Mercurial > repos > davidvanzessen > shm_csr

comparison gene_identification.py @ 92:cf8ad181628f draft

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planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
author rhpvorderman
date Mon, 12 Dec 2022 12:32:44 +0000
parents 729738462297
children
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91:f387cc1580c6 92:cf8ad181628f
1 #!/usr/bin/env python3
2
3 import argparse
1 import re 4 import re
2 import argparse 5 from typing import Dict, Iterator, List, Tuple
3 import time 6
4 starttime= int(time.time() * 1000) 7
5 8 def generate_sequence_and_id_from_summary(summary_file: str
6 parser = argparse.ArgumentParser() 9 ) -> Iterator[Tuple[str, str]]:
7 parser.add_argument("--input", help="The 1_Summary file from an IMGT zip file") 10 with open(summary_file, "rt") as summary:
8 parser.add_argument("--output", help="The annotated output file to be merged back with the summary file") 11 header = next(summary)
9 12 column_names = header.strip("\n").split("\t")
10 args = parser.parse_args() 13 id_column = column_names.index("Sequence ID")
11 14 sequence_column = column_names.index("Sequence")
12 infile = args.input 15 for line in summary:
13 #infile = "test_VH-Ca_Cg_25nt/1_Summary_test_VH-Ca_Cg_25nt_241013.txt" 16 values = line.strip("\n").split("\t")
14 output = args.output 17 id = values[id_column]
15 #outfile = "identified.txt" 18 try:
16 19 sequence = values[sequence_column]
17 dic = dict() 20 except IndexError: # weird rows without a sequence
18 total = 0 21 sequence = ""
19 22 yield id, sequence
20 23
21 first = True 24
22 IDIndex = 0 25 # old cm sequence: gggagtgcatccgccccaacccttttccccctcgtctcctgtgagaattccc
23 seqIndex = 0 26 # old cg sequence: ctccaccaagggcccatcggtcttccccctggcaccctcctccaagagcacctctg
24 27 # ggggcacagcggccctgggctgcctggtcaaggactacttccccgaaccggtgacggtgtcgtggaactcagg
25 with open(infile, 'r') as f: #read all sequences into a dictionary as key = ID, value = sequence 28 # cgccctgaccag
26 for line in f: 29 SEARCHSTRINGS = {"ca": "catccccgaccagccccaaggtcttcccgctgagcctctgcagcacccagccag"
27 total += 1 30 "atgggaacgtggtcatcgcctgcctgg",
28 linesplt = line.split("\t") 31 "cg": "ctccaccaagggcccatcggtcttccccctggcaccctcctccaagagcacctc"
29 if first: 32 "tgggggcacagcggcc",
30 print("linesplt", linesplt) 33 "ce": "gcctccacacagagcccatccgtcttccccttgacccgctgctgcaaaaacatt"
31 IDIndex = linesplt.index("Sequence ID") 34 "ccctcc",
32 seqIndex = linesplt.index("Sequence")
33 first = False
34 continue
35
36 ID = linesplt[IDIndex]
37 if len(linesplt) < 28: #weird rows without a sequence
38 dic[ID] = ""
39 else:
40 dic[ID] = linesplt[seqIndex]
41
42 print("Number of input sequences:", len(dic))
43
44 #old cm sequence: gggagtgcatccgccccaacccttttccccctcgtctcctgtgagaattccc
45 #old cg sequence: ctccaccaagggcccatcggtcttccccctggcaccctcctccaagagcacctctgggggcacagcggccctgggctgcctggtcaaggactacttccccgaaccggtgacggtgtcgtggaactcaggcgccctgaccag
46
47 #lambda/kappa reference sequence
