Mercurial > repos > drosofff > msp_blastparser_and_hits

comparison BlastParser_and_hits.py @ 15:1991c830504a draft

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/msp_blastparser_and_hits commit b6de14061c479f0418cd89e26d6f5ac26e565a07
author drosofff
date Wed, 09 Nov 2016 11:32:32 -0500
parents 78c34df2dd8d
children
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14:6dfa79a6908a 15:1991c830504a
1 #!/usr/bin/python 1 #!/usr/bin/python
2 # blastn tblastn blastx parser revised 14-1-2016. 2 # blastn tblastn blastx parser revised 14-1-2016.
3 # drosofff@gmail.com 3 # drosofff@gmail.com
4 4
5 import sys
6 import argparse 5 import argparse
7 from collections import defaultdict 6 from collections import defaultdict
7
8 8
9 def Parser(): 9 def Parser():
10 the_parser = argparse.ArgumentParser() 10 the_parser = argparse.ArgumentParser()
11 the_parser.add_argument('--blast', action="store", type=str, help="Path to the blast output (tabular format, 12 column)") 11 the_parser.add_argument('--blast', action="store", type=str, help="Path to the blast output (tabular format, 12 column)")
12 the_parser.add_argument('--sequences', action="store", type=str, help="Path to the fasta file with blasted sequences") 12 the_parser.add_argument('--sequences', action="store", type=str, help="Path to the fasta file with blasted sequences")
13 the_parser.add_argument('--fastaOutput', action="store", type=str, help="fasta output file of blast hits") 13 the_parser.add_argument('--fastaOutput', action="store", type=str, help="fasta output file of blast hits")
14 the_parser.add_argument('--tabularOutput', action="store", type=str, help="tabular output file of blast analysis") 14 the_parser.add_argument('--tabularOutput', action="store", type=str, help="tabular output file of blast analysis")
15 the_parser.add_argument('--flanking', action="store", type=int, help="number of flanking nucleotides added to the hit sequences") 15 the_parser.add_argument('--flanking', action="store", type=int, help="number of flanking nucleotides added to the hit sequences")
16 the_parser.add_argument('--mode', action="store", choices=["verbose", "short"], type=str, help="reporting (verbose) or not reporting (short) oases contigs") 16 the_parser.add_argument('--mode', action="store", choices=["verbose", "short"], type=str, help="reporting (verbose) or not reporting (short) oases contigs")
17 the_parser.add_argument('--filter_relativeCov', action="store", type=float, default=0, help="filter out relative coverages below the specified ratio (float number)") 17 the_parser.add_argument('--filter_relativeCov', action="store", type=float, default=0, help="filter out relative coverages below the specified ratio (float number)")
18 the_parser.add_argument('--filter_maxScore', action="store", type=float, default=0, help="filter out best BitScores below the specified float number") 18 the_parser.add_argument('--filter_maxScore', action="store", type=float, default=0, help="filter out best BitScores below the specified float number")
19 the_parser.add_argument('--filter_meanScore', action="store", type=float, default=0, help="filter out mean BitScores below the specified float number") 19 the_parser.add_argument('--filter_meanScore', action="store", type=float, default=0, help="filter out mean BitScores below the specified float number")
20 the_parser.add_argument('--filter_term_in', action="store", type=str, default="", help="select the specified term in the subject list") 20 the_parser.add_argument('--filter_term_in', action="store", type=str, default="", help="select the specified term in the subject list")
21 the_parser.add_argument('--filter_term_out', action="store", type=str, default="", help="exclude the specified term from the subject list") 21 the_parser.add_argument('--filter_term_out', action="store", type=str, default="", help="exclude the specified term from the subject list")
