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annotate metfrag.py @ 2:d040e27b6225 draft

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planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
author tomnl
date Mon, 03 Jun 2019 11:20:55 -0400
parents c1b168770b68
children 5ee936e570a7
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1 from __future__ import absolute_import, print_function
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2 import argparse
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3 import csv
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4 import os
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5 import sys
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6 import six
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7 import re
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8 import random
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9 import string
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10 import shutil
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11 import glob
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12 import tempfile
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13 import multiprocessing
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15 from subprocess import call
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16 from collections import defaultdict
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17
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18 print(sys.version)
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20 parser = argparse.ArgumentParser()
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21 parser.add_argument('--input_pth')
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22 parser.add_argument('--result_pth', default='metfrag_result.csv')
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24 parser.add_argument('--temp_dir')
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25 parser.add_argument('--polarity', default='pos')
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26 parser.add_argument('--minMSMSpeaks', default=1)
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28 parser.add_argument('--MetFragDatabaseType', default='PubChem')
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29 parser.add_argument('--LocalDatabasePath', default='')
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30 parser.add_argument('--LocalMetChemDatabaseServerIp', default='')
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32 parser.add_argument('--DatabaseSearchRelativeMassDeviation', default=5)
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33 parser.add_argument('--FragmentPeakMatchRelativeMassDeviation', default=10)
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34 parser.add_argument('--FragmentPeakMatchAbsoluteMassDeviation', default=0.001)
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35 parser.add_argument('--NumberThreads', default=1)
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36 parser.add_argument('--UnconnectedCompoundFilter', action='store_true')
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37 parser.add_argument('--IsotopeFilter', action='store_true')
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38
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39 parser.add_argument('--FilterMinimumElements', default='')
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40 parser.add_argument('--FilterMaximumElements', default='')
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41 parser.add_argument('--FilterSmartsInclusionList', default='')
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42 parser.add_argument('--FilterSmartsExclusionList', default='')
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43 parser.add_argument('--FilterIncludedElements', default='')
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44 parser.add_argument('--FilterExcludedElements', default='')
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45 parser.add_argument('--FilterIncludedExclusiveElements', default='')
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46
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47 parser.add_argument('--score_thrshld', default=0)
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48 parser.add_argument('--pctexplpeak_thrshld', default=0)
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49 parser.add_argument('--schema')
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50 parser.add_argument('--cores_top_level', default=1)
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51 parser.add_argument('--chunks', default=1)
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52 parser.add_argument('--meta_select_col', default='name')
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53
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54 parser.add_argument('--ScoreSuspectLists', default='')
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55 parser.add_argument('--MetFragScoreTypes', default="FragmenterScore,OfflineMetFusionScore")
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56 parser.add_argument('--MetFragScoreWeights', default="1.0,1.0")
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57
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58 args = parser.parse_args()
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59 print(args)
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61 # Create temporary working directory
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62 if args.temp_dir:
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63 wd = args.temp_dir
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64 else:
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65 wd = tempfile.mkdtemp()
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66
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67 if os.path.exists(wd):
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68 shutil.rmtree(wd)
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69 os.makedirs(wd)
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70 else:
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71 os.makedirs(wd)
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72
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73 ######################################################################
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74 # Setup regular expressions for MSP parsing dictionary
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75 ######################################################################
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76 regex_msp = {}
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77 regex_msp['name'] = ['^Name(?:=|:)(.*)$']
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78 regex_msp['polarity'] = ['^ion.*mode(?:=|:)(.*)$', '^ionization.*mode(?:=|:)(.*)$', '^polarity(?:=|:)(.*)$']
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79 regex_msp['precursor_mz'] = ['^precursor.*m/z(?:=|:)\s*(\d*[.,]?\d*)$', '^precursor.*mz(?:=|:)\s*(\d*[.,]?\d*)$']
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80 regex_msp['precursor_type'] = ['^precursor.*type(?:=|:)(.*)$', '^adduct(?:=|:)(.*)$', '^ADDUCTIONNAME(?:=|:)(.*)$']
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81 regex_msp['num_peaks'] = ['^Num.*Peaks(?:=|:)\s*(\d*)$']
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82 regex_msp['msp'] = ['^Name(?:=|:)(.*)$'] # Flag for standard MSP format
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83
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84 regex_massbank = {}
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85 regex_massbank['name'] = ['^RECORD_TITLE:(.*)$']
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86 regex_massbank['polarity'] = ['^AC\$MASS_SPECTROMETRY:\s+ION_MODE\s+(.*)$']
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87 regex_massbank['precursor_mz'] = ['^MS\$FOCUSED_ION:\s+PRECURSOR_M/Z\s+(\d*[.,]?\d*)$']
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88 regex_massbank['precursor_type'] = ['^MS\$FOCUSED_ION:\s+PRECURSOR_TYPE\s+(.*)$']
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89 regex_massbank['num_peaks'] = ['^PK\$NUM_PEAK:\s+(\d*)']
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90 regex_massbank['cols'] = ['^PK\$PEAK:\s+(.*)']
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91 regex_massbank['massbank'] = ['^RECORD_TITLE:(.*)$'] # Flag for massbank format
0
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92
1
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93 if args.schema == 'msp':
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94 meta_regex = regex_msp
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95 elif args.schema == 'massbank':
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96 meta_regex = regex_massbank
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97 elif args.schema == 'auto':