48 searchstrings = {"ca": "catccccgaccagccccaaggtcttcccgctgagcctctgcagcacccagccagatgggaacgtggtcatcgcctgcctgg",
49 "cg": "ctccaccaagggcccatcggtcttccccctggcaccctcctccaagagcacctctgggggcacagcggcc",
50 "ce": "gcctccacacagagcccatccgtcttccccttgacccgctgctgcaaaaacattccctcc",
51 "cm": "gggagtgcatccgccccaacc"} #new (shorter) cm sequence 35 "cm": "gggagtgcatccgccccaacc"} #new (shorter) cm sequence
52 36
53 compiledregex = {"ca": [], 37 #lambda/kappa referesearchstringsnce sequence variable nucleotides
54 "cg": [], 38 CA1_MUTATIONS = {38: 't', 39: 'g', 48: 'a', 49: 'g', 51: 'c', 68: 'a', 73: 'c'}
55 "ce": [], 39 CA2_MUTATIONS = {38: 'g', 39: 'a', 48: 'c', 49: 'c', 51: 'a', 68: 'g', 73: 'a'}
56 "cm": []} 40 CG1_MUTATIONS = {0: 'c', 33: 'a', 38: 'c', 44: 'a', 54: 't', 56: 'g', 58: 'g', 66: 'g', 132: 'c'}
57 41 CG2_MUTATIONS = {0: 'c', 33: 'g', 38: 'g', 44: 'g', 54: 'c', 56: 'a', 58: 'a', 66: 'g', 132: 't'}
58 #lambda/kappa reference sequence variable nucleotides 42 CG3_MUTATIONS = {0: 't', 33: 'g', 38: 'g', 44: 'g', 54: 't', 56: 'g', 58: 'g', 66: 'g', 132: 'c'}
59 ca1 = {38: 't', 39: 'g', 48: 'a', 49: 'g', 51: 'c', 68: 'a', 73: 'c'} 43 CG4_MUTATIONS = {0: 't', 33: 'g', 38: 'g', 44: 'g', 54: 'c', 56: 'a', 58: 'a', 66: 'c', 132: 'c'}
60 ca2 = {38: 'g', 39: 'a', 48: 'c', 49: 'c', 51: 'a', 68: 'g', 73: 'a'}
61 cg1 = {0: 'c', 33: 'a', 38: 'c', 44: 'a', 54: 't', 56: 'g', 58: 'g', 66: 'g', 132: 'c'}
62 cg2 = {0: 'c', 33: 'g', 38: 'g', 44: 'g', 54: 'c', 56: 'a', 58: 'a', 66: 'g', 132: 't'}
63 cg3 = {0: 't', 33: 'g', 38: 'g', 44: 'g', 54: 't', 56: 'g', 58: 'g', 66: 'g', 132: 'c'}
64 cg4 = {0: 't', 33: 'g', 38: 'g', 44: 'g', 54: 'c', 56: 'a', 58: 'a', 66: 'c', 132: 'c'}
65 44
66 #remove last snp for shorter cg sequence --- note, also change varsInCG 45 #remove last snp for shorter cg sequence --- note, also change varsInCG
67 del cg1[132] 46 del CG1_MUTATIONS[132]
68 del cg2[132] 47 del CG2_MUTATIONS[132]
69 del cg3[132] 48 del CG3_MUTATIONS[132]
70 del cg4[132] 49 del CG4_MUTATIONS[132]
71 50
72 #reference sequences are cut into smaller parts of 'chunklength' length, and with 'chunklength' / 2 overlap 51 # reference sequences are cut into smaller parts of 'chunklength' length,
73 chunklength = 8 52 # and with 'chunklength' / 2 overlap
74 53 CHUNK_LENGTH = 8
75 #create the chunks of the reference sequence with regular expressions for the variable nucleotides 54
76 for i in range(0, len(searchstrings["ca"]) - chunklength, chunklength // 2): 55
77 pos = i 56 def create_compiled_regexes() -> Dict[str, List[Tuple[re.Pattern, int]]]:
78 chunk = searchstrings["ca"][i:i+chunklength] 57
79 result = "" 58 compiledregex: Dict[str, List[Tuple[re.Pattern, int]]] = {
80 varsInResult = 0 59 "ca": [],
81 for c in chunk: 60 "cg": [],
82 if pos in list(ca1.keys()): 61 "ce": [],
83 varsInResult += 1 62 "cm": []
84 result += "[" + ca1[pos] + ca2[pos] + "]" 63 }
85 else: 64
86 result += c 65 for i in range(0, len(SEARCHSTRINGS["ca"]) - CHUNK_LENGTH, CHUNK_LENGTH // 2):
87 pos += 1 66 pos = i
