new algo to determine the consensus

Snakefile

@@ -91,17 +91,19 @@ else:
 
 
 
-ATTRIBUTES_DATA = ["nbIdentity","rIdentity","nbError","rError","nbMatch","rMatch","time","memory"]
+ATTRIBUTES_DATA = ["number_Ambiguity","percentage_Ambiguity","number_Identity","percentage_Identity","number_Error","percentage_Error","number_Match","percentage_Match","size","time","elapsed","memory"]
 
 onstart:
     print("Workflow Start")
 
 onsuccess:
     os.system('grep -r "ERROR" ' + EXP + '/'+EXP_NAME + '/*/logs ' + EXP + '/'+EXP_NAME + '/logs  >' +EXP + '/'+ EXP_NAME + '/final_log')
+    os.system('if [ `ls|grep ".dnd"|wc -l` -ne 0 ]; then rm *.dnd;fi')
     print("Workflow finished, no error")
 
 onerror:
     os.system('grep -r "ERROR" ' + EXP + '/'+EXP_NAME + '/*/logs ' + EXP + '/'+EXP_NAME + '/logs  >' + EXP + '/'+EXP_NAME + '/final_log')
+    os.system('if [ `ls|grep ".dnd"|wc -l` -ne 0 ]; then rm *.dnd;fi')
     print("An error has occurred. Please look in log files: " + EXP + '/'+EXP_NAME + "/final_log")
 
 #-------------------------------------------------------------------------------

src/data_formatting.py

@@ -109,21 +109,21 @@ for line in file_read.readlines():
 			msa = tab_line[0]
 			read_size = tab_line[1]
 			nb_read = tab_line[2]
-			user = float(tab_line[3])
-			system = float(tab_line[4])
+			#user = float(tab_line[3])
+			#system = float(tab_line[4])
 			time = float(tab_line[5])
 			elapsed = float(tab_line[6])
-			cpu = float(tab_line[7])
+			#cpu = float(tab_line[7])
 			memory = float(tab_line[8])
 
 			if msa in data:
 				if read_size in data[msa]:
 					if nb_read in data[msa][read_size]:
-						data[msa][read_size][nb_read] += [user,system,time,elapsed,cpu,memory]
+						data[msa][read_size][nb_read] += [time,elapsed,memory]
 
 #output
 sep=","
-print("MSA","region_size","depth","nbAmbiguity","rAmbiguity","nbIdentity","rIdentity","nbError","rError","nbMatch","rMatch","size","user","system","time","elapsed","cpu","memory",sep=sep)
+print("MSA","region_size","depth","number_Ambiguity","percentage_Ambiguity","number_Identity","percentage_Identity","number_Error","percentage_Error","number_Match","percentage_Match","size","time","elapsed","memory",sep=sep)
 for MSA in data:
 	for read_size in data[MSA]:
 		for nb_read in data[MSA][read_size]:

src/tool_consensus.py

@@ -39,32 +39,59 @@ def consensus_iupac(alignment,threshold):
 		frequency_letters={}
 
 		#Calculates the frequency of each letter
+		order_frequencys=[]
+		order_letters=[]
 		for letter in letters:
 			pass
-			frequency_letter=len(re.findall(letter,nucleotides))/nb_reads
+			frequency_letter=100*len(re.findall(letter,nucleotides))/nb_reads
 			frequency_letters[letter] = frequency_letter
-		#Gap closure
-		if ("-" not in frequency_letters):
-			frequency_letters["-"] = 0
-		if (frequency_letters["-"] < 0.50):
-			frequency_sum = 1 - frequency_letters["-"]
-			del frequency_letters["-"]
-			letters_threshold =[]
-			for letter in frequency_letters:
-				if ( (frequency_letters[letter]/frequency_sum) > threshold):
-					letters_threshold = letters_threshold + [letter]
-
-			if (len(letters_threshold) >= 1 ):
-				if (len(letters_threshold) == 1 ):
-					seq+=letters_threshold[0]
-
+			if order_frequencys == []:
+				order_frequencys.append(frequency_letter)
+				order_letters.append(letter)
 			else:
-					if (len(letters_threshold) > 1):
-						letters_threshold.sort()
-						id_iupac = "".join(letters_threshold)
+				len_order_frequencys=len(order_frequencys)
+				i=0
+				find=0
+				while (i<len_order_frequencys and find==0):
+					if(frequency_letter>order_frequencys[i]):
+						order_frequencys.append(order_frequencys[len_order_frequencys-1])
+						order_letters.append(order_letters[len_order_frequencys-1])
+						len_order_frequencys+=1
+						j=len_order_frequencys-2
+						while (j>i):
+							order_frequencys[j]=order_frequencys[j-1]
+							order_letters[j]=order_letters[j-1]
+							j-=1
+						order_frequencys[i]=frequency_letter
+						order_letters[i]=letter
+						find=1
+					i+=1
+				if i>=len_order_frequencys:
+					order_frequencys.append(frequency_letter)
+					order_letters.append(letter)
+		len_order_frequencys=len(order_frequencys)
+		#Gap closure
+		if ("-" != order_letters[0]):
+			conserved_nucs=[order_letters[0]]
+			total_frequency=order_frequencys[0];
+			i=1
+			while(total_frequency < threshold*100 and i<len_order_frequencys):
+				if(order_letters[i]!="-" and order_frequencys[i]!= 0):
+					total_frequency+=order_frequencys[i]
+					conserved_nucs=conserved_nucs + [order_letters[i]]
+					j=i
+					while (j+1<len_order_frequencys and order_frequencys[i]==order_frequencys[j+1]):
+						total_frequency+=order_frequencys[j+1]
+						conserved_nucs=conserved_nucs + [order_letters[j+1]]
+						j+=1
+					i=j
+				i+=1
+			conserved_nucs.sort()
+			if (len(conserved_nucs) > 1):
+				id_iupac = "".join(conserved_nucs)
 				seq+=nuc_to_iupac[id_iupac]
 			else:
-				seq += "N"
+				seq += conserved_nucs[0]
 	return seq
 
 #Creation of the consensus sequence