22 the_parser.add_argument('--al_sequences', action="store", type=str, help="sequences that have been blast aligned") 22 the_parser.add_argument('--al_sequences', action="store", type=str, help="sequences that have been blast aligned")
23 the_parser.add_argument('--un_sequences', action="store", type=str, help="sequences that have not been blast aligned") 23 the_parser.add_argument('--un_sequences', action="store", type=str, help="sequences that have not been blast aligned")
24 the_parser.add_argument('--dataset_name', action="store", type=str, default="", help="the name of the dataset that has been parsed, to be reported in the output") 24 the_parser.add_argument('--dataset_name', action="store", type=str, default="", help="the name of the dataset that has been parsed, to be reported in the output")
25 args = the_parser.parse_args() 25 args = the_parser.parse_args()
26 if not all ( (args.sequences, args.blast, args.fastaOutput, args.tabularOutput) ): 26 if not all((args.sequences, args.blast, args.fastaOutput, args.tabularOutput)):
27 the_parser.error('argument(s) missing, call the -h option of the script') 27 the_parser.error('argument(s) missing, call the -h option of the script')
28 if not args.flanking: 28 if not args.flanking:
29 args.flanking = 0 29 args.flanking = 0
30 return args 30 return args
31 31
32
32 def median(lst): 33 def median(lst):
33 lst = sorted(lst) 34 lst = sorted(lst)
34 if len(lst) < 1: 35 if len(lst) < 1:
35 return None 36 return None
36 if len(lst) %2 == 1: 37 if len(lst) % 2 == 1:
37 return lst[((len(lst)+1)/2)-1] 38 return lst[((len(lst)+1)/2)-1]
38 if len(lst) %2 == 0: 39 if len(lst) % 2 == 0:
39 return float(sum(lst[(len(lst)/2)-1:(len(lst)/2)+1]))/2.0 40 return float(sum(lst[(len(lst)/2)-1:(len(lst)/2)+1]))/2.0
41
40 42
41 def mean(lst): 43 def mean(lst):
42 if len(lst) < 1: 44 if len(lst) < 1:
43 return 0 45 return 0
44 return sum(lst) / float(len(lst)) 46 return sum(lst) / float(len(lst))
45 47
46 def getfasta (fastafile): 48
49 def getfasta(fastafile):
47 fastadic = {} 50 fastadic = {}
48 for line in open (fastafile): 51 for line in open(fastafile):
49 if line[0] == ">": 52 if line[0] == ">":
50 header = line[1:-1] 53 header = line[1:-1]
51 fastadic[header] = "" 54 fastadic[header] = ""
52 else: 55 else:
53 fastadic[header] += line 56 fastadic[header] += line
54 for header in fastadic: 57 for header in fastadic:
55 fastadic[header] = "".join(fastadic[header].split("\n")) 58 fastadic[header] = "".join(fastadic[header].split("\n"))
56 return fastadic 59 return fastadic
57 60
61
58 def insert_newlines(string, every=60): 62 def insert_newlines(string, every=60):
59 lines = [] 63 lines = []
60 for i in xrange(0, len(string), every): 64 for i in xrange(0, len(string), every):
61 lines.append(string[i:i+every]) 65 lines.append(string[i:i+every])
62 return '\n'.join(lines) 66 return '\n'.join(lines)
63 67
64 def getblast (blastfile): 68
69 def getblast(blastfile):
65 '''blastinfo [0] Percentage of identical matches 70 '''blastinfo [0] Percentage of identical matches
66 blastinfo [1] Alignment length 71 blastinfo [1] Alignment length
67 blastinfo [2] Number of mismatches 72 blastinfo [2] Number of mismatches
68 blastinfo [3] Number of gap openings 73 blastinfo [3] Number of gap openings
69 blastinfo [4] Start of alignment in query 74 blastinfo [4] Start of alignment in query
71 blastinfo [6] Start of alignment in subject (database hit) 76 blastinfo [6] Start of alignment in subject (database hit)
72 blastinfo [7] End of alignment in subject (database hit) 77 blastinfo [7] End of alignment in subject (database hit)
73 blastinfo [8] Expectation value (E-value) 78 blastinfo [8] Expectation value (E-value)
74 blastinfo [9] Bit score 79 blastinfo [9] Bit score