88 compiledregex["ca"].append((re.compile(result), varsInResult)) 67 chunk = SEARCHSTRINGS["ca"][i:i + CHUNK_LENGTH]
89 68 result = ""
90 for i in range(0, len(searchstrings["cg"]) - chunklength, chunklength // 2): 69 varsInResult = 0
91 pos = i 70 for c in chunk:
92 chunk = searchstrings["cg"][i:i+chunklength] 71 if pos in list(CA1_MUTATIONS.keys()):
93 result = "" 72 varsInResult += 1
94 varsInResult = 0 73 result += "[" + CA1_MUTATIONS[pos] + CA2_MUTATIONS[pos] + "]"
95 for c in chunk: 74 else:
96 if pos in list(cg1.keys()): 75 result += c
97 varsInResult += 1 76 pos += 1
98 result += "[" + "".join(set([cg1[pos], cg2[pos], cg3[pos], cg4[pos]])) + "]" 77 compiledregex["ca"].append((re.compile(result), varsInResult))
99 else: 78
100 result += c 79 for i in range(0, len(SEARCHSTRINGS["cg"]) - CHUNK_LENGTH, CHUNK_LENGTH // 2):
101 pos += 1 80 pos = i
102 compiledregex["cg"].append((re.compile(result), varsInResult)) 81 chunk = SEARCHSTRINGS["cg"][i:i + CHUNK_LENGTH]
103 82 result = ""
104 for i in range(0, len(searchstrings["cm"]) - chunklength, chunklength // 2): 83 varsInResult = 0
105 compiledregex["cm"].append((re.compile(searchstrings["cm"][i:i+chunklength]), False)) 84 for c in chunk:
106 85 if pos in list(CG1_MUTATIONS.keys()):
107 for i in range(0, len(searchstrings["ce"]) - chunklength + 1, chunklength // 2): 86 varsInResult += 1
108 compiledregex["ce"].append((re.compile(searchstrings["ce"][i:i+chunklength]), False)) 87 result += "[" + "".join(set([CG1_MUTATIONS[pos], CG2_MUTATIONS[pos], CG3_MUTATIONS[pos], CG4_MUTATIONS[pos]])) + "]"
88 else:
89 result += c
90 pos += 1
91 compiledregex["cg"].append((re.compile(result), varsInResult))
92
93 for i in range(0, len(SEARCHSTRINGS["cm"]) - CHUNK_LENGTH, CHUNK_LENGTH // 2):
94 compiledregex["cm"].append((re.compile(SEARCHSTRINGS["cm"][i:i + CHUNK_LENGTH]), 0))
95
96 for i in range(0, len(SEARCHSTRINGS["ce"]) - CHUNK_LENGTH + 1, CHUNK_LENGTH // 2):
97 compiledregex["ce"].append((re.compile(SEARCHSTRINGS["ce"][i:i + CHUNK_LENGTH]), 0))
98
99 return compiledregex
100
109 101
110 def removeAndReturnMaxIndex(x): #simplifies a list comprehension 102 def removeAndReturnMaxIndex(x): #simplifies a list comprehension
111 m = max(x) 103 m = max(x)
112 index = x.index(m) 104 index = x.index(m)
113 x[index] = 0 105 x[index] = 0
114 return index 106 return index
115 107
116 108
117 start_location = dict() 109 def match_sequence(seq, compiledregex):
118 hits = dict() 110 currentIDHits = {"ca_hits": 0, "cg_hits": 0, "cm_hits": 0, "ce_hits": 0,
119 alltotal = 0 111 "ca1": 0, "ca2": 0, "cg1": 0, "cg2": 0, "cg3": 0, "cg4": 0}
120 for key in compiledregex: #for ca/cg/cm/ce 112 alltotal = 0
121 regularexpressions = compiledregex[key] # get the compiled regular expressions 113 start_location = dict()
122 for ID in list(dic.keys())[0:]: #for every ID 114 for key in compiledregex: # for ca/cg/cm/ce
123 if ID not in list(hits.keys()): #ensure that the dictionairy that keeps track of the hits for every gene exists 115 regularexpressions = compiledregex[key]
