First attempt on postprocess

primingsitepredictor/createtranscript.py

@@ -12,27 +12,57 @@ Created on Wed Nov 16 17:48:04 2022
 #     print(len(content[3:]))
 #     print((content[3:]))
 
+import pandas as pd
+import math
+
 class CreateTranscript():
     def __init__(self):
         with open("RIBlast output example.txt", 'r') as file:
-            self.list_of_interactions = file.readlines()[3:]
+            self.raw_interactions = file.readlines()[3:]
 
     
     
-    def generate_interaction_list(self):
-        interaction_list = []
-        for i in range(0, (len(self.list_of_interactions)-1)):
-            current_interaction = self.list_of_interactions[i].strip(' \n').split(',')
-            #print(self.list_of_interactions[i].strip(' \n').split(','))
-            interaction_list.append(current_interaction)
-        return interaction_list
-
-            
-
-transcriptlist = CreateTranscript()            
-print(transcriptlist.generate_interaction_list())
-
-#go from interaction list to transcript list? -no we will serve them a interaction list.
-            
-  #          print(content[3:][0].strip(' \n').split(',')[-1].strip('()').split(':'))
+    def generate_interaction_df(self):
+        
+        self.interaction_list = []
+        
+        #clean up the original list so that we have a neet list
+        for i in range(0, (len(self.raw_interactions)-1)):
+            current_interaction = self.raw_interactions[i].strip(' \n').replace('(', '').replace(')','').replace('-',',').replace(':',',').split(',')
+            self.interaction_list.append(current_interaction) 
+        
+        #identify if the interaction is the same as the previous one, just shifted by 1 bp (if we have 20 A in the transcript the 15 T primer has 5 matching possibilities although it is only 1 bindingsite)
+        previous_interaction_base = int
+        for i in range(0, len(self.interaction_list)):
+            previous_interaction_base = int(self.interaction_list[i-1][13])
+            if int(self.interaction_list[i][13]) in range(previous_interaction_base-1,previous_interaction_base-15,-1):
+                self.interaction_list[i].append('Repeat')
+            else :
+                self.interaction_list[i].append('Not_repeat')
+
+        #exclude all interactions which are a repeat and belong to the same bindingsite
+        self.cleaned_interaction_list = [item for item in self.interaction_list if item[-1]=='Not_repeat']
+        
+        
+        #add total number of interactions per transcript and calculate energy
+        self.df = pd.DataFrame(self.cleaned_interaction_list)
+        self.df['Number of interactions'] = int
+        self.df['Interaction Energy'] = float
+        
+        energy_constant = 1.380649*10**(-23)*298
+        kcalmol_joul = 6.9477*10**-21
+        
+        
+        for ind in self.df.index:
+            self.df['Number of interactions'][ind]=self.df[3].value_counts()[self.df[3][ind]]
+            self.df['Interaction Energy'][ind]=math.exp(-float(self.df[5][ind])*kcalmol_joul/energy_constant)
+        print(self.df['Interaction Energy'])
+        print(self.df)
+        
+
+        return self.df
+
+transcripts = CreateTranscript()    
+interaction_df = transcripts.generate_interaction_df()        
+