Mercurial > repos > workflow4metabolomics > ms2snoop
annotate MS2snoop.R @ 0:91a3242fd67f draft
"planemo upload commit c7676a9c7ac542043691d735285ae19e430bf032"
author | workflow4metabolomics |
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date | Mon, 25 Apr 2022 08:23:54 +0000 |
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children | df2672c37732 |
rev | line source |
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0
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1 #' |
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2 #' read and process mspurity W4M files |
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3 #' create a summary of fragment for each precursor and a graphics of peseudo |
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4 #' spectra + correlation on which checking of fragment is based on |
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5 #' V3 try to identify and process multiple files for 1 precursor which may |
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6 #' occur if different collision energy are used |
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7 #' V4 elimination of correlation = NA. Correlation is done with precursor, if |
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8 #' precursor is not present correlation with most intense peak |
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9 #' author: Jean-Francois Martin |
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10 #' V5 is versionned, lintR-compliant, packaged, unit-tested, documented and |
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11 #' tested against data from other labs. |
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12 #' new maintainer: Lain Pavot - lain.pavot@inrae.fr |
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13 #' |
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14 #' @import optparse |
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15 #' |
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16 NULL |
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17 |
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18 |
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19 assign("DEFAULT_PRECURSOR_PATH", "peaklist_precursors.tsv") |
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20 assign("DEFAULT_FRAGMENTS_PATH", "peaklist_fragments.tsv") |
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21 assign("DEFAULT_COMPOUNDS_PATH", "compounds_pos.txt") |
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22 assign("DEFAULT_OUTPUT_PATH", "compound_fragments_result.txt") |
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23 assign("DEFAULT_TOLMZ", 0.01) |
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24 assign("DEFAULT_TOLRT", 20) |
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25 assign("DEFAULT_MZDECIMAL", 0) |
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26 assign("DEFAULT_R_THRESHOLD", 0.85) |
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27 assign("DEFAULT_MINNUMBERSCAN", 8) |
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28 assign("DEFAULT_SEUIL_RA", 0.5) |
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29 lockBinding("DEFAULT_PRECURSOR_PATH", globalenv()) |
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30 lockBinding("DEFAULT_FRAGMENTS_PATH", globalenv()) |
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31 lockBinding("DEFAULT_COMPOUNDS_PATH", globalenv()) |
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32 lockBinding("DEFAULT_OUTPUT_PATH", globalenv()) |
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33 lockBinding("DEFAULT_TOLMZ", globalenv()) |
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34 lockBinding("DEFAULT_TOLRT", globalenv()) |
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35 lockBinding("DEFAULT_MZDECIMAL", globalenv()) |
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36 lockBinding("DEFAULT_R_THRESHOLD", globalenv()) |
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37 lockBinding("DEFAULT_MINNUMBERSCAN", globalenv()) |
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38 lockBinding("DEFAULT_SEUIL_RA", globalenv()) |
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39 |
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40 assign("DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD", 0.85) |
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41 assign("DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA", 0.1) |
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42 assign("DEFAULT_EXTRACT_FRAGMENTS_TOLMZ", 0.01) |
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43 assign("DEFAULT_EXTRACT_FRAGMENTS_TOLRT", 60) |
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44 lockBinding("DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD", globalenv()) |
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45 lockBinding("DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA", globalenv()) |
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46 lockBinding("DEFAULT_EXTRACT_FRAGMENTS_TOLMZ", globalenv()) |
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47 lockBinding("DEFAULT_EXTRACT_FRAGMENTS_TOLRT", globalenv()) |
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48 |
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49 |
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50 debug <- FALSE |
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51 |
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52 |
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53 ######################################################################## |
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54 |
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55 #' @title plot_pseudo_spectra |
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56 #' @param x |
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57 #' @param r_threshold |
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58 #' @param fid |
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59 #' @param sum_int |
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60 #' @param vmz |
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61 #' @param cor_abs_int |
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62 #' @param refcol |
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63 #' @param c_name |
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64 #' @description plot_pseudo_spectra |
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65 #' function to compute sum of intensities among scans for all |
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66 #' m/z kept (cor > r_threshold & minimum number of scans) |
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67 #' and plot pseudo spectra |
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68 #' x dataframe scan X fragments with scans number in the 1st column and |
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69 #' ions in next with intensities |
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70 #' fid file id when several a precursor has been detected in several files |
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71 plot_pseudo_spectra <- function( |
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72 x, |
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73 r_threshold, |
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74 fid, |
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75 sum_int, |
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76 vmz, |
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77 cor_abs_int, |
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78 refcol, |
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79 c_name |
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80 ) { |
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81 ## du fait de la difference de nombre de colonne entre la dataframe qui |
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82 ## inclue les scans en 1ere col, mzRef se decale de 1 |
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83 refcol <- refcol - 1 |
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84 ## compute relative intensities max=100% |
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85 rel_int <- sum_int[-1] |
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86 rel_int <- rel_int / max(rel_int) |
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87 |
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88 ## define max value on vertical axis (need to increase in order to plot the |
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89 ## label of fragments) |
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90 ymax <- max(rel_int) + 0.2 * max(rel_int) |
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91 |
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92 par(mfrow = c(2, 1)) |
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93 plot(vmz, rel_int, type = "h", ylim = c(0, ymax), main = c_name) |
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94 ## low correl coef. will be display in grey |