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98 # If auto we just check for all the available paramter names and then determine if Massbank or MSP based on
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99 # the name parameter
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100 meta_regex = {}
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101 meta_regex.update(regex_massbank)
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102 meta_regex['name'].extend(regex_msp['name'])
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103 meta_regex['polarity'].extend(regex_msp['polarity'])
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104 meta_regex['precursor_mz'].extend(regex_msp['precursor_mz'])
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105 meta_regex['precursor_type'].extend(regex_msp['precursor_type'])
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106 meta_regex['num_peaks'].extend(regex_msp['num_peaks'])
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107 meta_regex['msp'] = regex_msp['msp']
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108
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109 print(meta_regex)
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110
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111 adduct_types = {
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112 '[M+H]+': 1.007276,
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113 '[M+NH4]+': 18.034374,
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114 '[M+Na]+': 22.989218,
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115 '[M+K]+': 38.963158,
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116 '[M+CH3OH+H]+': 33.033489,
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117 '[M+ACN+H]+': 42.033823,
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118 '[M+ACN+Na]+': 64.015765,
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119 '[M+2ACN+H]+': 83.06037,
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120 '[M-H]-': -1.007276,
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121 '[M+Cl]-': 34.969402,
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122 }
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123
2
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124 # function to extract the meta data using the regular expressions
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125 def parse_meta(meta_regex, meta_info={}):
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126 for k, regexes in six.iteritems(meta_regex):
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127 for reg in regexes:
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128 m = re.search(reg, line, re.IGNORECASE)
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129 if m:
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130 meta_info[k] = '-'.join(m.groups()).strip()
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131 return meta_info
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132
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133
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134
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135 ######################################################################
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136 # Setup parameter dictionary
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137 ######################################################################
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138 def init_paramd(args):
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139 paramd = defaultdict()
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140
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141 paramd["MetFragDatabaseType"] = args.MetFragDatabaseType
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142
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143 if args.MetFragDatabaseType == "LocalCSV":
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144 paramd["LocalDatabasePath"] = args.LocalDatabasePath
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145 elif args.MetFragDatabaseType == "MetChem":
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146 paramd["LocalMetChemDatabase"] = "metchem"
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147 paramd["LocalMetChemDatabasePortNumber"] = 5432
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148 paramd["LocalMetChemDatabaseServerIp"] = args.LocalMetChemDatabaseServerIp
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149 paramd["LocalMetChemDatabaseUser"] = "metchemro"
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150 paramd["LocalMetChemDatabasePassword"] = "metchemro"
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151
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152 paramd["FragmentPeakMatchAbsoluteMassDeviation"] = args.FragmentPeakMatchAbsoluteMassDeviation
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153 paramd["FragmentPeakMatchRelativeMassDeviation"] = args.FragmentPeakMatchRelativeMassDeviation
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154 paramd["DatabaseSearchRelativeMassDeviation"] = args.DatabaseSearchRelativeMassDeviation
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155 paramd["SampleName"] = ''
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156 paramd["ResultsPath"] = os.path.join(wd)
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157
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158 if args.polarity == "pos":
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159 paramd["IsPositiveIonMode"] = True
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160 paramd["PrecursorIonModeDefault"] = "1"
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161 paramd["PrecursorIonMode"] = "1"
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162 paramd["nm_mass_diff_default"] = 1.007276
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163 else:
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164 paramd["IsPositiveIonMode"] = False
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165 paramd["PrecursorIonModeDefault"] = "-1"
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166 paramd["PrecursorIonMode"] = "-1"
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167 paramd["nm_mass_diff_default"] = -1.007276
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168
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169 paramd["MetFragCandidateWriter"] = "CSV"
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170 paramd["NumberThreads"] = args.NumberThreads
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171
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172 if args.ScoreSuspectLists:
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173 paramd["ScoreSuspectLists"] = args.ScoreSuspectLists
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174
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175 paramd["MetFragScoreTypes"] = args.MetFragScoreTypes
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176 paramd["MetFragScoreWeights"] = args.MetFragScoreWeights
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177
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178 dct_filter = defaultdict()
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179 filterh = []
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180
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181 if args.UnconnectedCompoundFilter:
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182 filterh.append('UnconnectedCompoundFilter')
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183
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184 if args.IsotopeFilter:
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185 filterh.append('IsotopeFilter')
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186
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187 if args.FilterMinimumElements:
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188 filterh.append('MinimumElementsFilter')
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189 dct_filter['FilterMinimumElements'] = args.FilterMinimumElements
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190
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191 if args.FilterMaximumElements:
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192 filterh.append('MaximumElementsFilter')
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193 dct_filter['FilterMaximumElements'] = args.FilterMaximumElements
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194
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195 if args.FilterSmartsInclusionList:
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196 filterh.append('SmartsSubstructureInclusionFilter')
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197 dct_filter['FilterSmartsInclusionList'] = args.FilterSmartsInclusionList
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198
