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annotate unipept.py @ 4:4953dcd7dd39 draft

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planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
author galaxyp
date Wed, 23 Jan 2019 09:16:38 -0500
parents 34758ab8aaa4
children 917fd3ebc223
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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
4
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24
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25 """
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26 pept2taxa json
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27 pept2lca json
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28 pept2prot
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29 pept2ec ecjson ec
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30 pept2go go
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31 pept2funct go ec
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32 peptinfo json ecjson ec go
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34 """
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35
0
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36 try:
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37 import xml.etree.cElementTree as ET
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38 except ImportError:
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39 import xml.etree.ElementTree as ET
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40
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41 def warn_err(msg,exit_code=1):
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42 sys.stderr.write(msg)
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43 if exit_code:
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44 sys.exit(exit_code)
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45
4
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46 go_types = ['biological process', 'molecular function', 'cellular component']
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47 ec_name_dict = {
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48 '1' : 'Oxidoreductase',
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49 '1.1' : 'act on the CH-OH group of donors',
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50 '1.2' : 'act on the aldehyde or oxo group of donors',
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51 '1.3' : 'act on the CH-CH group of donors',
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52 '1.4' : 'act on the CH-NH2 group of donors',
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53 '1.5' : 'act on CH-NH group of donors',
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54 '1.6' : 'act on NADH or NADPH',
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55 '1.7' : 'act on other nitrogenous compounds as donors',
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56 '1.8' : 'act on a sulfur group of donors',
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57 '1.9' : 'act on a heme group of donors',
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58 '1.10' : 'act on diphenols and related substances as donors',
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59 '1.11' : 'act on peroxide as an acceptor -- peroxidases',
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60 '1.12' : 'act on hydrogen as a donor',
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61 '1.13' : 'act on single donors with incorporation of molecular oxygen',
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62 '1.14' : 'act on paired donors with incorporation of molecular oxygen',
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63 '1.15' : 'act on superoxide radicals as acceptors',
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64 '1.16' : 'oxidize metal ions',
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65 '1.17' : 'act on CH or CH2 groups',
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66 '1.18' : 'act on iron-sulfur proteins as donors',
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67 '1.19' : 'act on reduced flavodoxin as donor',
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68 '1.20' : 'act on phosphorus or arsenic as donors',
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69 '1.21' : 'act on X-H and Y-H to form an X-Y bond',
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70 '1.97' : 'other oxidoreductases',
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71 '2' : 'Transferase',
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72 '2.1' : 'transfer one-carbon groups, Methylase',
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73 '2.2' : 'transfer aldehyde or ketone groups',
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74 '2.3' : 'acyltransferases',
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75 '2.4' : 'glycosyltransferases',
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76 '2.5' : 'transfer alkyl or aryl groups, other than methyl groups',
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77 '2.6' : 'transfer nitrogenous groups',
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78 '2.7' : 'transfer phosphorus-containing groups',
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79 '2.8' : 'transfer sulfur-containing groups',
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80 '2.9' : 'transfer selenium-containing groups',
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81 '3' : 'Hydrolase',
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82 '3.1' : 'act on ester bonds',
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83 '3.2' : 'act on sugars - glycosylases',
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84 '3.3' : 'act on ether bonds',
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85 '3.4' : 'act on peptide bonds - Peptidase',
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86 '3.5' : 'act on carbon-nitrogen bonds, other than peptide bonds',
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87 '3.6' : 'act on acid anhydrides',
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88 '3.7' : 'act on carbon-carbon bonds',
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89 '3.8' : 'act on halide bonds',
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90 '3.9' : 'act on phosphorus-nitrogen bonds',
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91 '3.10' : 'act on sulfur-nitrogen bonds',
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92 '3.11' : 'act on carbon-phosphorus bonds',
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93 '3.12' : 'act on sulfur-sulfur bonds',
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94 '3.13' : 'act on carbon-sulfur bonds',
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95 '4' : 'Lyase',
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96 '4.1' : 'carbon-carbon lyases',
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97 '4.2' : 'carbon-oxygen lyases',
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98 '4.3' : 'carbon-nitrogen lyases',
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99 '4.4' : 'carbon-sulfur lyases',
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100 '4.5' : 'carbon-halide lyases',
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101 '4.6' : 'phosphorus-oxygen lyases',
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102 '5' : 'Isomerase',
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103 '5.1' : 'racemases and epimerases',
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104 '5.2' : 'cis-trans-isomerases',
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105 '5.3' : 'intramolecular oxidoreductases',
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106 '5.4' : 'intramolecular transferases -- mutases',
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107 '5.5' : 'intramolecular lyases',