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95 cor_low <- which(round(cor_abs_int, 2) < r_threshold) |
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96 |
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97 lbmzcor <- sprintf("%s(r=%s)", vmz, round(cor_abs_int, 2)) |
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98 |
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99 if (length(cor_low) > 0) { |
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100 text( |
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101 vmz[cor_low], |
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102 rel_int[cor_low], |
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103 lbmzcor[cor_low], |
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104 cex = 0.5, |
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105 col = "grey", |
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106 srt = 90, |
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107 adj = 0 |
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108 ) |
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109 if (length(vmz) - length(cor_low) > 1) { |
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110 text( |
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111 vmz[-c(refcol, cor_low)], |
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112 rel_int[-c(refcol, cor_low)], |
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113 lbmzcor[-c(refcol, cor_low)], |
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114 cex = 0.6, |
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115 col = 1, |
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116 srt = 90, |
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117 adj = 0 |
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118 ) |
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119 } |
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120 } else { |
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121 if (length(vmz) > 1) { |
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122 text( |
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123 vmz[-c(refcol)], |
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124 rel_int[-c(refcol)], |
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125 lbmzcor[-c(refcol)], |
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126 cex = 0.6, |
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127 col = 1, |
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128 srt = 90, |
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129 adj = 0 |
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130 ) |
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131 } |
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132 } |
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133 |
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134 text( |
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135 vmz[refcol], |
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136 rel_int[refcol], |
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137 lbmzcor[refcol], |
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138 cex = 0.8, |
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139 col = 2, |
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140 srt = 90, |
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141 adj = 0 |
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142 ) |
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143 |
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144 ## prepare result file |
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145 corValid <- (round(cor_abs_int, 2) >= r_threshold) ##nolint object_name_linter |
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146 cp_res <- data.frame( |
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147 rep(c_name, length(vmz)), |
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148 rep(fid, length(vmz)), |
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149 vmz, |
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150 cor_abs_int, |
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151 sum_int[-1], |
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152 rel_int, |
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153 corValid |
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154 ) |
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155 |
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156 colnames(cp_res) <- c( |
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157 "compoundName", |
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158 "fileid", |
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159 "fragments_mz", |
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160 "CorWithPrecursor", |
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161 "AbsoluteIntensity", |
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162 "relativeIntensity", |
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163 "corValid" |
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164 ) |
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165 return(cp_res) |
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166 |
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167 } |
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168 |
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169 #' |
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170 #' @title extract_fragments |
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171 #' |
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172 #' @param precursors the precursor list from mspurity |
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173 #' @param fragments the fragments list from ms purity |
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174 #' @param mzref |
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175 #' @param rtref |
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176 #' @param c_name |
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177 #' @param r_threshold default = DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD |
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178 #' @param seuil_ra default = DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA |
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179 #' @param tolmz default = DEFAULT_EXTRACT_FRAGMENTS_TOLMZ |
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180 #' @param tolrt default = DEFAULT_EXTRACT_FRAGMENTS_TOLRT |
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181 #' @returns |
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182 #' |
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183 #' @description |
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184 #' function for extraction of fragments corresponding to precursors |
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185 #' detected by MSPurity |
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186 extract_fragments <- function( ## nolint cyclocomp_linter |
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187 precursors, |
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188 fragments, |
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189 mzref, |
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190 rtref, |
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191 c_name, |
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192 min_number_scan, |
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193 mzdecimal, |
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194 r_threshold=DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD, |
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195 seuil_ra=DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA, |
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196 tolmz=DEFAULT_EXTRACT_FRAGMENTS_TOLMZ, |
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197 tolrt=DEFAULT_EXTRACT_FRAGMENTS_TOLRT |
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198 ) { |
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199 ## filter precursor in the precursors file based on mz and rt in the |
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200 ## compound list |
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201 cat("processing ", c_name, "\n") |
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202 selected_precursors <- which( |
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203 (abs(precursors$precurMtchMZ - mzref) <= tolmz) |
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204 & (abs(precursors$precurMtchRT - rtref) <= tolrt) |
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205 ) |
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206 |
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207 ## check if there is the precursor in the file |
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208 if (length(selected_precursors) > 0) { |
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209 |
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210 sprecini <- precursors[selected_precursors, ] |
