diff PDAUG_Sequence_Property_Based_Descriptors/PDAUG_Sequence_Property_Based_Descriptors.py @ 0:7557b48b2872 draft

"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"

--- /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 02:10:12 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