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108 '5.99' : 'other isomerases',
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109 '6' : 'Ligase',
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110 '6.1' : 'form carbon-oxygen bonds',
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111 '6.2' : 'form carbon-sulfur bonds',
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112 '6.3' : 'form carbon-nitrogen bonds',
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113 '6.4' : 'form carbon-carbon bonds',
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114 '6.5' : 'form phosphoric ester bonds',
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115 '6.6' : 'form nitrogen-metal bonds',
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116 }
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117 pept2lca_column_order = ['peptide','taxon_rank','taxon_id','taxon_name']
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118 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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119 pept2lca_all_column_order = pept2lca_column_order + pept2lca_extra_column_order[1:]
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120 pept2prot_column_order = ['peptide','uniprot_id','taxon_id']
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121 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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122 pept2ec_column_order = [['peptide', 'total_protein_count'], ['ec_number', 'protein_count']]
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123 pept2ec_extra_column_order = [['peptide', 'total_protein_count'], ['ec_number', 'protein_count', 'name']]
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124 pept2go_column_order = [['peptide', 'total_protein_count'], ['go_term', 'protein_count']]
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125 pept2go_extra_column_order = [['peptide', 'total_protein_count'], ['go_term', 'protein_count', 'name']]
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126 pept2funct_column_order = ['peptide', 'total_protein_count', 'ec', 'go']
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127
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128 def __main__():
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129 version = '2.0'
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130 pep_pat = '^([ABCDEFGHIKLMNPQRSTVWXYZ]+)$'
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131
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132 def read_tabular(filepath,col):
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133 peptides = []
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134 with open(filepath) as fp:
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135 for i,line in enumerate(fp):
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136 if line.strip() == '' or line.startswith('#'):
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137 continue
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138 fields = line.rstrip('\n').split('\t')
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139 peptide = fields[col]
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140 if not re.match(pep_pat,peptide):
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141 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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142 peptides.append(peptide)
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143 return peptides
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144
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145 def get_fasta_entries(fp):
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146 name, seq = None, []
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147 for line in fp:
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148 line = line.rstrip()
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149 if line.startswith(">"):
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150 if name: yield (name, ''.join(seq))
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151 name, seq = line, []
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152 else:
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153 seq.append(line)
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154 if name: yield (name, ''.join(seq))
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155
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156 def read_fasta(filepath):
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157 peptides = []
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158 with open(filepath) as fp:
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159 for id, peptide in get_fasta_entries(fp):
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160 if not re.match(pep_pat,peptide):
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161 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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162 peptides.append(peptide)
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163 return peptides
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164
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165 def read_mzid(fp):
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166 peptides = []
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167 for event, elem in ET.iterparse(fp):
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168 if event == 'end':
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169 if re.search('PeptideSequence',elem.tag):
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170 peptides.append(elem.text)
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171 return peptides
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172
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173 def read_pepxml(fp):
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174 peptides = []
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175 for event, elem in ET.iterparse(fp):
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176 if event == 'end':
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177 if re.search('search_hit',elem.tag):
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178 peptides.append(elem.get('peptide'))
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179 return peptides
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180
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181 def best_match(peptide,matches):
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182 if not matches:
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183 return None
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184 elif len(matches) == 1:
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185 return matches[0].copy()
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186 elif 'taxon_rank' in matches[0]:
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187 # find the most specific match (peptide is always the first column order field)
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188 for col in reversed(pept2lca_extra_column_order[1:]):
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189 col_id = col+"_id" if options.extra else col
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190 for match in matches:
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191 if 'taxon_rank' in match and match['taxon_rank'] == col:
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192 return match.copy()
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193 if col_id in match and match[col_id]:
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194 return match.copy()
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195 else:
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196 return sorted(matches, key=lambda x: len(x['peptide']))[-1].copy()
