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1 ###########################################################################################################################################
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2 # ANNOTATION SPECTRE 2D MATRICE COMPLEXE BASEE SUR UNE SEQUENCE RMN #
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3 # matriceComplexe : data.frame liste couples ppm de la matrice a annoter #
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4 # BdDStandards : objet contenant la base de donnees des composes standards #
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5 # nom_séquence : nom sequence 2D a utiliser pour annotation ("JRES","COSY","TOCSY","HMBC","HSQC") #
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6 # ppm1Tol : tolerance ppm axe abscisses #
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7 # ppm2Tol : tolerance ppm axe ordonnees #
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8 # nb_ligne_template : préciser le nombre total de ligne de la feuille de calcul à annoter #
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9 ###########################################################################################################################################
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10 annotationRmn2D <- function(matriceComplexe, BdDStandards, nom_sequence, ppm1Tol=0.01, ppm2Tol=0.01,
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11 seuil=0, unicite="NO")
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12 {
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13 ## Longueur de la peak-list de la matrice a annoter
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14 PeakListLength <- length(matriceComplexe[, 1])
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15
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16 ## Nombre de metabolites inclus dans BdD de composes standards
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17 nbMetabolitesBdD <- length(BdDStandards)
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18 matrixAnnotation <- data.frame()
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19 allMetabolitesList <- data.frame()
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20 seuil_score <- seuil
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21
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22 ## Boucle sur les metabolites inclus dans BdD
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23 for (i in 1:nbMetabolitesBdD)
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24 {
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25 ## Infos metabolite en cours
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26 iMetabolite <- BdDStandards[[i]]
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27 ppm1M <- iMetabolite[,1]
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28 ppm2M <- iMetabolite[,2]
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29 nbPeakMetabolite <- length(ppm1M)
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30 MetaboliteName <- names(BdDStandards[i])
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31 ## print(MetaboliteName)
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32 ## Initialisation
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33 k <- 0
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34 presenceScore <- 0
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35 annotatedPpmRef <- data.frame()
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36 annotatedPpmList <- data.frame()
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37 annotatedPeakLength <- 0
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38 metabolites <- data.frame()
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39 metabolitesList <- data.frame()
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40
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41 ## Boucle sur les couples de pics de la matrice a annoter
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42 for (p in 1:PeakListLength)
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43 {
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44 ppmAnnotationF1 <- as.numeric(matriceComplexe[p, 3])
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45 ppmAnnotationF2 <- as.numeric(matriceComplexe[p, 2])
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46 e <- simpleMessage("end of file")
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47 tryCatch({
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48 if (!is.na(ppmAnnotationF1))
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49 {
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50 matrixAnnotation <- unique.data.frame(rbind.data.frame(matrixAnnotation, matriceComplexe[p, ]))
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51 }
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52 # Recherche du couple de pics de la matrice la liste des couples du metabolite standard
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53 metaboliteIn <- (ppm1M >= (ppmAnnotationF2-ppm1Tol) & ppm1M <= (ppmAnnotationF2+ppm1Tol) &
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54 ppm2M >= (ppmAnnotationF1-ppm2Tol) & ppm2M <= (ppmAnnotationF1+ppm2Tol))
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55 WhichMetaboliteIn <- which(metaboliteIn)
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56 # Si au moins un couple de la matrice a annoter dans liste couples metabolite standard
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57 if (length(WhichMetaboliteIn) > 0)
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58 {
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59 for (a in 1:length(WhichMetaboliteIn))
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60 {
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61 annotatedPpmList <- data.frame(ppm1=ppm1M[WhichMetaboliteIn[a]], ppm2=ppm2M[WhichMetaboliteIn[a]], theoricalLength=nbPeakMetabolite)
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62 annotatedPpmRef <- rbind(annotatedPpmRef,annotatedPpmList)
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63 }
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64 }
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65 }, error=function(e){cat ("End of file \n");})
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66 }
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67
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68 # Au - 1 couple de ppm de la matrice complexe annote
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69 if (nrow(annotatedPpmRef) >= 1)
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70 {
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71 ## Nombre couples annotes
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72 annotatedPeakLength <- nrow(annotatedPpmRef)
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73
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74 ## Recherche doublons
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75 annotatedDoublons <- duplicated(annotatedPpmRef)
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76 if (sum(duplicated(annotatedPpmRef)) > 0)
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77 {
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78 annotatedPeakLength <- nrow(annotatedPpmRef) - sum(duplicated(annotatedPpmRef))
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79 annotatedPpmRef <- annotatedPpmRef[-duplicated(annotatedPpmRef), ]
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80 }
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81 presenceScore <- annotatedPeakLength/nbPeakMetabolite
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82 }
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83