124 hits[ID] = {"ca_hits": 0, "cg_hits": 0, "cm_hits": 0, "ce_hits": 0, "ca1": 0, "ca2": 0, "cg1": 0, "cg2": 0, "cg3": 0, "cg4": 0}
125 currentIDHits = hits[ID]
126 seq = dic[ID]
127 lastindex = 0 116 lastindex = 0
128 start_zero = len(searchstrings[key]) #allows the reference sequence to start before search sequence (start_locations of < 0) 117 start_zero = len(SEARCHSTRINGS[key]) #allows the reference sequence to start before search sequence (start_locations of < 0)
129 start = [0] * (len(seq) + start_zero) 118 start = [0] * (len(seq) + start_zero)
130 for i, regexp in enumerate(regularexpressions): #for every regular expression 119 for i, regexp in enumerate(regularexpressions): #for every regular expression
131 relativeStartLocation = lastindex - (chunklength // 2) * i 120 relativeStartLocation = lastindex - (CHUNK_LENGTH // 2) * i
132 if relativeStartLocation >= len(seq): 121 if relativeStartLocation >= len(seq):
133 break 122 break
134 regex, hasVar = regexp 123 regex, hasVar = regexp
135 matches = regex.finditer(seq[lastindex:]) 124 matches = regex.finditer(seq[lastindex:])
136 for match in matches: #for every match with the current regex, only uses the first hit because of the break at the end of this loop 125 for match in matches: #for every match with the current regex, only uses the first hit because of the break at the end of this loop
137 lastindex += match.start() 126 lastindex += match.start()
138 start[relativeStartLocation + start_zero] += 1 127 start[relativeStartLocation + start_zero] += 1
139 if hasVar: #if the regex has a variable nt in it 128 if hasVar: #if the regex has a variable nt in it
140 chunkstart = chunklength // 2 * i #where in the reference does this chunk start 129 chunkstart = CHUNK_LENGTH // 2 * i #where in the reference does this chunk start
141 chunkend = chunklength // 2 * i + chunklength #where in the reference does this chunk end 130 chunkend = CHUNK_LENGTH // 2 * i + CHUNK_LENGTH #where in the reference does this chunk end
142 if key == "ca": #just calculate the variable nt score for 'ca', cheaper 131 if key == "ca": #just calculate the variable nt score for 'ca', cheaper
143 currentIDHits["ca1"] += len([1 for x in ca1 if chunkstart <= x < chunkend and ca1[x] == seq[lastindex + x - chunkstart]]) 132 currentIDHits["ca1"] += len([1 for x in CA1_MUTATIONS if chunkstart <= x < chunkend and CA1_MUTATIONS[x] == seq[lastindex + x - chunkstart]])
144 currentIDHits["ca2"] += len([1 for x in ca2 if chunkstart <= x < chunkend and ca2[x] == seq[lastindex + x - chunkstart]]) 133 currentIDHits["ca2"] += len([1 for x in CA2_MUTATIONS if chunkstart <= x < chunkend and CA2_MUTATIONS[x] == seq[lastindex + x - chunkstart]])
145 elif key == "cg": #just calculate the variable nt score for 'cg', cheaper 134 elif key == "cg": #just calculate the variable nt score for 'cg', cheaper