75 blastinfo [10] Subject length (NEED TO BE SPECIFIED WHEN RUNNING BLAST) ''' 80 blastinfo [10] Subject length (NEED TO BE SPECIFIED WHEN RUNNING BLAST) '''
76 blastdic = defaultdict (dict) 81 blastdic = defaultdict(dict)
77 for line in open (blastfile): 82 for line in open(blastfile):
78 fields = line[:-1].split("\t") 83 fields = line[:-1].split("\t")
79 transcript = fields[0] 84 transcript = fields[0]
80 subject = fields[1] 85 subject = fields[1]
81 blastinfo = [float(fields[2]) ] # blastinfo[0] 86 blastinfo = [float(fields[2])] # blastinfo[0]
82 blastinfo = blastinfo + [int(i) for i in fields[3:10] ] # blastinfo[1:8] insets 1 to 7 87 blastinfo = blastinfo + [int(i) for i in fields[3:10]] # blastinfo[1:8] insets 1 to 7
83 blastinfo.append(fields[10]) # blastinfo[8] E-value remains as a string type 88 blastinfo.append(fields[10]) # blastinfo[8] E-value remains as a string type
84 blastinfo.append(float(fields[11])) # blastinfo[9] Bit score 89 blastinfo.append(float(fields[11])) # blastinfo[9] Bit score
85 blastinfo.append(int(fields[12])) # blastinfo[10] Subject length MUST BE RETRIEVED THROUGH A 13 COLUMN BLAST OUTPUT 90 blastinfo.append(int(fields[12])) # blastinfo[10] Subject length MUST BE RETRIEVED THROUGH A 13 COLUMN BLAST OUTPUT
86 try: 91 try:
87 blastdic[subject][transcript].append(blastinfo) 92 blastdic[subject][transcript].append(blastinfo)
88 except: 93 except Exception:
89 blastdic[subject][transcript] = [ blastinfo ] 94 blastdic[subject][transcript] = [blastinfo]
90 return blastdic 95 return blastdic
91 96
92 def getseq (fastadict, transcript, up, down, orientation="direct"): 97
93 def reverse (seq): 98 def getseq(fastadict, transcript, up, down, orientation="direct"):
94 revdict = {"A":"T","T":"A","G":"C","C":"G","N":"N"} 99 def reverse(seq):
100 revdict = {"A": "T", "T": "A", "G": "C", "C": "G", "N": "N"}
95 revseq = [revdict[i] for i in seq[::-1]] 101 revseq = [revdict[i] for i in seq[::-1]]
96 return "".join(revseq) 102 return "".join(revseq)
97 pickseq = fastadict[transcript][up-1:down] 103 pickseq = fastadict[transcript][up-1:down]
98 if orientation == "direct": 104 if orientation == "direct":
99 return pickseq 105 return pickseq
100 else: 106 else:
101 return reverse(pickseq) 107 return reverse(pickseq)
102 108
103 def subjectCoverage (fastadict, blastdict, subject, QueriesFlankingNucleotides=0): 109
110 def subjectCoverage(fastadict, blastdict, subject, QueriesFlankingNucleotides=0):
104 SubjectCoverageList = [] 111 SubjectCoverageList = []
105 HitDic = {} 112 HitDic = {}
106 bitScores = [] 113 bitScores = []
107 for transcript in blastdict[subject]: 114 for transcript in blastdict[subject]:
108 prefix = "%s--%s_" % (subject, transcript) 115 prefix = "%s--%s_" % (subject, transcript)
109 hitNumber = 0 116 hitNumber = 0
110 for hit in blastdict[subject][transcript]: 117 for hit in blastdict[subject][transcript]:
111 hitNumber += 1 118 hitNumber += 1
112 suffix = "hit%s_IdMatch=%s,AligLength=%s,E-val=%s" % (hitNumber, hit[0], hit[1], hit[8]) 119 suffix = "hit%s_IdMatch=%s,AligLength=%s,E-val=%s" % (hitNumber, hit[0], hit[1], hit[8])
113 HitDic[prefix+suffix] = GetHitSequence (fastadict, transcript, hit[4], hit[5], QueriesFlankingNucleotides) #query coverage by a hit is in hit[4:6] 120 HitDic[prefix+suffix] = GetHitSequence(fastadict, transcript, hit[4], hit[5], QueriesFlankingNucleotides) # query coverage by a hit is in hit[4:6]
114 SubjectCoverageList += range (min([hit[6], hit[7]]), max([hit[6], hit[7]]) + 1) # subject coverage by a hit is in hit[6:8] 121 SubjectCoverageList += range(min([hit[6], hit[7]]), max([hit[6], hit[7]]) + 1) # subject coverage by a hit is in hit[6:8]
115 bitScores.append(hit[9]) 122 bitScores.append(hit[9])
116 subjectLength = hit [10] # always the same value for a given subject. Stupid but simple 123 subjectLength = hit[10] # always the same value for a given subject. Stupid but simple