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199 if args.FilterSmartsExclusionList:
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200 filterh.append('SmartsSubstructureExclusionFilter')
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201 dct_filter['FilterSmartsExclusionList'] = args.FilterSmartsExclusionList
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202
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203 # My understanding is that both 'ElementInclusionExclusiveFilter' and 'ElementExclusionFilter' use
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204 # 'FilterIncludedElements'
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205 if args.FilterIncludedExclusiveElements:
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206 filterh.append('ElementInclusionExclusiveFilter')
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207 dct_filter['FilterIncludedElements'] = args.FilterIncludedExclusiveElements
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208
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209 if args.FilterIncludedElements:
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210 filterh.append('ElementInclusionFilter')
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211 dct_filter['FilterIncludedElements'] = args.FilterIncludedElements
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212
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213 if args.FilterExcludedElements:
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214 filterh.append('ElementExclusionFilter')
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215 dct_filter['FilterExcludedElements'] = args.FilterExcludedElements
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216
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217 if filterh:
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218 fcmds = ','.join(filterh) + ' '
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219 for k, v in six.iteritems(dct_filter):
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220 fcmds += "{0}={1} ".format(str(k), str(v))
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221
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222 paramd["MetFragPreProcessingCandidateFilter"] = fcmds
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223
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224 return paramd
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225
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226
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227 ######################################################################
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228 # Function to run metfrag when all metainfo and peaks have been parsed
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229 ######################################################################
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230 def run_metfrag(meta_info, peaklist, args, wd, spectrac, adduct_types):
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231 # Get sample details (if possible to extract) e.g. if created as part of the msPurity pipeline)
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232 # choose between getting additional details to add as columns as either all meta data from msp, just
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233 # details from the record name (i.e. when using msPurity and we have the columns coded into the name) or
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234 # just the spectra index (spectrac)]
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235 # Returns the parameters used and the command line call
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236
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237 paramd = init_paramd(args)
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238 if args.meta_select_col == 'name':
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239 # have additional column of just the name
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240 paramd['additional_details'] = {'name': meta_info['name']}
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241 elif args.meta_select_col == 'name_split':
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242 # have additional columns split by "|" and then on ":" e.g. MZ:100.2 | RT:20 | xcms_grp_id:1
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243 paramd['additional_details'] = {sm.split(":")[0].strip(): sm.split(":")[1].strip() for sm in
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244 meta_info['name'].split("|")}
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245 elif args.meta_select_col == 'all':
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246 # have additional columns based on all the meta information extracted from the MSP
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247 paramd['additional_details'] = meta_info
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248 else:
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249 # Just have and index of the spectra in the MSP file
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250 paramd['additional_details'] = {'spectra_idx': spectrac}
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251
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252 paramd["SampleName"] = "{}_metfrag_result".format(spectrac)
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253
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254 # =============== Output peaks to txt file ==============================
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255 paramd["PeakListPath"] = os.path.join(wd, "{}_tmpspec.txt".format(spectrac))
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256
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257 # write spec file
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258 with open(paramd["PeakListPath"], 'w') as outfile:
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259 for p in peaklist:
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260 outfile.write(p[0] + "\t" + p[1] + "\n")
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261
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262 # =============== Update param based on MSP metadata ======================
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263 # Replace param details with details from MSP if required
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264 if 'precursor_type' in meta_info and meta_info['precursor_type'] in adduct_types:
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265
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266 nm = float(meta_info['precursor_mz']) + adduct_types[meta_info['precursor_type']]
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267 paramd["PrecursorIonMode"] = int(round(adduct_types[meta_info['precursor_type']], 0))
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268 else:
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269
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270 paramd["PrecursorIonMode"] = paramd['PrecursorIonModeDefault']
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271 nm = float(meta_info['precursor_mz']) + paramd['nm_mass_diff_default']
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272
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273 paramd["NeutralPrecursorMass"] = nm
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274
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275 # =============== Create CLI cmd for metfrag ===============================
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276 cmd = "metfrag"
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277 for k, v in six.iteritems(paramd):
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278 if not k in ['PrecursorIonModeDefault', 'nm_mass_diff_default', 'additional_details']:
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279 cmd += " {}={}".format(str(k), str(v))
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280
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281 # =============== Run metfrag ==============================================
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282 # Filter before process with a minimum number of MS/MS peaks
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283 if plinesread >= float(args.minMSMSpeaks):
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284
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285 if int(args.cores_top_level) == 1:
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286 os.system(cmd)
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287
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288 return paramd, cmd
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289
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290
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291 def work(cmds):