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84 ## Conservation metabolites dont score > seuil
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85 if (presenceScore > seuil_score)
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86 {
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87 metabolites <- data.frame(Metabolite=MetaboliteName, score=presenceScore)
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88 metabolitesList <- cbind.data.frame(annotatedPpmRef, metabolites)
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89 allMetabolitesList <- rbind.data.frame(allMetabolitesList, metabolitesList)
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90 }
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91 }
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92
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93 # Initialisation
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94 commonPpm <- data.frame()
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95 commonPpmList <- data.frame()
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96 metaboliteAdd <- data.frame()
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97 metaboliteAddList <- data.frame()
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98 # metabolite_ref <- data.frame()
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99 commonMetabolitesList <- data.frame()
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100 commonMetabolitesPpmList <- data.frame()
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101 commonMetabolitesPpmAllList1 <- data.frame()
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102 commonMetabolitesPpmAllList <- data.frame()
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103 listeTotale_2D_unicite <- allMetabolitesList[, 1:4]
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104 allMetabolitesList <- allMetabolitesList[, -3]
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105 metabolitesAllUnicite <- data.frame()
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106
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107 ## Boucle sur tous couples annotes
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108 for (j in 1:length(allMetabolitesList$ppm1))
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109 {
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110 ## Boucle sur metabolites dans BdD composes standards
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111 for (i in 1:nbMetabolitesBdD)
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112 {
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113 ppmMetaboliteBdD <- BdDStandards[[i]]
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114 ppm1M <- ppmMetaboliteBdD[,1]
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115 ppm2M <- ppmMetaboliteBdD[,2]
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116 # Nombre de couples metabolite
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117 nbPeakMetabolite <- length(ppm1M)
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118 MetaboliteName <- names(BdDStandards[i])
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119
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120 metabolitesInAll <- (ppm1M >= (allMetabolitesList[j,1]-ppm1Tol) & ppm1M <= (allMetabolitesList[j,1]+ppm1Tol) &
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121 ppm2M >= (allMetabolitesList[j,2]-ppm2Tol) & ppm2M <= (allMetabolitesList[j,2]+ppm2Tol))
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122 WhichMetabolitesInAll <- which(metabolitesInAll)
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123
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124 if (MetaboliteName != allMetabolitesList[j, 3] & length(WhichMetabolitesInAll) > 0)
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125 {
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126 metabolitesAllUnicite <- rbind.data.frame(metabolitesAllUnicite, listeTotale_2D_unicite[j,])
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127 commonPpm <- data.frame(ppm1=allMetabolitesList[j,1], ppm2=allMetabolitesList[j,2])
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128 commonPpmList <- rbind.data.frame(commonPpmList, commonPpm)
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129 commonPpmList <- unique(commonPpmList)
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130 metaboliteAdd <- data.frame(nom_metabolite=MetaboliteName)
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131 metaboliteAddList <- rbind.data.frame(metaboliteAddList, metaboliteAdd)
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132 # metabolite_ref <- data.frame(nom_metabolite=allMetabolitesList[j,3])
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133 commonMetabolitesList <- rbind.data.frame(data.frame(nom_metabolite=allMetabolitesList[j, 3]), metaboliteAddList)
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134 commonMetabolitesPpmList <- cbind.data.frame(commonPpm, commonMetabolitesList)
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135 commonMetabolitesPpmAllList1 <- rbind.data.frame(commonMetabolitesPpmAllList1, commonMetabolitesPpmList)
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136 commonMetabolitesPpmAllList1 <- unique.data.frame(commonMetabolitesPpmAllList1)
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137 }
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138 }
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139 commonMetabolitesPpmAllList <- rbind.data.frame(commonMetabolitesPpmAllList, commonMetabolitesPpmAllList1)
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140 commonMetabolitesPpmAllList <- unique.data.frame(commonMetabolitesPpmAllList)
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141
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142 #initialisation des data.frame
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143 commonPpm <- data.frame()
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144 metaboliteAdd <- data.frame()
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145 metaboliteAddList <- data.frame()
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146 metabolite_ref <- data.frame()
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147 commonMetabolitesList <- data.frame()
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148 commonMetabolitesPpmList <- data.frame()
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149 commonMetabolitesPpmAllList1 <- data.frame()
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150 }
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151
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152 unicityAllList <- listeTotale_2D_unicite
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153 if (nrow(listeTotale_2D_unicite)!=0 & nrow(metabolitesAllUnicite)!=0)
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154 unicityAllList <- setdiff(listeTotale_2D_unicite, metabolitesAllUnicite)
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155
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156 unicitynbCouplesRectif <- data.frame()
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157 for (g in 1:nrow(unicityAllList))
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158 {
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159 metaboliteUnicity <- (unicityAllList$Metabolite == unicityAllList$Metabolite[g])
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160 WhichMetaboliteUnicity <- which(metaboliteUnicity)
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161 nb_occurence <- length(WhichMetaboliteUnicity)
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162 unicitynbCouplesRectif <- rbind.data.frame(unicitynbCouplesRectif, nb_occurence)
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163 }