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211 |
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212 ## check if fragments corresponding to precursor are found in several |
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213 ## files (collision energy) |
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214 ## this lead to a processing for each fileid |
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215 mf <- levels(as.factor(sprecini$fileid)) |
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216 if (length(mf) > 1) { |
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217 cat(" several files detected for this compounds :\n") |
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218 } |
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219 |
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220 for (f in seq_along(mf)) { |
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221 |
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222 sprec <- sprecini[sprecini$fileid == mf[f], ] |
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223 |
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224 ## selection of fragment in the fragments file with the grpid common in |
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225 ## both fragments and precursors |
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226 selfrgt <- levels(as.factor(sprec$grpid)) |
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227 sfrgt <- fragments[ |
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228 fragments$grpid %in% selfrgt |
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229 & fragments$fileid == mf[f], |
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230 ] |
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231 |
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232 ## filter fragments on relative intensity seuil_ra = user defined |
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233 ## parameter (MSpurity flags could be used here) |
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234 sfrgtfil <- sfrgt[sfrgt$ra > seuil_ra, ] |
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235 |
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236 mznominal <- round(x = sfrgtfil$mz, mzdecimal) |
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237 sfrgtfil <- data.frame(sfrgtfil, mznominal) |
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238 |
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239 ## creation of cross table row=scan col=mz X=ra |
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240 vmz <- levels(as.factor(sfrgtfil$mznominal)) |
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241 |
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242 cat(" fragments :", vmz) |
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243 |
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244 ## mz of precursor in data precursor to check correlation with |
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245 mz_prec <- paste0("mz", round(mean(sprec$mz), mzdecimal)) |
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246 |
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247 for (m in seq_along(vmz)) { |
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248 |
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249 ## absolute intensity |
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250 cln <- c( |
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251 which(colnames(sfrgtfil) == "acquisitionNum"), |
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252 which(colnames(sfrgtfil) == "i") |
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253 ) |
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254 int_mz <- sfrgtfil[sfrgtfil$mznominal == vmz[m], cln] |
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255 colnames(int_mz)[2] <- paste0("mz", vmz[m]) |
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256 |
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257 ## average intensities of mass in duplicate scans |
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258 comp_scans <- aggregate(x = int_mz, by = list(int_mz[[1]]), FUN = mean) |
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259 int_mz <- comp_scans[, -1] |
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260 |
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261 if (m == 1) { |
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262 ds_abs_int <- int_mz |
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263 } else { |
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264 ds_abs_int <- merge( |
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265 x = ds_abs_int, |
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266 y = int_mz, |
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267 by.x = 1, |
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268 by.y = 1, |
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269 all.x = TRUE, |
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270 all.y = TRUE |
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271 ) |
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272 } |
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273 } |
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274 if (debug) { |
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275 write.table( |
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276 x = ds_abs_int, |
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277 file = paste0(c_name, "ds_abs_int.txt"), |
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278 row.names = FALSE, |
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279 sep = "\t" |
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280 ) |
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281 } |
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282 |
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283 ## elimination of mz with less than min_number_scan scans (user defined |
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284 ## parameter) |
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285 xmz <- rep(NA, ncol(ds_abs_int) - 1) |
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286 sum_int <- rep(NA, ncol(ds_abs_int)) |
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287 nbxmz <- 0 |
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288 nb_scan_check <- min(nrow(ds_abs_int), min_number_scan) |
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289 |
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290 for (j in 2:ncol(ds_abs_int)) { |
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291 sum_int[j] <- sum(ds_abs_int[j], na.rm = TRUE) |
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292 if (sum(!is.na(ds_abs_int[[j]])) < nb_scan_check) { |
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293 nbxmz <- nbxmz + 1 |
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294 xmz[nbxmz] <- j |
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295 } |
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296 } |
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297 |
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298 xmz <- xmz[-which(is.na(xmz))] |
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299 if (length(xmz) > 0) { |
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300 ds_abs_int <- ds_abs_int[, -c(xmz)] |
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301 sum_int <- sum_int[-c(xmz)] |
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302 ## liste des mz keeped decale de 1 avec ds_abs_int |
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303 vmz <- as.numeric(vmz[-c(xmz - 1)]) |
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304 } |
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305 |
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306 ## reference ion for correlation computing = precursor OR maximum |
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307 ## intensity ion in precursor is not present |
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308 refcol <- which(colnames(ds_abs_int) == mz_prec) |
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309 if (length(refcol) == 0) { |
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310 refcol <- which(sum_int == max(sum_int, na.rm = TRUE)) |
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311 } |
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312 pdf( |
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313 file = sprintf("%s_processing_file%s.pdf", c_name, mf[f]), |
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314 width = 8, |
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315 height = 11 |
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316 ) |
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317 par(mfrow = c(3, 2)) |
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318 |
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319 ## Pearson correlations between absolute intensities computing |