146 currentIDHits["cg1"] += len([1 for x in cg1 if chunkstart <= x < chunkend and cg1[x] == seq[lastindex + x - chunkstart]]) 135 currentIDHits["cg1"] += len([1 for x in CG1_MUTATIONS if chunkstart <= x < chunkend and CG1_MUTATIONS[x] == seq[lastindex + x - chunkstart]])
147 currentIDHits["cg2"] += len([1 for x in cg2 if chunkstart <= x < chunkend and cg2[x] == seq[lastindex + x - chunkstart]]) 136 currentIDHits["cg2"] += len([1 for x in CG2_MUTATIONS if chunkstart <= x < chunkend and CG2_MUTATIONS[x] == seq[lastindex + x - chunkstart]])
148 currentIDHits["cg3"] += len([1 for x in cg3 if chunkstart <= x < chunkend and cg3[x] == seq[lastindex + x - chunkstart]]) 137 currentIDHits["cg3"] += len([1 for x in CG3_MUTATIONS if chunkstart <= x < chunkend and CG3_MUTATIONS[x] == seq[lastindex + x - chunkstart]])
149 currentIDHits["cg4"] += len([1 for x in cg4 if chunkstart <= x < chunkend and cg4[x] == seq[lastindex + x - chunkstart]]) 138 currentIDHits["cg4"] += len([1 for x in CG4_MUTATIONS if chunkstart <= x < chunkend and CG4_MUTATIONS[x] == seq[lastindex + x - chunkstart]])
150 else: #key == "cm" #no variable regions in 'cm' or 'ce' 139 else: #key == "cm" #no variable regions in 'cm' or 'ce'
151 pass 140 pass
152 break #this only breaks when there was a match with the regex, breaking means the 'else:' clause is skipped 141 break #this only breaks when there was a match with the regex, breaking means the 'else:' clause is skipped
153 else: #only runs if there were no hits 142 else: #only runs if there were no hits
154 continue 143 continue
155 #print "found ", regex.pattern , "at", lastindex, "adding one to", (lastindex - chunklength / 2 * i), "to the start array of", ID, "gene", key, "it's now:", start[lastindex - chunklength / 2 * i] 144 #print "found ", regex.pattern , "at", lastindex, "adding one to", (lastindex - chunklength / 2 * i), "to the start array of", ID, "gene", key, "it's now:", start[lastindex - chunklength / 2 * i]
156 currentIDHits[key + "_hits"] += 1 145 currentIDHits[key + "_hits"] += 1
157 start_location[ID + "_" + key] = str([(removeAndReturnMaxIndex(start) + 1 - start_zero) for x in range(5) if len(start) > 0 and max(start) > 1]) 146 start_location[key] = str([(removeAndReturnMaxIndex(start) + 1 - start_zero) for x in range(5) if len(start) > 0 and max(start) > 1])
158 #start_location[ID + "_" + key] = str(start.index(max(start))) 147
159 148 cahits = currentIDHits["ca_hits"]
160 149 cghits = currentIDHits["cg_hits"]
161 varsInCA = float(len(list(ca1.keys())) * 2) 150 cmhits = currentIDHits["cm_hits"]
162 varsInCG = float(len(list(cg1.keys())) * 2) - 2 # -2 because the sliding window doesn't hit the first and last nt twice 151 cehits = currentIDHits["ce_hits"]
163 varsInCM = 0 152 if cahits >= cghits and cahits >= cmhits and cahits >= cehits: # its a ca gene
164 varsInCE = 0 153 ca1hits = currentIDHits["ca1"]
165 154 ca2hits = currentIDHits["ca2"]
166 def round_int(val): 155 if ca1hits >= ca2hits:
167 return int(round(val)) 156 # TODO: All variants with 0 matched are matched to IGA1 with 0 hits