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292 return [os.system(cmd) for cmd in cmds]
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293
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294
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295
1
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296 ######################################################################
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297 # Parse MSP file and run metfrag CLI
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298 ######################################################################
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299 # keep list of commands if performing in CLI in parallel
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300 cmds = []
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301 # keep a dictionary of all params
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302 paramds = {}
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303 # keep count of spectra (for uid)
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304 spectrac = 0
2
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305 # this dictionary will store the meta data results form the MSp file
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306 meta_info = {}
1
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307
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308 with open(args.input_pth, "r") as infile:
2
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309 # number of lines for the peaks
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310 pnumlines = 0
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311 # number of lines read for the peaks
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312 plinesread = 0
0
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313 for line in infile:
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314 line = line.strip()
2
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315
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316 if pnumlines == 0:
1
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317 # =============== Extract metadata from MSP ========================
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318 meta_info = parse_meta(meta_regex, meta_info)
2
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319
1
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320 if ('massbank' in meta_info and 'cols' in meta_info) or ('msp' in meta_info and 'num_peaks' in meta_info):
2
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321
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322 pnumlines = int(meta_info['num_peaks'])
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323 plinesread = 0
0
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324 peaklist = []
1
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325
2
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326 elif plinesread < pnumlines:
1
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327 # =============== Extract peaks from MSP ==========================
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328 line = tuple(line.split()) # .split() will split on any empty space (i.e. tab and space)
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329 # Keep only m/z and intensity, not relative intensity
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330 save_line = tuple(line[0].split() + line[1].split())
2
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331 plinesread += 1
1
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332 peaklist.append(save_line)
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333
2
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334 elif plinesread and plinesread == pnumlines:
1
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335 # =============== Get sample name and additional details for output =======
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336 spectrac += 1
2
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337 paramd, cmd = run_metfrag(meta_info, peaklist, args, wd, spectrac, adduct_types)
1
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338
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339 paramds[paramd["SampleName"]] = paramd
2
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340 cmds.append(cmd)
1
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341
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342 meta_info = {}
2
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343 pnumlines = 0
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344 plinesread = 0
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345
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346 # end of file. Check if there is a MSP spectra to run metfrag on still
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347 if plinesread and plinesread == pnumlines:
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348
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349 paramd, cmd = run_metfrag(meta_info, peaklist, args, wd, spectrac+1, adduct_types)
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350
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351 paramds[paramd["SampleName"]] = paramd
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352 cmds.append(cmd)
0
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353
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354
2
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355
1
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356
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357
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358 # Perform multiprocessing on command line call level
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359 if int(args.cores_top_level) > 1:
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360 cmds_chunks = [cmds[x:x + int(args.chunks)] for x in list(range(0, len(cmds), int(args.chunks)))]
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361 pool = multiprocessing.Pool(processes=int(args.cores_top_level))
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362 pool.map(work, cmds_chunks)
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363 pool.close()
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364 pool.join()
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365
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366 ######################################################################
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367 # Concatenate and filter the output
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368 ######################################################################
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369 # outputs might have different headers. Need to get a list of all the headers before we start merging the files
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370 # outfiles = [os.path.join(wd, f) for f in glob.glob(os.path.join(wd, "*_metfrag_result.csv"))]
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371 outfiles = glob.glob(os.path.join(wd, "*_metfrag_result.csv"))
0
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372
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373 headers = []
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374 c = 0
1
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375 for fn in outfiles:
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376 with open(fn, 'r') as infile:
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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377 reader = csv.reader(infile)
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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parents: 0
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378 if sys.version_info >= (3, 0):
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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379 headers.extend(next(reader))
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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380 else:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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381 headers.extend(reader.next())
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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382 # check if file has any data rows
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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383 for i, row in enumerate(reader):
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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384 c += 1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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385 if i == 1:
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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386 break
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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387