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320 cor_abs_int <- rep(NA, length(vmz)) |
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321 |
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322 if (length(refcol) > 0) { |
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323 for (i in 2:length(ds_abs_int)) { |
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324 cor_abs_int[i - 1] <- cor( |
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325 x = ds_abs_int[[refcol]], |
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326 y = ds_abs_int[[i]], |
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327 use = "pairwise.complete.obs", |
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328 method = "pearson" |
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329 ) |
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330 plot( |
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331 ds_abs_int[[refcol]], |
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332 ds_abs_int[[i]], |
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333 xlab = colnames(ds_abs_int)[refcol], |
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334 ylab = colnames(ds_abs_int)[i], |
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335 main = sprintf( |
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336 "%s corr coeff r=%s", c_name, round(cor_abs_int[i - 1], 2) |
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337 ) |
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338 ) |
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339 } |
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340 ## plot pseudo spectra |
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341 res_comp_by_file <- plot_pseudo_spectra( |
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342 x = ds_abs_int, |
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343 r_threshold = r_threshold, |
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344 fid = mf[f], |
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345 sum_int = sum_int, |
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346 vmz = vmz, |
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347 cor_abs_int = cor_abs_int, |
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348 refcol = refcol, |
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349 c_name = c_name |
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350 ) |
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351 if (f == 1) { |
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352 res_comp <- res_comp_by_file |
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353 } |
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354 } else { |
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355 res_comp_by_file <- NULL |
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356 cat(" non detected in fragments file \n") |
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357 } |
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358 if (!is.null(res_comp_by_file)) { |
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359 res_comp <- rbind(res_comp, res_comp_by_file) |
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360 } |
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361 cat("\n") |
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362 dev.off() |
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363 } |
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364 } else { |
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365 res_comp <- NULL |
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366 cat(" non detected in precursor file \n") |
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367 } |
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368 return(res_comp) |
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369 } |
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370 |
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371 |
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372 create_parser <- function() { |
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373 parser <- optparse::OptionParser() |
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374 parser <- optparse::add_option( |
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375 parser, |
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376 c("-v", "--verbose"), |
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377 action = "store_true", |
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378 default = FALSE, |
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379 help = "Print extra output [default %default]" |
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380 ) |
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381 parser <- optparse::add_option( |
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382 parser, |
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383 c("-o", "--output"), |
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384 type = "character", |
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385 default = DEFAULT_OUTPUT_PATH, |
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386 action = "store", |
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387 help = "Path to the output file [default %default]" |
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388 ) |
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389 parser <- optparse::add_option( |
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390 parser, |
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391 c("-p", "--precursors"), |
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392 type = "character", |
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393 default = DEFAULT_PRECURSOR_PATH, |
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394 action = "store", |
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395 help = "Path to the precursors file [default %default]" |
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396 ) |
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397 parser <- optparse::add_option( |
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398 parser, |
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399 c("-f", "--fragments"), |
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400 type = "character", |
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401 default = DEFAULT_FRAGMENTS_PATH, |
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402 action = "store", |
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403 help = "Path to the fragments file [default %default]" |
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404 ) |
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405 parser <- optparse::add_option( |
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406 parser, |
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407 c("-c", "--compounds"), |
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408 type = "character", |
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409 default = DEFAULT_COMPOUNDS_PATH, |
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410 action = "store", |
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411 help = "Path to the compounds file [default %default]" |
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412 ) |
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413 parser <- optparse::add_option( |
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414 parser, |
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415 c("--tolmz"), |
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416 type = "numeric", |
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417 action = "store", |
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418 default = DEFAULT_TOLMZ, |
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419 metavar = "number" |
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420 ) |
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421 parser <- optparse::add_option( |
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422 parser, |
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423 c("--tolrt"), |
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424 type = "integer", |
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425 action = "store", |
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426 default = DEFAULT_TOLRT, |
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427 metavar = "number" |
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428 ) |
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429 parser <- optparse::add_option( |
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430 parser, |
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431 c("--seuil_ra"), |
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432 type = "numeric", |
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433 action = "store", |
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434 help = "relative intensity threshold", |
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435 default = DEFAULT_SEUIL_RA, |
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436 metavar = "number" |