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197 return None
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198
4
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199 def get_taxon_json(resp):
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200 found_keys = set()
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201 for i,pdict in enumerate(resp):
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202 found_keys |= set(pdict.keys())
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203 taxa_cols = []
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204 for col in pept2lca_extra_column_order[-1:0:-1]:
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205 if col+'_id' in found_keys:
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206 taxa_cols.append(col)
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207 id_to_node = dict()
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208 def get_node(id,name,rank,child,seq):
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209 if id not in id_to_node:
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210 data = {'count' : 0, 'self_count' : 0, 'valid_taxon' : 1, 'rank' : rank, 'sequences' : [] }
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211 node = {'id' : id, 'name' : name, 'children' : [], 'kids': [],'data' : data }
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212 id_to_node[id] = node
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213 else:
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214 node = id_to_node[id]
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215 node['data']['count'] += 1
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216 if seq is not None and seq not in node['data']['sequences']:
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217 node['data']['sequences'].append(seq)
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218 if child is None:
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219 node['data']['self_count'] += 1
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220 elif child['id'] not in node['kids']:
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221 node['kids'].append(child['id'])
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222 node['children'].append(child)
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223 return node
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224 root = get_node(1,'root','no rank',None,None)
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225 for i,pdict in enumerate(resp):
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226 sequence = pdict.get('peptide',pdict.get('tryptic_peptide',None))
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227 seq = sequence
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228 child = None
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229 for col in taxa_cols:
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230 col_id = col+'_id'
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231 if col_id in pdict and pdict.get(col_id):
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232 col_name = col if col in found_keys else col+'_name'
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233 child = get_node(pdict.get(col_id,None),pdict.get(col_name,''),col,child,seq)
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234 seq = None
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235 if child:
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236 get_node(1,'root','no rank',child,None)
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237 return root
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238
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239 def get_ec_json(resp):
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240 ecMap = dict()
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241 for pdict in resp:
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242 if 'ec' in pdict:
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243 for ec in pdict['ec']:
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244 ec_number = ec['ec_number']
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245 if ec_number not in ecMap:
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246 ecMap[ec_number] = []
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247 ecMap[ec_number].append(pdict)
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248 def get_ids(ec):
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249 ids = []
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250 i = len(ec)
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251 while i >= 0:
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252 ids.append(ec[:i])
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253 i = ec.rfind('.',0,i - 1)
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254 return ids
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255 id_to_node = dict()
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256 def get_node(id,name,child,seq):
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257 if id not in id_to_node:
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258 data = {'count' : 0, 'self_count' : 0, 'sequences' : [] }
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259 node = {'id' : id, 'name' : name, 'children' : [], 'kids': [],'data' : data }
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260 id_to_node[id] = node
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261 else:
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262 node = id_to_node[id]
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263 node['data']['count'] += 1
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264 if seq is not None and seq not in node['data']['sequences']:
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265 node['data']['sequences'].append(seq)
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266 if child is None:
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267 node['data']['self_count'] += 1
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268 elif child['id'] not in node['kids']:
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269 node['kids'].append(child['id'])
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270 node['children'].append(child)
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271 return node
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272 root = get_node(0,'-.-.-.-',None,None)
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273 for i in range(1,7):
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274 child = get_node(str(i),'%s\n%s' %(str(i), ec_name_dict[str(i)] ),None,None)
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275 get_node(0,'-.-.-.-',child,None)
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276 for i,pdict in enumerate(resp):
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277 sequence = pdict.get('peptide',pdict.get('tryptic_peptide',None))
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278 seq = sequence
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279 if 'ec' in pdict:
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280 for ec in pdict['ec']:
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281 child = None
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282 protein_count = ec['protein_count']
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283 ec_number = ec['ec_number']
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284 for ec_id in get_ids(ec_number):
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285 ec_name = str(ec_id)
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286 ## if len(ec_id) == 3:
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287 ## ec_name = '%s\n%s\n%s' %(str(ec_id), ec_name_dict[str(ec_id[0])], ec_name_dict[str(ec_id)])
