annotate unipept.py @ 2:503ab8a39006 draft

planemo upload for repository http://unipept.ugent.be/apidocs commit b4871f9659a924a68430aed3a93f4f9bad733fd6
author galaxyp
date Wed, 07 Dec 2016 16:44:07 -0500
parents 0c1ee95282fa
children 34758ab8aaa4
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1 #!/usr/bin/env python
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2 """
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3 #
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4 #------------------------------------------------------------------------------
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5 # University of Minnesota
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6 # Copyright 2015, Regents of the University of Minnesota
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7 #------------------------------------------------------------------------------
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8 # Author:
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9 #
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10 # James E Johnson
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11 #
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12 #------------------------------------------------------------------------------
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13 """
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14
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15 import json
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16 import logging
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17 import optparse
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18 from optparse import OptionParser
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19 import os
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20 import sys
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21 import re
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22 import urllib
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23 import urllib2
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24 try:
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25 import xml.etree.cElementTree as ET
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26 except ImportError:
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27 import xml.etree.ElementTree as ET
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28
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29 def warn_err(msg,exit_code=1):
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30 sys.stderr.write(msg)
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31 if exit_code:
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32 sys.exit(exit_code)
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33
1
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34 pept2lca_column_order = ['peptide','taxon_rank','taxon_id','taxon_name']
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35 pept2lca_extra_column_order = ['peptide','superkingdom','kingdom','subkingdom','superphylum','phylum','subphylum','superclass','class','subclass','infraclass','superorder','order','suborder','infraorder','parvorder','superfamily','family','subfamily','tribe','subtribe','genus','subgenus','species_group','species_subgroup','species','subspecies','varietas','forma' ]
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36 pept2lca_all_column_order = pept2lca_column_order + pept2lca_extra_column_order[1:]
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37 pept2prot_column_order = ['peptide','uniprot_id','taxon_id']
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38 pept2prot_extra_column_order = pept2prot_column_order + ['taxon_name','ec_references','go_references','refseq_ids','refseq_protein_ids','insdc_ids','insdc_protein_ids']
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39
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40 def __main__():
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41 version = '1.1'
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42 pep_pat = '^([ABCDEFGHIKLMNPQRSTVWXYZ]+)$'
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43
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44 def read_tabular(filepath,col):
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45 peptides = []
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46 with open(filepath) as fp:
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47 for i,line in enumerate(fp):
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48 if line.strip() == '' or line.startswith('#'):
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49 continue
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50 fields = line.rstrip('\n').split('\t')
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51 peptide = fields[col]
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52 if not re.match(pep_pat,peptide):
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53 warn_err('"%s" is not a peptide (line %d column %d of tabular file: %s)\n' % (peptide,i,col,filepath),exit_code=invalid_ec)
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54 peptides.append(peptide)
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55 return peptides
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56
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57 def get_fasta_entries(fp):
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58 name, seq = None, []
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59 for line in fp:
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60 line = line.rstrip()
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61 if line.startswith(">"):
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62 if name: yield (name, ''.join(seq))
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63 name, seq = line, []
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64 else:
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65 seq.append(line)
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66 if name: yield (name, ''.join(seq))
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67
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68 def read_fasta(filepath):
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69 peptides = []
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70 with open(filepath) as fp:
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71 for id, peptide in get_fasta_entries(fp):
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72 if not re.match(pep_pat,peptide):
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73 warn_err('"%s" is not a peptide (id %s of fasta file: %s)\n' % (peptide,id,filepath),exit_code=invalid_ec)
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74 peptides.append(peptide)
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75 return peptides
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76
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77 def read_mzid(fp):
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78 peptides = []
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79 for event, elem in ET.iterparse(fp):
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80 if event == 'end':
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81 if re.search('PeptideSequence',elem.tag):
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82 peptides.append(elem.text)
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83 return peptides
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84
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85 def read_pepxml(fp):
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86 peptides = []
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87 for event, elem in ET.iterparse(fp):
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88 if event == 'end':
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89 if re.search('search_hit',elem.tag):
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90 peptides.append(elem.get('peptide'))
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91 return peptides
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92
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93 def best_match(peptide,matches):
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94 if not matches:
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95 return None
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96 elif len(matches) == 1:
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97 return matches[0].copy()
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98 else:
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99 # find the most specific match (peptide is always the first column order field)
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100 for col in reversed(pept2lca_extra_column_order[1:]):
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101 col_id = col+"_id" if options.extra else col
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102 for match in matches:
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103 if 'taxon_rank' in match and match['taxon_rank'] == col:
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104 return match.copy()
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105 if col_id in match and match[col_id]:
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106 return match.copy()
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107 return None
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108
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109 #Parse Command Line
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110 parser = optparse.OptionParser()
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111 # unipept API choice
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112 parser.add_option( '-a', '--api', dest='unipept', default='pept2lca', choices=['pept2lca','pept2taxa','pept2prot'], help='The unipept application: pept2lca, pept2taxa, or pept2prot' )
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113 # input files
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114 parser.add_option( '-t', '--tabular', dest='tabular', default=None, help='A tabular file that contains a peptide column' )
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115 parser.add_option( '-c', '--column', dest='column', type='int', default=0, help='The column (zero-based) in the tabular file that contains peptide sequences' )
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116 parser.add_option( '-f', '--fasta', dest='fasta', default=None, help='A fasta file containing peptide sequences' )
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117 parser.add_option( '-m', '--mzid', dest='mzid', default=None, help='A mxIdentML file containing peptide sequences' )
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118 parser.add_option( '-p', '--pepxml', dest='pepxml', default=None, help='A pepxml file containing peptide sequences' )
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119 # Unipept Flags
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120 parser.add_option( '-e', '--equate_il', dest='equate_il', action='store_true', default=False, help='isoleucine (I) and leucine (L) are equated when matching tryptic peptides to UniProt records' )
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121 parser.add_option( '-x', '--extra', dest='extra', action='store_true', default=False, help='return the complete lineage of the taxonomic lowest common ancestor' )
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122 parser.add_option( '-n', '--names', dest='names', action='store_true', default=False, help='return the names of all ranks in the lineage of the taxonomic lowest common ancestor' )
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123 # output fields
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124 parser.add_option( '-A', '--allfields', dest='allfields', action='store_true', default=False, help='inlcude fields: taxon_rank,taxon_id,taxon_name csv and tsv outputs' )
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125 # Warn vs Error Flag
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126 parser.add_option( '-S', '--strict', dest='strict', action='store_true', default=False, help='Print exit on invalid peptide' )
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127 # output files
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128 parser.add_option( '-J', '--json', dest='json', default=None, help='Output file path for json formatted results')
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129 parser.add_option( '-T', '--tsv', dest='tsv', default=None, help='Output file path for TAB-separated-values (.tsv) formatted results')
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130 parser.add_option( '-C', '--csv', dest='csv', default=None, help='Output file path for Comma-separated-values (.csv) formatted results')
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131 parser.add_option( '-U', '--unmatched', dest='unmatched', default=None, help='Output file path for peptide with no matches' )
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132 # debug
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133 parser.add_option( '-d', '--debug', dest='debug', action='store_true', default=False, help='Turning on debugging' )
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134 parser.add_option( '-v', '--version', dest='version', action='store_true', default=False, help='pring version and exit' )
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135 (options, args) = parser.parse_args()
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136 if options.version:
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137 print >> sys.stdout,"%s" % version
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138 sys.exit(0)
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139 invalid_ec = 2 if options.strict else None
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140 peptides = []
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141 ## Get peptide sequences
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142 if options.mzid:
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143 peptides += read_mzid(options.mzid)
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144 if options.pepxml:
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145 peptides += read_pepxml(options.pepxml)
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146 if options.tabular:
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147 peptides += read_tabular(options.tabular,options.column)
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148 if options.fasta:
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149 peptides += read_fasta(options.fasta)
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150 if args and len(args) > 0:
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151 for i,peptide in enumerate(args):
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152 if not re.match(pep_pat,peptide):
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153 warn_err('"%s" is not a peptide (arg %d)\n' % (peptide,i),exit_code=invalid_ec)
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154 peptides.append(peptide)
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155 if len(peptides) < 1:
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156 warn_err("No peptides input!",exit_code=1)
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157 column_order = pept2lca_column_order
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158 if options.unipept == 'pept2prot':
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159 column_order = pept2prot_extra_column_order if options.extra else pept2prot_column_order
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160 else:
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161 if options.extra or options.names:
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162 column_order = pept2lca_all_column_order if options.allfields else pept2lca_extra_column_order
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163 else:
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164 column_order = pept2lca_column_order
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165 ## map to tryptic peptides
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166 pepToParts = {p: re.split("\n", re.sub(r'(?<=[RK])(?=[^P])','\n', p)) for p in peptides}
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167 partToPeps = {}
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168 for peptide, parts in pepToParts.iteritems():