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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388 # if no data rows (e.g. matches) then do not save an output and leave the program
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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389 if c == 0:
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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390 sys.exit()
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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391
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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392 additional_detail_headers = ['sample_name']
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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393 for k, paramd in six.iteritems(paramds):
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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394 additional_detail_headers = list(set(additional_detail_headers + list(paramd['additional_details'].keys())))
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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395
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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396 headers = additional_detail_headers + sorted(list(set(headers)))
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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397
2
d040e27b6225 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
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parents: 1
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398
d040e27b6225 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
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399 # Sort files nicely
d040e27b6225 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
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400 outfiles.sort(key = lambda s: int(re.match('^.*/(\d+)_metfrag_result.csv', s).group(1)))
d040e27b6225 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
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parents: 1
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401
d040e27b6225 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
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402 print(outfiles)
d040e27b6225 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
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parents: 1
diff changeset
403
d040e27b6225 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 59631850110e60900d03f642c445cc35a36414b5
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parents: 1
diff changeset
404
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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parents: 0
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405 # merge outputs
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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406 with open(args.result_pth, 'a') as merged_outfile:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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407 dwriter = csv.DictWriter(merged_outfile, fieldnames=headers, delimiter='\t', quotechar='"',
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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408 quoting=csv.QUOTE_NONNUMERIC,)
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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diff changeset
409 dwriter.writeheader()
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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diff changeset
410
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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parents: 0
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411 for fn in outfiles:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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parents: 0
diff changeset
412
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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413 with open(fn) as infile:
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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diff changeset
414 reader = csv.DictReader(infile, delimiter=',', quotechar='"')
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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415 for line in reader:
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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416 bewrite = True
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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417 for key, value in line.items():
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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418 # Filter when no MS/MS peak matched
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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419 if key == "ExplPeaks":
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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420 if float(args.pctexplpeak_thrshld) > 0 and "NA" in value:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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421 bewrite = False
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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422 # Filter with a score threshold
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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parents: 0
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423 elif key == "Score":
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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424 if float(value) <= float(args.score_thrshld):
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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425 bewrite = False
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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426 elif key == "NoExplPeaks":
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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427 nbfindpeak = float(value)
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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428 elif key == "NumberPeaksUsed":
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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429 totpeaks = float(value)
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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430 # Filter with a relative number of peak matched
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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431 try:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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432 pctexplpeak = nbfindpeak / totpeaks * 100
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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433 except ZeroDivisionError:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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434 bewrite = False
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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435 else:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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436 if pctexplpeak < float(args.pctexplpeak_thrshld):
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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437 bewrite = False
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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diff changeset
438
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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439 # Write the line if it pass all filters
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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440 if bewrite:
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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441 bfn = os.path.basename(fn)
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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442 bfn = bfn.replace(".csv", "")
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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443 ad = paramds[bfn]['additional_details']
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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444 line.update(ad)
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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445 line['sample_name'] = paramds[bfn]['SampleName']
0
75c805123b45 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit b5f4005c77b275b9b1b4349b08476afc783a8e14
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diff changeset
446
1
c1b168770b68 planemo upload for repository https://github.com/computational-metabolomics/metfrag-galaxy commit 5b384bd55e5bb4b0dc1daebd2ef5d3ee0e379b2e-dirty
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447 dwriter.writerow(line)