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288 child = get_node(ec_id,ec_name,child,seq)
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289 seq = None
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290 if child:
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291 get_node(0,'-.-.-.-',child,None)
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292 return root
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293
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294 def get_taxon_dict(resp, column_order, extra=False, names=False):
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295 found_keys = set()
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296 results = []
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297 for i,pdict in enumerate(resp):
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298 results.append(pdict)
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299 found_keys |= set(pdict.keys())
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300 # print >> sys.stderr, "%s\n%s" % (pdict.keys(),found_keys)
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301 column_names = []
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302 column_keys = []
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303 for col in column_order:
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304 if col in found_keys:
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305 column_names.append(col)
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306 column_keys.append(col)
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307 elif names:
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308 col_id = col+'_id'
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309 col_name = col+'_name'
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310 if extra:
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311 if col_id in found_keys:
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312 column_names.append(col_id)
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313 column_keys.append(col_id)
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314 if names:
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315 if col_name in found_keys:
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316 column_names.append(col)
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317 column_keys.append(col_name)
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318 else:
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319 if col+'_name' in found_keys:
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320 column_names.append(col)
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321 column_keys.append(col+'_name')
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322 elif col+'_id' in found_keys:
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323 column_names.append(col)
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324 column_keys.append(col+'_id')
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325 # print >> sys.stderr, "%s\n%s" % (column_names,column_keys)
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326 taxa = dict() ## peptide : [taxonomy]
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327 for i,pdict in enumerate(results):
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328 peptide = pdict['peptide'] if 'peptide' in pdict else None
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329 if peptide and peptide not in taxa:
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330 vals = [str(pdict[x]) if x in pdict and pdict[x] else '' for x in column_keys]
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331 taxa[peptide] = vals
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332 return (taxa,column_names)
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333
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334 def get_ec_dict(resp, extra=False):
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335 ec_cols = ['ec_numbers', 'ec_protein_counts']
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336 if extra:
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337 ec_cols.append('ec_names')
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338 ec_dict = dict()
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339 for i,pdict in enumerate(resp):
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340 peptide = pdict['peptide']
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341 ec_numbers = []
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342 protein_counts = []
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343 ec_names = []
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344 if 'ec' in pdict:
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345 for ec in pdict['ec']:
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346 ec_numbers.append(ec['ec_number'])
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347 protein_counts.append(str(ec['protein_count']))
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348 if extra:
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349 ec_names.append(ec['name'] if 'name' in ec else '')
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350 vals = [','.join(ec_numbers),','.join(protein_counts)]
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351 if extra:
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352 vals.append(','.join(ec_names))
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353 ec_dict[peptide] = vals
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354 return (ec_dict, ec_cols)
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355
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356 def get_go_dict(resp, extra=False):
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357 go_cols = ['go_terms', 'go_protein_counts']
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358 if extra:
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359 go_cols.append('go_names')
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360 go_dict = dict()
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361 for i,pdict in enumerate(resp):
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362 peptide = pdict['peptide']
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363 go_terms = []
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364 protein_counts = []
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365 go_names = []
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366 if 'go' in pdict:
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367 for go in pdict['go']:
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368 if 'go_term' in go:
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369 go_terms.append(go['go_term'])
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370 protein_counts.append(str(go['protein_count']))
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371 if extra:
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372 go_names.append(go['name'] if 'name' in go else '')
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373 else:
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374 for go_type in go_types:
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375 if go_type in go:
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376 for _go in go[go_type]:
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377 go_terms.append(_go['go_term'])
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378 protein_counts.append(str(_go['protein_count']))
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379 if extra:
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380 go_names.append(_go['name'] if 'name' in _go else '')
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381 vals = [','.join(go_terms),','.join(protein_counts)]