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437 ) |
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438 parser <- optparse::add_option( |
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439 parser, |
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440 c("--mzdecimal"), |
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441 type = "integer", |
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442 default = DEFAULT_MZDECIMAL, |
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443 action = "store", |
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444 help = "nb decimal for mz", |
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445 metavar = "number" |
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446 ) |
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447 parser <- optparse::add_option( |
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448 parser, |
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449 c("--r_threshold"), |
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450 type = "integer", |
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451 default = DEFAULT_R_THRESHOLD, |
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452 action = "store", |
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453 help = paste0( |
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454 "r pearson correlation threshold between precursor and fragment ", |
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455 "absolute intensity" |
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456 ), |
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457 metavar = "number" |
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458 ) |
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459 parser <- optparse::add_option( |
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460 parser, |
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461 c("--min_number_scan"), |
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462 type = "numeric", |
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463 action = "store", |
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464 default = DEFAULT_MINNUMBERSCAN, |
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465 help = paste0( |
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466 "fragments are kept if there are found in a minimum number ", |
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467 "of scans" |
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468 ), |
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469 metavar = "number" |
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470 ) |
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471 return(parser) |
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472 } |
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473 |
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474 main <- function(args) { |
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475 ## FOLDER AND FILES |
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476 ## MSpurity precursors file |
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477 precursors <- read.table( |
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478 file = args$precursors, |
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479 header = TRUE, |
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480 sep = "\t", |
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481 quote = "\"" |
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482 ) |
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483 ## MSpurity fragments file |
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484 fragments <- read.table( |
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485 file = args$fragments, |
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486 header = TRUE, |
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487 sep = "\t", |
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488 quote = "\"" |
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489 ) |
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490 ## list of compounds : col1=Name of molecule, col2=m/z, col3=retention time |
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491 compounds <- read.table( |
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492 file = args$compounds, |
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493 sep = "\t", |
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494 quote = "\"", |
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495 header = TRUE |
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496 ) |
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497 ## PARAMETERS |
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498 ## tolerance for mz(dalton) rt(seconds) to match the standard in the compounds |
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499 ## list with the precursor MSpurity file |
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500 tolmz <- args$tolmz |
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501 tolrt <- args$tolrt |
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502 |
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503 ## relative intensity threshold |
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504 seuil_ra <- args$seuil_ra |
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505 ## nb decimal for mz |
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506 mzdecimal <- args$mzdecimal |
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507 ## r pearson correlation threshold between precursor and |
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508 # #fragment absolute intensity |
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509 r_threshold <- args$r_threshold |
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510 ## fragments are kept if there are found in a minimum number of scans |
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511 min_number_scan <- args$min_number_scan |
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512 |
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513 for (i in seq_len(nrow(compounds))) { |
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514 ## loop execution for all compounds in the compounds file |
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515 res_cor <- NULL |
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516 res_cor <- extract_fragments( |
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517 precursors = precursors, |
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518 fragments = fragments, |
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519 mzref = compounds[[2]][i], |
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520 rtref = compounds[[3]][i], |
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521 c_name = compounds[[1]][i], |
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522 min_number_scan = min_number_scan, |
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523 mzdecimal = mzdecimal, |
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524 r_threshold = r_threshold, |
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525 seuil_ra = seuil_ra, |
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526 tolmz = tolmz, |
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527 tolrt = tolrt |
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528 ) |
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529 if (i == 1 & !is.null(res_cor)) { |
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530 res_all <- res_cor |
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531 } else if (!is.null(res_cor)) { |
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532 res_all <- rbind(res_all, res_cor) |
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533 } |
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534 } |
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535 |
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536 if (is.null(res_all)) { |
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537 stop("No result at all!") |
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538 } |
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539 write.table( |
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540 x = res_all, |
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541 file = args$output, |
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542 sep = "\t", |
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543 row.names = FALSE |
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544 ) |
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545 } |
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546 |
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547 args <- optparse::parse_args(create_parser()) |
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548 sessionInfo() |
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549 main(args) |
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550 |
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551 warnings() |