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169 if options.debug: print >> sys.stdout, "peptide: %s\ttryptic: %s\n" % (peptide, parts)
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170 for part in parts:
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171 if len(part) > 50:
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172 warn_err("peptide: %s tryptic fragment len %d > 50 for %s\n" % (peptide,len(part),part),exit_code=None)
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173 if 5 <= len(part) <= 50:
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174 partToPeps.setdefault(part,[]).append(peptide)
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175 trypticPeptides = partToPeps.keys()
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176 ## unipept
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177 post_data = []
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178 if options.equate_il:
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179 post_data.append(("equate_il","true"))
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180 if options.names:
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181 post_data.append(("extra","true"))
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182 post_data.append(("names","true"))
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183 elif options.extra:
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184 post_data.append(("extra","true"))
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185 post_data += [('input[]', x) for x in trypticPeptides]
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186 headers = {'Content-Type': 'application/x-www-form-urlencoded', 'Accept': 'application/json'}
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187 url = 'http://api.unipept.ugent.be/api/v1/%s' % options.unipept
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188 req = urllib2.Request( url, headers = headers, data = urllib.urlencode(post_data) )
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189 unipept_resp = json.loads( urllib2.urlopen( req ).read() )
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190 unmatched_peptides = []
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191 peptideMatches = []
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192 if options.debug: print >> sys.stdout,"unipept response: %s\n" % str(unipept_resp)
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193 if options.unipept == 'pept2prot' or options.unipept == 'pept2taxa':
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194 dupkey = 'uniprot_id' if options.unipept == 'pept2prot' else 'taxon_id' ## should only keep one of these per input peptide
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195 ## multiple entries per trypticPeptide for pep2prot or pep2taxa
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196 mapping = {}
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197 for match in unipept_resp:
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198 mapping.setdefault(match['peptide'],[]).append(match)
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199 for peptide in peptides:
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200 # Get the intersection of matches to the tryptic parts
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201 keyToMatch = None
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202 for part in pepToParts[peptide]:
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parents: 0
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203 if part in mapping:
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204 temp = {match[dupkey] : match for match in mapping[part]}
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205 if keyToMatch:
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206 dkeys = set(keyToMatch.keys()) - set(temp.keys())
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207 for k in dkeys:
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208 del keyToMatch[k]
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209 else:
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210 keyToMatch = temp
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211 ## keyToMatch = keyToMatch.fromkeys([x for x in keyToMatch if x in temp]) if keyToMatch else temp
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parents: 0
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212 if not keyToMatch:
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213 unmatched_peptides.append(peptide)
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parents: 0
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214 else:
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215 for key,match in keyToMatch.iteritems():
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216 match['tryptic_peptide'] = match['peptide']
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217 match['peptide'] = peptide
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218 peptideMatches.append(match)
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parents: 0
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219 else:
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220 ## should be one response per trypticPeptide for pep2lca
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221 respMap = {v['peptide']:v for v in unipept_resp}
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parents: 0
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222 ## map resp back to peptides
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parents: 0
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223 for peptide in peptides:
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224 matches = list()
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parents: 0
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225 for part in pepToParts[peptide]:
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parents: 0
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226 if part in respMap:
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parents: 0
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227 matches.append(respMap[part])
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parents: 0
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228 match = best_match(peptide,matches)
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parents: 0
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229 if not match:
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230 unmatched_peptides.append(peptide)
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parents: 0
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231 longest_tryptic_peptide = sorted(pepToParts[peptide], key=lambda x: len(x))[-1]
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parents: 0
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232 match = {'peptide' : longest_tryptic_peptide}
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parents: 0
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233 match['tryptic_peptide'] = match['peptide']
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parents: 0
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234 match['peptide'] = peptide
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parents: 0
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235 peptideMatches.append(match)
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parents: 0
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236 resp = peptideMatches
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parents: 0
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237 if options.debug: print >> sys.stdout,"\nmapped response: %s\n" % str(resp)
0
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parents:
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238 ## output results
1
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parents: 0
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239 if not (options.unmatched or options.json or options.tsv or options.csv):
0
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parents:
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240 print >> sys.stdout, str(resp)
1
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parents: 0