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382 if extra:
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383 vals.append(','.join(go_names))
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384 go_dict[peptide] = vals
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385 return (go_dict, go_cols)
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386
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387 def write_ec_table(outfile, resp, column_order):
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388 with open(outfile,'w') as fh:
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389 for i,pdict in enumerate(resp):
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390 if 'ec' in pdict:
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391 tvals = [str(pdict[x]) if x in pdict and pdict[x] else '' for x in column_order[0]]
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392 for ec in pdict['ec']:
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393 vals = [str(ec[x]) if x in ec and ec[x] else '' for x in column_order[-1]]
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394 fh.write('%s\n' % '\t'.join(tvals + vals))
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395
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396 def write_go_table(outfile, resp, column_order):
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397 with open(outfile,'w') as fh:
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398 for i,pdict in enumerate(resp):
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399 if 'go' in pdict:
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400 tvals = [str(pdict[x]) if x in pdict and pdict[x] else '' for x in column_order[0]]
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401 for go in pdict['go']:
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402 if 'go_term' in go:
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403 vals = [str(go[x]) if x in go and go[x] else '' for x in column_order[-1]]
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404 fh.write('%s\n' % '\t'.join(tvals + vals))
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405 else:
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406 for go_type in go_types:
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407 if go_type in go:
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408 for _go in go[go_type]:
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409 vals = [str(_go[x]) if x in _go and _go[x] else '' for x in column_order[-1]]
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410 vals.append(go_type)
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411 fh.write('%s\n' % '\t'.join(tvals + vals))
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412
0
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413 #Parse Command Line
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414 parser = optparse.OptionParser()
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415 # unipept API choice
4
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416 parser.add_option( '-a', '--api', dest='unipept', default='pept2lca', choices=['pept2lca','pept2taxa','pept2prot', 'pept2ec', 'pept2go', 'pept2funct', 'peptinfo'],
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417 help='The unipept application: pept2lca, pept2taxa, pept2prot, pept2ec, pept2go, pept2funct, or peptinfo' )
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418 # input files
0
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419 parser.add_option( '-t', '--tabular', dest='tabular', default=None, help='A tabular file that contains a peptide column' )
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420 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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421 parser.add_option( '-f', '--fasta', dest='fasta', default=None, help='A fasta file containing peptide sequences' )
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422 parser.add_option( '-m', '--mzid', dest='mzid', default=None, help='A mxIdentML file containing peptide sequences' )
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423 parser.add_option( '-p', '--pepxml', dest='pepxml', default=None, help='A pepxml file containing peptide sequences' )
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424 # Unipept Flags
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425 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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426 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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427 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' )
4
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428 parser.add_option( '-D', '--domains', dest='domains', action='store_true', default=False, help='group response by GO namaspace: biological process, molecular function, cellular component' )
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429 parser.add_option( '-M', '--max_request', dest='max_request', type='int', default=200, help='The maximum number of entries per unipept request' )
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430
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431 # output fields
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432 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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433 # Warn vs Error Flag
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434 parser.add_option( '-S', '--strict', dest='strict', action='store_true', default=False, help='Print exit on invalid peptide' )
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435 # output files
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436 parser.add_option( '-J', '--json', dest='json', default=None, help='Output file path for json formatted results')
4
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437 parser.add_option( '-j', '--ec_json', dest='ec_json', default=None, help='Output file path for json formatted results')
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438 parser.add_option( '-E', '--ec_tsv', dest='ec_tsv', default=None, help='Output file path for EC TAB-separated-values (.tsv) formatted results')
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439 parser.add_option( '-G', '--go_tsv', dest='go_tsv', default=None, help='Output file path for GO TAB-separated-values (.tsv) formatted results')
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440 parser.add_option( '-L', '--lineage_tsv', dest='lineage_tsv', default=None, help='Output file path for Lineage TAB-separated-values (.tsv) formatted results')
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441 parser.add_option( '-T', '--tsv', dest='tsv', default=None, help='Output file path for TAB-separated-values (.tsv) formatted results')
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442 parser.add_option( '-C', '--csv', dest='csv', default=None, help='Output file path for Comma-separated-values (.csv) formatted results')
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443 parser.add_option( '-U', '--unmatched', dest='unmatched', default=None, help='Output file path for peptide with no matches' )
4
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444 parser.add_option( '-u', '--url', dest='url', default='http://api.unipept.ugent.be/api/v1/', help='unipept url http://api.unipept.ugent.be/api/v1/' )
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445 # debug
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446 parser.add_option( '-g', '--get', dest='get', action='store_true', default=False, help='Use GET instead of POST' )
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447 parser.add_option( '-d', '--debug', dest='debug', action='store_true', default=False, help='Turning on debugging' )
