1", required=True, default=None, help="")
+PlotSaummary.add_argument("-I2", "--InFile2", required=True, default=None, help="Out.tsv")
+PlotSaummary.add_argument("--PlotFile", required=False, default='Out.pdf', help="out.pdf")
+PlotSaummary.add_argument("--htmlFname", required="False", default='report.html', help="Output file")
+PlotSaummary.add_argument("-O","--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'),  help="HTML Out Dir")
+PlotSaummary.add_argument("-Wp","--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
+PlotSaummary.add_argument("-fn", "--First_lib_name", required=True, help="Name of the fist peptide data")
+PlotSaummary.add_argument("-sn", "--Second_lib_name", required=True, help="Name of the second peptide data")
+
+
+args = parser.parse_args()
+
+
+
+def SummaryPlot(Lib_1, Lib_2, First_lib_name, Second_lib_Name, Workdirpath, htmlOutDir, htmlFname):
+
+    if not os.path.exists(htmlOutDir):
+        os.makedirs(htmlOutDir)
+
+
+    AA = ['A','C','D','E','F','G','H','I','K','L','M','N','P','Q','R','S','T','V','W','Y']
+
+    Pep1, Index1 = ReturnPeptide(Lib_1)
+    Pep2, Index2 = ReturnPeptide(Lib_2)
+
+    fig = make_subplots(
+        rows=2, cols=3,
+        specs=[[{"type": "xy"}, {"type": "histogram"},   {"type": "box"}  ],[{"type": "violin"}, {"type": "violin"}, {"type": "scatter3d"} ]],
+    subplot_titles=(" Amino Acid Fraction", "Global Charge", "Length Distribution", "Global Hydrophobicity", "Global Hydrophobic Movement", "Scatter Plot"))
+
+
+    #########################################
+    g = GlobalAnalysis([Pep1, Pep2])
+    df = g.calc_aa_freq(plot=False)
+
+    data1 = g.aafreq[0]
+    data2 = g.aafreq[1] 
+
+    fig.add_trace(go.Bar(x=AA, y=data1, name=First_lib_name, marker_color='#1F77B4'),  row=1, col=1)
+    fig.add_trace(go.Bar( x=AA, y=data2,name=Second_lib_Name, marker_color='#FF7F0E'), row=1, col=1)
+    fig.update_layout(showlegend=True)
+    ##########################################
+
+
+    #########################################
+    d1  = GlobalDescriptor(Pep1)
+    d1.calculate_charge(ph=7.4, amide=True)
+    charge1 = [x[0] for x in d1.descriptor]
+
+    d2  = GlobalDescriptor(Pep2)
+    d2.calculate_charge(ph=7.4, amide=True)
+    charge2 = [x[0] for x in d2.descriptor]
+
+    fig.add_trace(go.Histogram(x=charge1, histnorm='probability', marker_color='#1F77B4', name=First_lib_name,  xbins=dict(  start=min(charge1), end=max(charge1), ), opacity=0.75), row=1, col=2)
+    fig.add_trace(go.Histogram( x=charge2, histnorm='probability', marker_color='#FF7F0E', name=Second_lib_Name, xbins=dict( start=min(charge2), end=max(charge2), ),  opacity=0.75), row=1, col=2 )
+    #fig.update_layout( ,  xaxis_title_text='Charge',  yaxis_title_text='Fraction',  bargap=0.1, bargroupgap=0.1 )
+    ###########################################
+
+    ##############################################################################
+    Length1 = [len(x) for x in Pep1]
+    Length2 = [len(x) for x in Pep2]
+
+    fig.add_trace(go.Box(y=Length1, name=First_lib_name, marker_color='#1F77B4'), row=1, col=3)
+    fig.add_trace(go.Box(y=Length2, name=Second_lib_Name, marker_color='#FF7F0E'), row=1, col=3)
+    #############################################################################
+
+    ########################################################################
+    g = GlobalAnalysis([Pep1, Pep2])
+
+    g.calc_H()
+
+    h1 = g.H[0]
+    h2 = g.H[1]
+
+    fig.add_trace(go.Violin( y=h1,box_visible=True, name =First_lib_name, marker_color='#1F77B4', meanline_visible=True), row=2, col=1)