168 157 # TODO: these are later turned into unmatched by the merge_and_filter.R
169 first = True 158 # TODO: script
170 seq_write_count=0 159 return "IGA1", ca1hits, cahits, start_location["ca"]
171 with open(infile, 'r') as f: #read all sequences into a dictionary as key = ID, value = sequence 160 else:
172 with open(output, 'w') as o: 161 return "IGA2", ca2hits, cahits, start_location["ca"]
173 for line in f: 162 elif cghits >= cahits and cghits >= cmhits and cghits >= cehits: # its a cg gene
174 total += 1 163 cg1hits = currentIDHits["cg1"]
175 if first: 164 cg2hits = currentIDHits["cg2"]
176 o.write("Sequence ID\tbest_match\tnt_hit_percentage\tchunk_hit_percentage\tstart_locations\n") 165 cg3hits = currentIDHits["cg3"]
177 first = False 166 cg4hits = currentIDHits["cg4"]
178 continue 167 if cg1hits >= cg2hits and cg1hits >= cg3hits and cg1hits >= cg4hits: # cg1 gene
179 linesplt = line.split("\t") 168 return "IGG1", cg1hits, cghits, start_location["cg"]
180 if linesplt[2] == "No results": 169 elif cg2hits >= cg1hits and cg2hits >= cg3hits and cg2hits >= cg4hits: # cg2 gene
181 pass 170 return "IGG2", cg2hits, cghits, start_location["cg"]
182 ID = linesplt[1] 171 elif cg3hits >= cg1hits and cg3hits >= cg2hits and cg3hits >= cg4hits: # cg3 gene
183 currentIDHits = hits[ID] 172 return "IGG3", cg3hits, cghits, start_location["cg"]
184 possibleca = float(len(compiledregex["ca"])) 173 else: # cg4 gene
185 possiblecg = float(len(compiledregex["cg"])) 174 return "IGG4", cg4hits, cghits, start_location["cg"]
186 possiblecm = float(len(compiledregex["cm"])) 175 else: # its a cm or ce gene
187 possiblece = float(len(compiledregex["ce"])) 176 if cmhits >= cehits:
188 cahits = currentIDHits["ca_hits"] 177 return "IGM", 0, cmhits, start_location["cm"]
189 cghits = currentIDHits["cg_hits"] 178 else:
190 cmhits = currentIDHits["cm_hits"] 179 return "IGE", 0, cehits, start_location["ce"]
191 cehits = currentIDHits["ce_hits"] 180
192 if cahits >= cghits and cahits >= cmhits and cahits >= cehits: #its a ca gene 181
193 ca1hits = currentIDHits["ca1"] 182 def main():
194 ca2hits = currentIDHits["ca2"] 183 parser = argparse.ArgumentParser()
195 if ca1hits >= ca2hits: 184 parser.add_argument("--input",
196 o.write(ID + "\tIGA1\t" + str(round_int(ca1hits / varsInCA * 100)) + "\t" + str(round_int(cahits / possibleca * 100)) + "\t" + start_location[ID + "_ca"] + "\n") 185 help="The 1_Summary file from an IMGT zip file")
197 else: 186 parser.add_argument("--output",
198 o.write(ID + "\tIGA2\t" + str(round_int(ca2hits / varsInCA * 100)) + "\t" + str(round_int(cahits / possibleca * 100)) + "\t" + start_location[ID + "_ca"] + "\n") 187 help="The annotated output file to be merged back "
199 elif cghits >= cahits and cghits >= cmhits and cghits >= cehits: #its a cg gene 188 "with the summary file")
200 cg1hits = currentIDHits["cg1"] 189 args = parser.parse_args()
201 cg2hits = currentIDHits["cg2"] 190 varsInCA = float(len(list(CA1_MUTATIONS.keys())) * 2)