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448 parser.add_option( '-v', '--version', dest='version', action='store_true', default=False, help='pring version and exit' )
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449 (options, args) = parser.parse_args()
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450 if options.version:
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451 print >> sys.stdout,"%s" % version
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452 sys.exit(0)
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parents:
diff changeset
453 invalid_ec = 2 if options.strict else None
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galaxyp
parents:
diff changeset
454 peptides = []
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galaxyp
parents:
diff changeset
455 ## Get peptide sequences
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galaxyp
parents:
diff changeset
456 if options.mzid:
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galaxyp
parents:
diff changeset
457 peptides += read_mzid(options.mzid)
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galaxyp
parents:
diff changeset
458 if options.pepxml:
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galaxyp
parents:
diff changeset
459 peptides += read_pepxml(options.pepxml)
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galaxyp
parents:
diff changeset
460 if options.tabular:
1
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parents: 0
diff changeset
461 peptides += read_tabular(options.tabular,options.column)
0
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galaxyp
parents:
diff changeset
462 if options.fasta:
1
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galaxyp
parents: 0
diff changeset
463 peptides += read_fasta(options.fasta)
0
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galaxyp
parents:
diff changeset
464 if args and len(args) > 0:
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galaxyp
parents:
diff changeset
465 for i,peptide in enumerate(args):
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galaxyp
parents:
diff changeset
466 if not re.match(pep_pat,peptide):
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galaxyp
parents:
diff changeset
467 warn_err('"%s" is not a peptide (arg %d)\n' % (peptide,i),exit_code=invalid_ec)
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galaxyp
parents:
diff changeset
468 peptides.append(peptide)
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galaxyp
parents:
diff changeset
469 if len(peptides) < 1:
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galaxyp
parents:
diff changeset
470 warn_err("No peptides input!",exit_code=1)
1
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galaxyp
parents: 0
diff changeset
471 column_order = pept2lca_column_order
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
472 if options.unipept == 'pept2prot':
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galaxyp
parents: 0
diff changeset
473 column_order = pept2prot_extra_column_order if options.extra else pept2prot_column_order
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galaxyp
parents: 0
diff changeset
474 else:
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galaxyp
parents: 0
diff changeset
475 if options.extra or options.names:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
476 column_order = pept2lca_all_column_order if options.allfields else pept2lca_extra_column_order
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galaxyp
parents: 0
diff changeset
477 else:
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galaxyp
parents: 0
diff changeset
478 column_order = pept2lca_column_order
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galaxyp
parents: 0
diff changeset
479 ## map to tryptic peptides
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galaxyp
parents: 0
diff changeset
480 pepToParts = {p: re.split("\n", re.sub(r'(?<=[RK])(?=[^P])','\n', p)) for p in peptides}
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galaxyp
parents: 0
diff changeset
481 partToPeps = {}
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galaxyp
parents: 0
diff changeset
482 for peptide, parts in pepToParts.iteritems():
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galaxyp
parents: 0
diff changeset
483 if options.debug: print >> sys.stdout, "peptide: %s\ttryptic: %s\n" % (peptide, parts)
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galaxyp
parents: 0
diff changeset
484 for part in parts:
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galaxyp
parents: 0
diff changeset
485 if len(part) > 50:
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galaxyp
parents: 0
diff changeset
486 warn_err("peptide: %s tryptic fragment len %d > 50 for %s\n" % (peptide,len(part),part),exit_code=None)
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galaxyp
parents: 0
diff changeset
487 if 5 <= len(part) <= 50:
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galaxyp
parents: 0
diff changeset
488 partToPeps.setdefault(part,[]).append(peptide)
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galaxyp
parents: 0
diff changeset
489 trypticPeptides = partToPeps.keys()
0
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galaxyp
parents:
diff changeset
490 ## unipept
3
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galaxyp
parents: 1
diff changeset
491 unipept_resp = []
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galaxyp
parents: 1
diff changeset
492 idx = range(0,len(trypticPeptides),options.max_request)
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galaxyp
parents: 1
diff changeset
493 idx.append(len(trypticPeptides))
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galaxyp
parents: 1
diff changeset
494 for i in range(len(idx)-1):
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galaxyp
parents: 1
diff changeset
495 post_data = []
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galaxyp
parents: 1
diff changeset
496 if options.equate_il:
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galaxyp
parents: 1
diff changeset
497 post_data.append(("equate_il","true"))
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galaxyp
parents: 1
diff changeset
498 if options.names or options.json:
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galaxyp
parents: 1
diff changeset
499 post_data.append(("extra","true"))
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galaxyp
parents: 1
diff changeset
500 post_data.append(("names","true"))
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galaxyp
parents: 1
diff changeset
501 elif options.extra or options.json:
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galaxyp
parents: 1
diff changeset
502 post_data.append(("extra","true"))
4
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galaxyp
parents: 3
diff changeset
503 if options.domains:
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galaxyp
parents: 3
diff changeset
504 post_data.append(("domains","true"))
3
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parents: 1
diff changeset
505 post_data += [('input[]', x) for x in trypticPeptides[idx[i]:idx[i+1]]]
4
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galaxyp
parents: 3
diff changeset
506 if options.debug: print >> sys.stdout, "post_data: %s\n" % (str(post_data))
3
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galaxyp
parents: 1
diff changeset
507 headers = {'Content-Type': 'application/x-www-form-urlencoded', 'Accept': 'application/json'}
4
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galaxyp
parents: 3
diff changeset
508 ## headers = {'Accept': 'application/json'}
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galaxyp
parents: 3
diff changeset
509 url = '%s/%s' % (options.url.rstrip('/'),options.unipept)
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galaxyp
parents: 3