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241 if options.unmatched:
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parents: 0
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242 with open(options.unmatched,'w') as outputFile:
0
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parents:
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243 for peptide in peptides:
1
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parents: 0
diff changeset
244 if peptide in unmatched_peptides:
0
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parents:
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245 outputFile.write("%s\n" % peptide)
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parents:
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246 if options.json:
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parents:
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247 with open(options.json,'w') as outputFile:
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parents:
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248 outputFile.write(str(resp))
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parents:
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249 if options.tsv or options.csv:
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parents:
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250 # 'pept2lca','pept2taxa','pept2prot'
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parents:
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251 found_keys = set()
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parents:
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252 results = []
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parents:
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253 for i,pdict in enumerate(resp):
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parents:
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254 results.append(pdict)
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parents:
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255 found_keys |= set(pdict.keys())
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parents:
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256 # print >> sys.stderr, "%s\n%s" % (pdict.keys(),found_keys)
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parents:
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257 column_names = []
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parents:
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258 column_keys = []
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parents:
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259 for col in column_order:
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parents:
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260 if col in found_keys:
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parents:
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261 column_names.append(col)
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parents:
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262 column_keys.append(col)
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parents:
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263 elif options.extra or options.names:
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parents:
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264 col_id = col+'_id'
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parents:
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265 col_name = col+'_name'
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parents:
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266 if options.extra:
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parents:
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267 if col_id in found_keys:
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parents:
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268 column_names.append(col_id)
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parents:
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269 column_keys.append(col_id)
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parents:
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270 if options.names:
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parents:
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271 if col_name in found_keys:
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parents:
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272 column_names.append(col)
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parents:
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273 column_keys.append(col_name)
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parents:
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274 else:
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parents:
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275 if col+'_name' in found_keys:
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parents:
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276 column_names.append(col)
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parents:
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277 column_keys.append(col+'_name')
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parents:
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278 elif col+'_id' in found_keys:
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parents:
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279 column_names.append(col)
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parents:
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280 column_keys.append(col+'_id')
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parents:
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281 # print >> sys.stderr, "%s\n%s" % (column_names,column_keys)
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282 taxa = []
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parents:
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283 for i,pdict in enumerate(results):
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parents:
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284 vals = [str(pdict[x]) if x in pdict and pdict[x] else '' for x in column_keys]
1
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parents: 0
diff changeset
285 if vals not in taxa:
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parents: 0
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286 taxa.append(vals)
0
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parents:
diff changeset
287 if options.tsv:
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parents:
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288 with open(options.tsv,'w') as outputFile:
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parents:
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289 outputFile.write("#%s\n"% '\t'.join(column_names))
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parents:
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290 for vals in taxa:
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parents:
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291 outputFile.write("%s\n"% '\t'.join(vals))
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parents:
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292 if options.csv:
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parents:
diff changeset
293 with open(options.csv,'w') as outputFile:
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parents:
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294 outputFile.write("%s\n"% ','.join(column_names))
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parents:
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295 for vals in taxa:
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parents:
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296 outputFile.write("%s\n"% ','.join(['"%s"' % (v if v else '') for v in vals]))
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parents:
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297
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parents:
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298 if __name__ == "__main__" : __main__()