+    fig.add_trace(go.Violin(y=h2,box_visible=True, name=Second_lib_Name, marker_color='#FF7F0E', meanline_visible=True), row=2, col=1)
+    #################################################################
+
+    #####################################
+    uH = GlobalAnalysis([Pep1, Pep2])
+    uH.calc_uH()
+
+    uh1 = uH.uH[0]
+    uh2 = uH.uH[1]
+
+    fig.add_trace(go.Violin( y=uh1,box_visible=True, name =First_lib_name, marker_color='#1F77B4', meanline_visible=True), row=2, col=2)
+    fig.add_trace(go.Violin(y=uh2,box_visible=True, name=Second_lib_Name, marker_color='#FF7F0E', meanline_visible=True), row=2, col=2)
+    #######################################
+
+
+    ############################################
+    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)
+    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)
+    fig.update_layout(scene = dict(xaxis_title='Hydrophobicity', yaxis_title='Hydrophobic Movement', zaxis_title='Charge'),uniformtext_minsize=4, font=dict(
+            family="Times New Roman",
+            size=12,
+            color="black"))
+    ###########################################
+
+    fig.update_xaxes(title_text="Amino Acid", row=1, col=1)
+    fig.update_xaxes(title_text="Global Charge", row=1, col=2)
+    fig.update_xaxes(title_text="Peptide dataset", showgrid=False, row=1, col=3)
+    fig.update_xaxes(title_text="Peptide dataset",  row=2, col=1)
+    fig.update_xaxes(title_text="Peptide dataset",  row=2, col=2)
+
+    fig.update_yaxes(title_text="Fraction", row=1, col=1)
+    fig.update_yaxes(title_text="Fraction",  row=1, col=2)
+    fig.update_yaxes(title_text="Length",  row=1, col=3)
+    fig.update_yaxes(title_text="Global hydrophobicity", row=2, col=1)
+    fig.update_yaxes(title_text="Global hydrophobic Movement", row=2, col=2)
+    fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname))
+    #fig.show()
+
+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
+
+if sys.argv[1] == 'CalcAAFreq':
+
+    Pep, Index = ReturnPeptide(args.InFile)
+    g = GlobalAnalysis(Pep)
+    g.calc_aa_freq(plot=False, color='#83AF9B')
+    df1 =  pd.DataFrame(g.aafreq[0], columns=['aa_freq'])
+    df1.to_csv(args.OutFile,  sep='\t', index=None)
+
+elif sys.argv[1] == 'H':
+
+    Pep, _ = ReturnPeptide(args.InFile)
+    g = GlobalAnalysis(Pep)
+    g.calc_H(args.Scale)
+    df1 = pd.DataFrame(g.H[0].T, columns=['H'])
+    df1.to_csv(args.OutFile,  sep='\t', index=None)
+
+elif sys.argv[1] == 'uH':
+
+    Pep, _ = ReturnPeptide(args.InFile)
+
+    g = GlobalAnalysis(Pep)
+    g.calc_uH(int(args.Window), int(args.Angle), args.Modality)
+    df1 = pd.DataFrame(g.uH[0].T, columns=['uH'])
+    df1.to_csv(args.OutFile,  sep='\t', index=None)
+  
+elif sys.argv[1] == 'charge':
+
+    Pep, _ = ReturnPeptide(args.InFile)
+
+    g = GlobalAnalysis(Pep)
+
+    if args.Amide == 'true':
+        amide = True
+    else:
+      amide = False
+
+    g.calc_charge(float(args.ph), amide)
+    df1 = pd.DataFrame(g.charge[0].T, columns=['charge'])
+    df1.to_csv(args.OutFile,  sep='\t', index=None)
+
+elif sys.argv[1] == 'Len':
+
+    Pep, _ = ReturnPeptide(args.InFile)
+    df1 = pd.DataFrame([len(x) for x in Pep], columns=['c'])
+    df1.to_csv( args.OutFile,  sep='\t', index=None)
+
+elif sys.argv[1] == "PlotSummary":
+
+    SummaryPlot(args.InFile1, args.InFile2, args.First_lib_name, args.Second_lib_name, args.Workdirpath, args.htmlOutDir, args.htmlFname)
+
+
+
+
+
+