diff --git a/primingsitepredictor/Primer1.fasta b/primingsitepredictor/Primer1.fasta
index 61ea48b62158516ac0c24d630eb7796c7a745485..545f1100114ec5eb992d22bc71d364b8663a7638 100644
--- a/primingsitepredictor/Primer1.fasta
+++ b/primingsitepredictor/Primer1.fasta
@@ -1,2 +1,2 @@
<primer1
-TTTTTTTTTTTTTTTT
+TTTTTTTTTTTTTTT
diff --git a/primingsitepredictor/cli.py b/primingsitepredictor/cli.py
index 518fea18a365aae2b8aa4eac5d264966adba984e..5b665962b5b9b5aa698793c7fe4e3d4cba2db16f 100644
--- a/primingsitepredictor/cli.py
+++ b/primingsitepredictor/cli.py
@@ -6,6 +6,7 @@ Created on Mon Nov 14 14:49:50 2022
"""
import argparse
import logging
+import main
def create_parser():
"""This function creates the parser"""
@@ -30,5 +31,5 @@ if __name__ == '__main__':
level=logging.INFO,
)
LOG = logging.getLogger(__name__)
- letsgo()
+ main()
#here we would point to the main module and parse the energy cutoff
diff --git a/primingsitepredictor/createtranscript.py b/primingsitepredictor/createtranscript.py
deleted file mode 100644
index dddeb1fc4374b5e17da87e30c395b91340da2d87..0000000000000000000000000000000000000000
--- a/primingsitepredictor/createtranscript.py
+++ /dev/null
@@ -1,80 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Wed Nov 16 17:48:04 2022
-
-@author: baerma
-"""
-
-# with open("RIBlast output example.txt", 'r') as file:
-# content = file.readlines()
-# print(content[3:][0].strip(' \n').split(',')[-1].strip('()').split(':'))
-# #create a instant of each transcript class
-# 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.raw_interactions = file.readlines()[3:]
-
-
-
- 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()
-
-#print line by line to file and then you're done
-
-output = str()
-for i in interaction_df.index:
- #print(interaction_df[3][i]+'\t' + 'RIBlast' + '\t' + 'Priming_site' + '\t' + interaction_df[13][i] + '\t' + interaction_df[12][i] + '\t' + '.' + '\t' + '+' + '\t' + '.' + '\t' + f'Accessibility_Energy "{interaction_df["Interaction Energy"][i]}"')
- output = output + str(interaction_df[3][i]+'\t' + 'RIBlast' + '\t' + 'Priming_site' + '\t' + interaction_df[13][i] + '\t' + interaction_df[12][i] + '\t' + '.' + '\t' + '+' + '\t' + '.' + '\t' + f'Accessibility_Energy "{interaction_df["Interaction Energy"][i]}"' + '\n')
-
-print(output)
-with open('output_transcripts_df.txt', 'w') as f:
- f.write(output)
-
diff --git a/primingsitepredictor/main.py b/primingsitepredictor/main.py
index e1488c300ab894afa325de33644271716cdb1b61..07348dd4b21c73c4a8be7d07a2f351e1cab7fd5f 100644
--- a/primingsitepredictor/main.py
+++ b/primingsitepredictor/main.py
@@ -1,17 +1,28 @@
import sys
-#from .classmodule import MyClass
-#from .funcmodule import my_function
+from createprimer import CreatePrimer
+from postprocessing import PostProcessRIBlast
def main():
- print('in main')
- args = sys.argv[1:]
- print('count of args :: {}'.format(len(args)))
- for arg in args:
- print('passed argument :: {}'.format(arg))
+ generate_RIBlast_input()
+ create_gtf()
+
- #my_function('Hello World')
- #my_object = MyClass('Robin')
- #my_object.say_name()
+def generate_RIBlast_input():
+ """This function creates a list of the filenames for the RIBlast"""
+ my_primer = CreatePrimer()
+ my_primer.create_fasta()
+ primer_filename = my_primer.name +".fasta"
+ transcripts_filename = "transcripts.fasta"
+
+ return [primer_filename, transcripts_filename]
+
+def create_gtf():
+ gtf_file = PostProcessRIBlast().output
+ print(gtf_file)
+
+
+
+main()
if __name__ == '__main__':
main()
diff --git a/primingsitepredictor/postprocessing.py b/primingsitepredictor/postprocessing.py
new file mode 100644
index 0000000000000000000000000000000000000000..11687931ff27ddaf64682fd8655ff054ab2a6c7e