117 TotalSubjectCoverage = len ( set (SubjectCoverageList) ) 124 TotalSubjectCoverage = len(set(SubjectCoverageList))
118 RelativeSubjectCoverage = TotalSubjectCoverage/float(subjectLength) 125 RelativeSubjectCoverage = TotalSubjectCoverage/float(subjectLength)
119 return HitDic, subjectLength, TotalSubjectCoverage, RelativeSubjectCoverage, max(bitScores), mean(bitScores) 126 return HitDic, subjectLength, TotalSubjectCoverage, RelativeSubjectCoverage, max(bitScores), mean(bitScores)
120 127
121 def GetHitSequence (fastadict, FastaHeader, leftCoordinate, rightCoordinate, FlankingValue): 128
129 def GetHitSequence(fastadict, FastaHeader, leftCoordinate, rightCoordinate, FlankingValue):
122 if rightCoordinate > leftCoordinate: 130 if rightCoordinate > leftCoordinate:
123 polarity = "direct" 131 polarity = "direct"
124 else: 132 else:
125 polarity = "reverse" 133 polarity = "reverse"
126 leftCoordinate, rightCoordinate = rightCoordinate, leftCoordinate 134 leftCoordinate, rightCoordinate = rightCoordinate, leftCoordinate
127 if leftCoordinate - FlankingValue > 0: 135 if leftCoordinate - FlankingValue > 0:
128 leftCoordinate -= FlankingValue 136 leftCoordinate -= FlankingValue
129 else: 137 else:
130 leftCoordinate = 1 138 leftCoordinate = 1
131 return getseq (fastadict, FastaHeader, leftCoordinate, rightCoordinate, polarity) 139 return getseq(fastadict, FastaHeader, leftCoordinate, rightCoordinate, polarity)
132 140
133 def outputParsing (dataset_name, F, Fasta, results, Xblastdict, fastadict, filter_relativeCov=0, filter_maxScore=0, filter_meanScore=0, filter_term_in="", filter_term_out="", mode="verbose"): 141
134 def filter_results (results, filter_relativeCov=0, filter_maxScore=0, filter_meanScore=0, filter_term_in="", filter_term_out=""): 142 def outputParsing(dataset_name, F, Fasta, results, Xblastdict, fastadict, filter_relativeCov=0, filter_maxScore=0, filter_meanScore=0, filter_term_in="", filter_term_out="", mode="verbose"):
143 def filter_results(results, filter_relativeCov=0, filter_maxScore=0, filter_meanScore=0, filter_term_in="", filter_term_out=""):
135 for subject in results.keys(): 144 for subject in results.keys():
136 if results[subject]["RelativeSubjectCoverage"]<filter_relativeCov: 145 if results[subject]["RelativeSubjectCoverage"] < filter_relativeCov:
137 del results[subject] 146 del results[subject]
138 continue 147 continue
139 if results[subject]["maxBitScores"]<filter_maxScore: 148 if results[subject]["maxBitScores"] < filter_maxScore:
140 del results[subject] 149 del results[subject]
141 continue 150 continue
142 if results[subject]["meanBitScores"]<filter_meanScore: 151 if results[subject]["meanBitScores"] < filter_meanScore:
143 del results[subject] 152 del results[subject]
144 continue 153 continue
145 if filter_term_in in subject: 154 if filter_term_in in subject:
146 pass 155 pass
147 else: 156 else:
149 continue 158 continue
150 if filter_term_out and filter_term_out in subject: 159 if filter_term_out and filter_term_out in subject:
151 del results[subject] 160 del results[subject]
152 continue 161 continue
153 return results 162 return results
154 163
155 F= open(F, "w") 164 F = open(F, "w")
156 Fasta=open(Fasta, "w") 165 Fasta = open(Fasta, "w")
157 blasted_transcripts = [] 166 blasted_transcripts = []
158 filter_results (results, filter_relativeCov, filter_maxScore, filter_meanScore, filter_term_in, filter_term_out) 167 filter_results(results, filter_relativeCov, filter_maxScore, filter_meanScore, filter_term_in, filter_term_out)
159 for subject in results: 168 for subject in results:
160 for transcript in Xblastdict[subject]: 169 for transcript in Xblastdict[subject]:
161 blasted_transcripts.append(transcript) 170 blasted_transcripts.append(transcript)
162 blasted_transcripts = list( set( blasted_transcripts)) 171 blasted_transcripts = list(set(blasted_transcripts))