diff changeset
510 if options.get:
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galaxyp
parents: 3
diff changeset
511 params = '&'.join(['%s=%s' % (i[0],i[1]) for i in post_data])
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
512 url = '%s.json?%s' % (url,params)
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galaxyp
parents: 3
diff changeset
513 req = urllib2.Request( url )
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galaxyp
parents: 3
diff changeset
514 else:
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galaxyp
parents: 3
diff changeset
515 url = '%s.json' % (url)
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galaxyp
parents: 3
diff changeset
516 req = urllib2.Request( url, headers = headers, data = urllib.urlencode(post_data) )
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
517 if options.debug: print >> sys.stdout, "url: %s\n" % (str(url))
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
518 try:
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
519 resp = urllib2.urlopen( req )
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
520 if options.debug: print >> sys.stdout,"%s %s\n" % (url,str(resp.getcode()))
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
521 if resp.getcode() == 200:
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galaxyp
parents: 3
diff changeset
522 unipept_resp += json.loads( urllib2.urlopen( req ).read() )
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galaxyp
parents: 3
diff changeset
523 except Exception, e:
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galaxyp
parents: 3
diff changeset
524 warn_err('HTTP Error %s\n' % (str(e)),exit_code=None)
1
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
525 unmatched_peptides = []
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
526 peptideMatches = []
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
527 if options.debug: print >> sys.stdout,"unipept response: %s\n" % str(unipept_resp)
4
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galaxyp
parents: 3
diff changeset
528 if options.unipept in ['pept2prot', 'pept2taxa']:
1
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galaxyp
parents: 0
diff changeset
529 dupkey = 'uniprot_id' if options.unipept == 'pept2prot' else 'taxon_id' ## should only keep one of these per input peptide
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galaxyp
parents: 0
diff changeset
530 ## multiple entries per trypticPeptide for pep2prot or pep2taxa
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
531 mapping = {}
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
532 for match in unipept_resp:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
533 mapping.setdefault(match['peptide'],[]).append(match)
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
534 for peptide in peptides:
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galaxyp
parents: 0
diff changeset
535 # Get the intersection of matches to the tryptic parts
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galaxyp
parents: 0
diff changeset
536 keyToMatch = None
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
537 for part in pepToParts[peptide]:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
538 if part in mapping:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
539 temp = {match[dupkey] : match for match in mapping[part]}
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
540 if keyToMatch:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
541 dkeys = set(keyToMatch.keys()) - set(temp.keys())
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galaxyp
parents: 0
diff changeset
542 for k in dkeys:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
543 del keyToMatch[k]
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
544 else:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
545 keyToMatch = temp
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
546 ## keyToMatch = keyToMatch.fromkeys([x for x in keyToMatch if x in temp]) if keyToMatch else temp
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
547 if not keyToMatch:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
548 unmatched_peptides.append(peptide)
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
549 else:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
550 for key,match in keyToMatch.iteritems():
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
551 match['tryptic_peptide'] = match['peptide']
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galaxyp
parents: 0
diff changeset
552 match['peptide'] = peptide
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
553 peptideMatches.append(match)
4
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galaxyp
parents: 3
diff changeset
554 elif options.unipept in ['pept2lca', 'peptinfo']:
1
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
555 ## should be one response per trypticPeptide for pep2lca
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
556 respMap = {v['peptide']:v for v in unipept_resp}
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
557 ## map resp back to peptides
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galaxyp
parents: 0
diff changeset
558 for peptide in peptides:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
559 matches = list()
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
560 for part in pepToParts[peptide]:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
561 if part in respMap:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
562 matches.append(respMap[part])
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
563 match = best_match(peptide,matches)
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
564 if not match:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
565 unmatched_peptides.append(peptide)
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
566 longest_tryptic_peptide = sorted(pepToParts[peptide], key=lambda x: len(x))[-1]
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
567 match = {'peptide' : longest_tryptic_peptide}
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
568 match['tryptic_peptide'] = match['peptide']
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
569 match['peptide'] = peptide
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
570 peptideMatches.append(match)
4
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galaxyp
parents: 3
diff changeset
571 else:
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galaxyp
parents: 3
diff changeset
572 respMap = {v['peptide']:v for v in unipept_resp}
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galaxyp
parents: 3
diff changeset
573 ## map resp back to peptides
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galaxyp
parents: 3
diff changeset
574 for peptide in peptides:
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galaxyp
parents: 3
diff changeset
575 matches = list()
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galaxyp
parents: 3
diff changeset
576 for part in pepToParts[peptide]:
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
577 if part in respMap and 'total_protein_count' in respMap[part]:
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galaxyp
parents: 3
diff changeset
578 matches.append(respMap[part])
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galaxyp
parents: 3
diff changeset
579 match = best_match(peptide,matches)
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galaxyp
parents: 3
diff changeset
580 if not match:
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
581 unmatched_peptides.append(peptide)
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
582 longest_tryptic_peptide = sorted(pepToParts[peptide], key=lambda x: len(x))[-1]
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
583 match = {'peptide' : longest_tryptic_peptide}
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galaxyp