202 cg3hits = currentIDHits["cg3"] 191 varsInCG = float(len(list(
203 cg4hits = currentIDHits["cg4"] 192 CG1_MUTATIONS.keys())) * 2) - 2 # -2 because the sliding window doesn't hit the first and last nt twice
204 if cg1hits >= cg2hits and cg1hits >= cg3hits and cg1hits >= cg4hits: #cg1 gene 193 subclass_vars = {
205 o.write(ID + "\tIGG1\t" + str(round_int(cg1hits / varsInCG * 100)) + "\t" + str(round_int(cghits / possiblecg * 100)) + "\t" + start_location[ID + "_cg"] + "\n") 194 "IGA1": varsInCA, "IGA2": varsInCA,
206 elif cg2hits >= cg1hits and cg2hits >= cg3hits and cg2hits >= cg4hits: #cg2 gene 195 "IGG1": varsInCG, "IGG2": varsInCG, "IGG3": varsInCG, "IGG4": varsInCG,
207 o.write(ID + "\tIGG2\t" + str(round_int(cg2hits / varsInCG * 100)) + "\t" + str(round_int(cghits / possiblecg * 100)) + "\t" + start_location[ID + "_cg"] + "\n") 196 "IGE": 0,
208 elif cg3hits >= cg1hits and cg3hits >= cg2hits and cg3hits >= cg4hits: #cg3 gene 197 "IGM": 0,
209 o.write(ID + "\tIGG3\t" + str(round_int(cg3hits / varsInCG * 100)) + "\t" + str(round_int(cghits / possiblecg * 100)) + "\t" + start_location[ID + "_cg"] + "\n") 198 }
210 else: #cg4 gene 199 compiledregex = create_compiled_regexes()
211 o.write(ID + "\tIGG4\t" + str(round_int(cg4hits / varsInCG * 100)) + "\t" + str(round_int(cghits / possiblecg * 100)) + "\t" + start_location[ID + "_cg"] + "\n") 200 possibleca = float(len(compiledregex["ca"]))
212 else: #its a cm or ce gene 201 possiblecg = float(len(compiledregex["cg"]))
213 if cmhits >= cehits: 202 possiblecm = float(len(compiledregex["cm"]))
214 o.write(ID + "\tIGM\t100\t" + str(round_int(cmhits / possiblecm * 100)) + "\t" + start_location[ID + "_cm"] + "\n") 203 possiblece = float(len(compiledregex["ce"]))
215 else: 204 class_chunks = {
216 o.write(ID + "\tIGE\t100\t" + str(round_int(cehits / possiblece * 100)) + "\t" + start_location[ID + "_ce"] + "\n") 205 "IGA1": possibleca, "IGA2": possibleca,
217 seq_write_count += 1 206 "IGE": possiblece,
218 207 "IGG1": possiblecg, "IGG2": possiblecg, "IGG3": possiblecg,
219 print("Time: %i" % (int(time.time() * 1000) - starttime)) 208 "IGG4": possiblecg,
220 209 "IGM": possiblecm
221 print("Number of sequences written to file:", seq_write_count) 210 }
222 211 with open(args.output, "wt") as output:
223 212 output.write("Sequence ID\tbest_match\tnt_hit_percentage\t"
224 213 "chunk_hit_percentage\tstart_locations\n")
225 214 for id, sequence in generate_sequence_and_id_from_summary(args.input):
226 215 best_match, subclass_hits, class_hits, start_locations = \
216 match_sequence(sequence, compiledregex)
217 variable_nucs = subclass_vars[best_match]
218 if variable_nucs:
219 subclass_percentage = round(subclass_hits * 100 /
220 variable_nucs)
221 else:
222 subclass_percentage = 100
223 class_percentage = round(class_hits * 100 / class_chunks[best_match])
224 output.write(f"{id}\t{best_match}\t{subclass_percentage}\t"
225 f"{class_percentage}\t{start_locations}\n")
226
227
228 if __name__ == "__main__":
229 main()