163 if mode == "verbose": 172 if mode == "verbose":
164 print >>F, "--- %s ---" % (dataset_name) 173 print >>F, "--- %s ---" % (dataset_name)
165 print >>F, "# SeqId\t%Identity\tAlignLength\tStartSubject\tEndSubject\t%QueryHitCov\tE-value\tBitScore" 174 print >>F, "# SeqId\t%Identity\tAlignLength\tStartSubject\tEndSubject\t%QueryHitCov\tE-value\tBitScore"
166 for subject in sorted (results, key=lambda x: results[x]["meanBitScores"], reverse=True): 175 for subject in sorted(results, key=lambda x: results[x]["meanBitScores"], reverse=True):
167 print >> F, " \n# %s" % subject 176 print >> F, " \n# %s" % subject
168 print >> F, "# Suject Length: %s" % (results[subject]["subjectLength"]) 177 print >> F, "# Suject Length: %s" % (results[subject]["subjectLength"])
169 print >> F, "# Total Subject Coverage: %s" % (results[subject]["TotalCoverage"]) 178 print >> F, "# Total Subject Coverage: %s" % (results[subject]["TotalCoverage"])
170 print >> F, "# Relative Subject Coverage: %s" % (results[subject]["RelativeSubjectCoverage"]) 179 print >> F, "# Relative Subject Coverage: %s" % (results[subject]["RelativeSubjectCoverage"])
171 print >> F, "# Best Bit Score: %s" % (results[subject]["maxBitScores"]) 180 print >> F, "# Best Bit Score: %s" % (results[subject]["maxBitScores"])
172 print >> F, "# Mean Bit Score: %s" % (results[subject]["meanBitScores"]) 181 print >> F, "# Mean Bit Score: %s" % (results[subject]["meanBitScores"])
173 for header in results[subject]["HitDic"]: 182 for header in results[subject]["HitDic"]:
174 print >> Fasta, ">%s\n%s" % (header, insert_newlines(results[subject]["HitDic"][header]) ) 183 print >> Fasta, ">%s\n%s" % (header, insert_newlines(results[subject]["HitDic"][header]))
175 print >> Fasta, "" # final carriage return for the sequence 184 print >> Fasta, "" # final carriage return for the sequence
176 for transcript in Xblastdict[subject]: 185 for transcript in Xblastdict[subject]:
177 transcriptSize = float(len(fastadict[transcript])) 186 transcriptSize = float(len(fastadict[transcript]))
178 for hit in Xblastdict[subject][transcript]: 187 for hit in Xblastdict[subject][transcript]:
179 percentIdentity, alignLenght, subjectStart, subjectEnd, queryCov = hit[0], hit[1], hit[6], hit[7], "%.1f" % (abs(hit[5]-hit[4])/transcriptSize*100) 188 percentIdentity, alignLenght, subjectStart, subjectEnd, queryCov = hit[0], hit[1], hit[6], hit[7], "%.1f" % (abs(hit[5]-hit[4])/transcriptSize*100)
180 Eval, BitScore = hit[8], hit[9] 189 Eval, BitScore = hit[8], hit[9]
183 info = "\t".join(info) 192 info = "\t".join(info)
184 print >> F, info 193 print >> F, info
185 else: 194 else:
186 print >>F, "--- %s ---" % (dataset_name) 195 print >>F, "--- %s ---" % (dataset_name)
187 print >>F, "# subject\tsubject length\tTotal Subject Coverage\tRelative Subject Coverage\tBest Bit Score\tMean Bit Score" 196 print >>F, "# subject\tsubject length\tTotal Subject Coverage\tRelative Subject Coverage\tBest Bit Score\tMean Bit Score"
188 for subject in sorted (results, key=lambda x: results[x]["meanBitScores"], reverse=True): 197 for subject in sorted(results, key=lambda x: results[x]["meanBitScores"], reverse=True):
189 line = [] 198 line = []
190 line.append(subject) 199 line.append(subject)
191 line.append(results[subject]["subjectLength"]) 200 line.append(results[subject]["subjectLength"])
192 line.append(results[subject]["TotalCoverage"]) 201 line.append(results[subject]["TotalCoverage"])
193 line.append(results[subject]["RelativeSubjectCoverage"]) 202 line.append(results[subject]["RelativeSubjectCoverage"])
194 line.append(results[subject]["maxBitScores"]) 203 line.append(results[subject]["maxBitScores"])
195 line.append(results[subject]["meanBitScores"]) 204 line.append(results[subject]["meanBitScores"])
196 line = [str(i) for i in line] 205 line = [str(i) for i in line]
197 print >> F, "\t".join(line) 206 print >> F, "\t".join(line)