--- /dev/null
+++ b/primingsitepredictor/postprocessing.py
@@ -0,0 +1,66 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Dec 20 14:06:20 2022
+
+@author: baerma
+"""
+
+import pandas as pd
+import math
+pd.options.mode.chained_assignment = None
+
+class PostProcessRIBlast():
+
+ def __init__(self):
+ output = self.generate_gtf()
+ #print(output)
+
+
+ def calculate_energy(self, value):
+ energy_constant = 1.380649*10**(-23)*298
+ kcalmol_joul = 6.9477*10**-21
+ return (math.exp(-float(value)*kcalmol_joul/energy_constant))
+
+
+ def create_list_from_output(self):
+ self.file = "RIBlast output example.txt"
+ self.firstline = 3
+ self.interaction_list = []
+ with open(self.file, 'r') as file:
+ self.raw_interactions = file.readlines()[self.firstline:]
+ self.number_entries = len(self.raw_interactions)
+
+ for i in range(0, self.number_entries-1):
+ current_interaction = self.raw_interactions[i].strip(' \n').replace('(', '').replace(')','').replace('-',',').replace(':',',').split(',')
+ self.interaction_list.append(current_interaction)
+
+ return self.interaction_list
+
+
+ def create_pandas_df(self):
+ self.interaction_list = self.create_list_from_output()
+ self.df = pd.DataFrame(self.interaction_list)
+ self.df['Number_of_interactions'] = int(0)
+ self.df['Interaction_Energy'] = float(0)
+ self.transcript = 3
+ self.energy = 5
+
+ for index in self.df.index:
+ self.df['Number_of_interactions'][index]=self.df[self.transcript].value_counts()[self.df[self.transcript][index]]
+ self.df['Interaction_Energy'][index]=self.calculate_energy(self.df[self.energy][index])
+
+ self.df['Normalised_interaction_energy']=self.df['Interaction_Energy']/self.df['Number_of_interactions']
+
+ return self.df
+
+
+ def generate_gtf(self):
+ self.interaction_df = self.create_pandas_df()
+ self.output = str()
+
+ for index in self.interaction_df.index:
+ self.output = self.output + str(self.interaction_df[3][index]+'\t' + 'RIBlast' + '\t' + 'Priming_site' + '\t' + self.interaction_df[13][index] + '\t' + self.interaction_df[12][index] + '\t' + '.' + '\t' + '+' + '\t' + '.' + '\t' + f'Interaction_Energy "{self.interaction_df["Normalised_interaction_energy"][index]}"' + '\n')
+
+ return(self.output)
+
+#print(PostProcessRIBlast().output)
\ No newline at end of file
diff --git a/primingsitepredictor/postprocessingmodule.py b/primingsitepredictor/postprocessingmodule.py
deleted file mode 100644
index 84888e5129504d2fbb9dc4d2ebf007164da16458..0000000000000000000000000000000000000000
--- a/primingsitepredictor/postprocessingmodule.py
+++ /dev/null
@@ -1,16 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Wed Nov 16 16:47:20 2022
-
-@author: baerma
-"""
-from createtranscript import CreateTranscript
-
-
-transcripts = CreateTranscript()
-interaction_df = transcripts.generate_interaction_df()
-
-
-
-#os.chdir('C:/Users/baerma/Desktop/PhD-Local/Lectures/Programming for Life Sciences/priming-site-predictor/primingsitepredictor')
-
diff --git a/primingsitepredictor/preprocessingmodule.py b/primingsitepredictor/preprocessingmodule.py
deleted file mode 100644
index 16b6da0f998d2b32183056b4959f6ce3657bcdf3..0000000000000000000000000000000000000000
--- a/primingsitepredictor/preprocessingmodule.py
+++ /dev/null
@@ -1,21 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Wed Nov 16 14:17:06 2022
-
-@author: baerma
-"""
-from createprimer import CreatePrimer
-
-def generate_RIBlast_input():
- """This function creates a list of the filenames for the RIBlast"""
- my_primer = CreatePrimer()
- my_primer.create_fasta()
- primer_filename = my_primer.name +".fasta"
- transcripts_filename = "transcripts.fasta"
-
- return [primer_filename, transcripts_filename]
-
-print(generate_RIBlast_input())
-
-
-