parents: 3
diff changeset
584 match['tryptic_peptide'] = match['peptide']
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
585 match['peptide'] = peptide
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
586 peptideMatches.append(match)
1
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galaxyp
parents: 0
diff changeset
587 resp = peptideMatches
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
588 if options.debug: print >> sys.stdout,"\nmapped response: %s\n" % str(resp)
0
6430407e5869 Uploaded
galaxyp
parents:
diff changeset
589 ## output results
1
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
590 if not (options.unmatched or options.json or options.tsv or options.csv):
0
6430407e5869 Uploaded
galaxyp
parents:
diff changeset
591 print >> sys.stdout, str(resp)
1
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
592 if options.unmatched:
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
593 with open(options.unmatched,'w') as outputFile:
0
6430407e5869 Uploaded
galaxyp
parents:
diff changeset
594 for peptide in peptides:
1
0c1ee95282fa Uploaded
galaxyp
parents: 0
diff changeset
595 if peptide in unmatched_peptides:
0
6430407e5869 Uploaded
galaxyp
parents:
diff changeset
596 outputFile.write("%s\n" % peptide)
6430407e5869 Uploaded
galaxyp
parents:
diff changeset
597 if options.json:
4
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galaxyp
parents: 3
diff changeset
598 if options.unipept in ['pept2lca', 'pept2taxa', 'peptinfo']:
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
599 root = get_taxon_json(resp)
3
34758ab8aaa4 Uploaded
galaxyp
parents: 1
diff changeset
600 with open(options.json,'w') as outputFile:
34758ab8aaa4 Uploaded
galaxyp
parents: 1
diff changeset
601 outputFile.write(json.dumps(root))
4
4953dcd7dd39 planemo upload for repository http://unipept.ugent.be/apidocs commit e91b0fe16bf468b34884508652359b91847d1f95-dirty
galaxyp
parents: 3
diff changeset
602 elif options.unipept in ['pept2prot', 'pept2ec', 'pept2go', 'pept2funct']:
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603 with open(options.json,'w') as outputFile:
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604 outputFile.write(str(resp))
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605 if options.ec_json:
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606 if options.unipept in ['pept2ec', 'pept2funct', 'peptinfo']:
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607 root = get_ec_json(resp)
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608 with open(options.ec_json,'w') as outputFile:
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609 outputFile.write(json.dumps(root))
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610 if options.tsv or options.csv:
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611 rows = []
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612 column_names = None
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613 if options.unipept in ['pept2ec', 'pept2go', 'pept2funct', 'peptinfo']:
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614 taxa = None
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615 ec_dict = None
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616 go_dict = None
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617 if options.unipept in ['peptinfo']:
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618 (taxa,taxon_cols) = get_taxon_dict(resp, column_order, extra=options.extra, names=options.names)
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619 if options.unipept in ['pept2ec', 'pept2funct', 'peptinfo']:
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620 (ec_dict,ec_cols) = get_ec_dict(resp, extra=options.extra)
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621 if options.unipept in ['pept2go', 'pept2funct', 'peptinfo']:
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622 (go_dict,go_cols) = get_go_dict(resp, extra=options.extra)
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623 for i,pdict in enumerate(resp):
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624 peptide = pdict['peptide']
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625 total_protein_count = str(pdict['total_protein_count']) if 'total_protein_count' in pdict else '0'
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626 column_names = ['peptide', 'total_protein_count']
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627 vals = [peptide,total_protein_count]
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628 if ec_dict:
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629 vals += ec_dict[peptide]
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630 column_names += ec_cols
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631 if go_dict:
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632 vals += go_dict[peptide]
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633 column_names += go_cols
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634 if taxa:
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635 vals += taxa[peptide][1:]
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636 column_names += taxon_cols[1:]
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637 rows.append(vals)
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638 elif options.unipept in ['pept2lca', 'pept2taxa', 'pept2prot']:
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639 (taxa,taxon_cols) = get_taxon_dict(resp, column_order, extra=options.extra, names=options.names)
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640 column_names = taxon_cols
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641 rows = taxa.values()
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642 for peptide,vals in taxa.iteritems():
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643 rows.append(vals)
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644 if options.tsv:
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645 with open(options.tsv,'w') as outputFile:
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646 if column_names:
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647 outputFile.write("#%s\n"% '\t'.join(column_names))
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648 for vals in rows:
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649 outputFile.write("%s\n"% '\t'.join(vals))
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650 if options.csv:
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651 with open(options.csv,'w') as outputFile:
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652 if column_names:
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653 outputFile.write("%s\n"% ','.join(column_names))
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654 for vals in rows:
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655 outputFile.write("%s\n"% ','.join(['"%s"' % (v if v else '') for v in vals]))
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656 if options.ec_tsv and options.unipept in ['pept2ec', 'pept2funct', 'peptinfo']:
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657 column_order = pept2ec_extra_column_order if options.extra else pept2ec_column_order
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658 write_ec_table(options.ec_tsv, resp, column_order)
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659 if options.go_tsv and options.unipept in ['pept2go', 'pept2funct', 'peptinfo']:
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660 column_order = pept2go_extra_column_order if options.extra else pept2go_column_order
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661 write_go_table(options.go_tsv, resp, column_order)
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662
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663 if __name__ == "__main__" : __main__()