198 for header in results[subject]["HitDic"]: 207 for header in results[subject]["HitDic"]:
199 print >> Fasta, ">%s\n%s" % (header, insert_newlines(results[subject]["HitDic"][header]) ) 208 print >> Fasta, ">%s\n%s" % (header, insert_newlines(results[subject]["HitDic"][header]))
200 print >> Fasta, "" # final carriage return for the sequence 209 print >> Fasta, "" # final carriage return for the sequence
201 F.close() 210 F.close()
202 Fasta.close() 211 Fasta.close()
203 return blasted_transcripts 212 return blasted_transcripts
204 213
205 def dispatch_sequences (fastadict, blasted_transcripts, matched_sequences, unmatched_sequences): 214
215 def dispatch_sequences(fastadict, blasted_transcripts, matched_sequences, unmatched_sequences):
206 '''to output the sequences that matched and did not matched in the blast''' 216 '''to output the sequences that matched and did not matched in the blast'''
207 F_matched = open (matched_sequences, "w") 217 F_matched = open(matched_sequences, "w")
208 F_unmatched = open (unmatched_sequences, "w") 218 F_unmatched = open(unmatched_sequences, "w")
209 for transcript in fastadict: 219 for transcript in fastadict:
210 if transcript in blasted_transcripts: # le list of blasted_transcripts is generated by the outputParsing function 220 if transcript in blasted_transcripts: # list of blasted_transcripts is generated by the outputParsing function
211 print >> F_matched, ">%s\n%s" % (transcript, insert_newlines(fastadict[transcript]) ) 221 print >> F_matched, ">%s\n%s" % (transcript, insert_newlines(fastadict[transcript]))
212 else: 222 else:
213 print >> F_unmatched, ">%s\n%s" % (transcript, insert_newlines(fastadict[transcript]) ) 223 print >> F_unmatched, ">%s\n%s" % (transcript, insert_newlines(fastadict[transcript]))
214 F_matched.close() 224 F_matched.close()
215 F_unmatched.close() 225 F_unmatched.close()
216 return 226 return
217 227
218 def __main__ (): 228
229 def __main__():
219 args = Parser() 230 args = Parser()
220 fastadict = getfasta (args.sequences) 231 fastadict = getfasta(args.sequences)
221 Xblastdict = getblast (args.blast) 232 Xblastdict = getblast(args.blast)
222 results = defaultdict(dict) 233 results = defaultdict(dict)
223 for subject in Xblastdict: 234 for subject in Xblastdict:
224 results[subject]["HitDic"], results[subject]["subjectLength"], results[subject]["TotalCoverage"], results[subject]["RelativeSubjectCoverage"], results[subject]["maxBitScores"], results[subject]["meanBitScores"] = subjectCoverage(fastadict, Xblastdict, subject, args.flanking) 235 results[subject]["HitDic"], results[subject]["subjectLength"], results[subject]["TotalCoverage"], results[subject]["RelativeSubjectCoverage"], results[subject]["maxBitScores"], results[subject]["meanBitScores"] = subjectCoverage(fastadict, Xblastdict, subject, args.flanking)
225 blasted_transcripts = outputParsing (args.dataset_name, args.tabularOutput, args.fastaOutput, results, Xblastdict, fastadict, 236 blasted_transcripts = outputParsing(args.dataset_name, args.tabularOutput,
226 filter_relativeCov=args.filter_relativeCov, filter_maxScore=args.filter_maxScore, 237 args.fastaOutput, results, Xblastdict, fastadict,
227 filter_meanScore=args.filter_meanScore, filter_term_in=args.filter_term_in, 238 filter_relativeCov=args.filter_relativeCov,
228 filter_term_out=args.filter_term_out, mode=args.mode) 239 filter_maxScore=args.filter_maxScore,
229 dispatch_sequences (fastadict, blasted_transcripts, args.al_sequences, args.un_sequences) 240 filter_meanScore=args.filter_meanScore,
230 241 filter_term_in=args.filter_term_in,
231 if __name__=="__main__": __main__() 242 filter_term_out=args.filter_term_out,
243 mode=args.mode)
244 dispatch_sequences(fastadict, blasted_transcripts, args.al_sequences, args.un_sequences)
245
246 if __name__ == "__main__":
247 __main__()