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164 names(unicitynbCouplesRectif) <- "NbCouplesAnnotes"
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165 unicityAllList <- cbind.data.frame(unicityAllList, unicitynbCouplesRectif)
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166
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167 unicityAllList <- cbind.data.frame(unicityAllList, score_unicite=unicityAllList$NbCouplesAnnotes/unicityAllList$theoricalLength)
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168 unicityAllList <- unicityAllList[, -3]
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169 unicityAllList <- unicityAllList[, -4]
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170
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171 ## unicityAllList <- filter(unicityAllList, unicityAllList$score_unicite > seuil_score)
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172 unicityAllList <- unicityAllList[unicityAllList$score_unicite > seuil_score,]
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173
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174 listeTotale_metabo <- data.frame()
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175 if (nrow(commonPpmList) !=0)
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176 {
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177 for (o in 1:length(commonPpmList[, 1]))
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178 {
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179 tf6 <- (commonMetabolitesPpmAllList$ppm1 == commonPpmList[o,1] & commonMetabolitesPpmAllList$ppm2 == commonPpmList[o,2])
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180 w6 <- which(tf6)
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181
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182 for (s in 1:length(w6))
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183 {
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184 metaboliteAdd <- data.frame(nom_metabolite=commonMetabolitesPpmAllList[w6[s],3])
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185 commonMetabolitesList <- paste(commonMetabolitesList, metaboliteAdd[1,], sep = " ")
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186 }
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187 liste_metabo_ppm <- cbind.data.frame(ppm1=commonPpmList[o,1],ppm2=commonPpmList[o,2], commonMetabolitesList)
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188 listeTotale_metabo <- rbind.data.frame(listeTotale_metabo, liste_metabo_ppm)
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189 commonMetabolitesList <- data.frame()
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190 }
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191 }
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192
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193 # Representation graphique
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194 if (nom_sequence == "HSQC" | nom_sequence == "HMBC")
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195 {
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196 atome <- "13C"
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197 indice_positif <- 1
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198 indice_negatif <- -10
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199 }else{
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200 atome <- "1H"
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201 indice_positif <- 0.5
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202 indice_negatif <- -0.5
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203 }
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204
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205 matriceComplexe <- matrixAnnotation
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206 ppm1 <- as.numeric(matriceComplexe[,2])
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207 ppm2 <- as.numeric(matriceComplexe[,3])
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208
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209 if (unicite == "NO")
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210 {
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211 listeTotale_2D_a_utiliser <- allMetabolitesList
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212 d1.ppm <- allMetabolitesList$ppm1
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213 d2.ppm <- allMetabolitesList$ppm2
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214 }else{
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215 listeTotale_2D_a_utiliser <- unicityAllList
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216 d1.ppm <- listeTotale_2D_a_utiliser$ppm1
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217 d2.ppm <- listeTotale_2D_a_utiliser$ppm2
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218 }
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219
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220 if (nrow(listeTotale_2D_a_utiliser) > 0)
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221 {
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222 ## Taches de correlations
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223 # Matrice biologique + Annotations
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224 maxX <- max(round(max(as.numeric(matriceComplexe[,2])))+0.5, round(max(as.numeric(matriceComplexe[,2]))))
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225 maxY <- max(round(max(as.numeric(matriceComplexe[,3])))+indice_positif, round(max(as.numeric(matriceComplexe[,3]))))
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226 probability.score <- as.factor(round(listeTotale_2D_a_utiliser[,4],2))
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227 lgr <- length(unique(probability.score))
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228 sp <- ggplot(matriceComplexe, aes(x=ppm1, y=ppm2))
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229 sp <- sp + geom_point(size=2) + scale_x_reverse(breaks=seq(maxX, 0, -0.5)) +
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230 scale_y_reverse(breaks=seq(maxY, 0, indice_negatif)) +
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231 xlab("1H chemical shift (ppm)") + ylab(paste(atome, " chemical shift (ppm)")) + ggtitle(nom_sequence) +
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232 geom_text(data=listeTotale_2D_a_utiliser, aes(d1.ppm, d2.ppm, label=str_to_lower(substr(listeTotale_2D_a_utiliser[,3],1,3)),
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233 col=probability.score),
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234 size=4, hjust=0, nudge_x=0.02, vjust=0, nudge_y=0.2) + scale_colour_manual(values=viridis(lgr))
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235 ## scale_color_colormap('Annotation', discrete=T, reverse=T)
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236 print(sp)
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237 }
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238
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239 # Liste des résultats (couples pmm / metabolite / score) + liste ppms metabolites communs
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240 if (unicite == "NO")
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241 {
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242 return(list(liste_resultat=allMetabolitesList, listing_ppm_commun=listeTotale_metabo))
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243 }else{
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244 return(list(liste_resultat_unicite=unicityAllList, listing_ppm_commun_affichage=listeTotale_metabo))
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245 }
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246 } |
