Mercurial > repos > marie-tremblay-metatoul > 2dnmrannotation

annotate annotationRmn2D.R @ 4:cf11fa0c47c8 draft default tip

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planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics commit b5f7f56b5ffc3c900236c077f72b321df20647be
author workflow4metabolomics
date Thu, 23 Jan 2025 15:28:44 +0000
parents 546c7ccd2ed4
children
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4
cf11fa0c47c8 planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics commit b5f7f56b5ffc3c900236c077f72b321df20647be
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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_sequence : nom sequence 2D a utiliser pour annotation ("JRES", "COSY", "TOCSY", "HMBC", "HSQC") #
cf11fa0c47c8 planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics commit b5f7f56b5ffc3c900236c077f72b321df20647be
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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 : preciser le nombre total de ligne de la feuille de calcul a 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 ## Longueur de la peak-list de la matrice a annoter
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13 PeakListLength <- length(matriceComplexe[, 1])
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14
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15 ## Nombre de metabolites inclus dans BdD de composes standards
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16 nbMetabolitesBdD <- length(BdDStandards)
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17 matrixAnnotation <- data.frame()
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18 allMetabolitesList <- data.frame()
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19 seuil_score <- seuil
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20
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21 ## Boucle sur les metabolites inclus dans BdD
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22 for (i in seq_len(nbMetabolitesBdD)) {
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23 ## Infos metabolite en cours
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24 iMetabolite <- BdDStandards[[i]]
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25 ppm1M <- iMetabolite[, 1]
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26 ppm2M <- iMetabolite[, 2]
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27 nbPeakMetabolite <- length(ppm1M)
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28 MetaboliteName <- names(BdDStandards[i])
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29
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30 ## Initialisation
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31 k <- 0
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32 presenceScore <- 0
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33 annotatedPpmRef <- data.frame()
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34 annotatedPpmList <- data.frame()
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35 annotatedPeakLength <- 0
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36 metabolites <- data.frame()
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37 metabolitesList <- data.frame()
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38
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39 ## Boucle sur les couples de pics de la matrice a annoter
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40 for (p in seq_len(PeakListLength)) {
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41 ppmAnnotationF1 <- as.numeric(matriceComplexe[p, 3])
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42 ppmAnnotationF2 <- as.numeric(matriceComplexe[p, 2])
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43 e <- simpleMessage("end of file")
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44 tryCatch(
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45 {
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46 if (!is.na(ppmAnnotationF1)) {
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47 matrixAnnotation <- unique.data.frame(rbind.data.frame(matrixAnnotation, matriceComplexe[p, ]))
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48 }
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49 # Recherche du couple de pics de la matrice la liste des couples du metabolite standard
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50 metaboliteIn <- (ppm1M >= (ppmAnnotationF2 - ppm1Tol) & ppm1M <= (ppmAnnotationF2 + ppm1Tol) &
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51 ppm2M >= (ppmAnnotationF1 - ppm2Tol) & ppm2M <= (ppmAnnotationF1 + ppm2Tol))
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52 WhichMetaboliteIn <- which(metaboliteIn)
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53 # Si au moins un couple de la matrice a annoter dans liste couples metabolite standard
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54 if (length(WhichMetaboliteIn) > 0) {
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55 for (a in seq_len(length(WhichMetaboliteIn))) {
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56 annotatedPpmList <- data.frame(ppm1 = ppm1M[WhichMetaboliteIn[a]], ppm2 = ppm2M[WhichMetaboliteIn[a]], theoricalLength = nbPeakMetabolite)
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57 annotatedPpmRef <- rbind(annotatedPpmRef, annotatedPpmList)
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58 }
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59 }
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60 },
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61 error = function(e) {
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62 cat("End of file \n")
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63 }
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64 )
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65 }
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66
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67 # Au - 1 couple de ppm de la matrice complexe annote
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68 if (nrow(annotatedPpmRef) >= 1) {
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69 ## Nombre couples annotes
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70 annotatedPeakLength <- nrow(annotatedPpmRef)
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71
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72 ## Recherche doublons
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73 annotatedDoublons <- duplicated(annotatedPpmRef)
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74 if (sum(duplicated(annotatedPpmRef)) > 0) {
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75 annotatedPeakLength <- nrow(annotatedPpmRef) - sum(duplicated(annotatedPpmRef))
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76 annotatedPpmRef <- annotatedPpmRef[-duplicated(annotatedPpmRef), ]
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77 }
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78 presenceScore <- round(annotatedPeakLength / nbPeakMetabolite, 2)
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79 }
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80
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81 ## Conservation metabolites dont score > seuil
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82 if (presenceScore > seuil_score) {
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83 metabolites <- data.frame(Metabolite = MetaboliteName, score = presenceScore)
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84 metabolitesList <- cbind.data.frame(annotatedPpmRef, metabolites)
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85 allMetabolitesList <- rbind.data.frame(allMetabolitesList, metabolitesList)
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86 }
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87 }
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88
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89 # Initialisation
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90 commonPpm <- data.frame()
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91 commonPpmList <- data.frame()
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92 metaboliteAdd <- data.frame()
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93 metaboliteAddList <- data.frame()
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94 commonMetabolitesList <- data.frame()
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95 commonMetabolitesPpmList <- data.frame()
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96 commonMetabolitesPpmAllList1 <- data.frame()
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97 commonMetabolitesPpmAllList <- data.frame()
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98 listeTotale_2D_unicite <- allMetabolitesList[, 1:4]
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99 allMetabolitesList <- allMetabolitesList[, -3]
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100 metabolitesAllUnicite <- data.frame()
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101
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102 ## Boucle sur tous couples annotes
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103 for (j in seq_len(length(allMetabolitesList$ppm1))) {
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104 ## Boucle sur metabolites dans BdD composes standards
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105 for (i in seq_len(nbMetabolitesBdD)) {
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106 ppmMetaboliteBdD <- BdDStandards[[i]]
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107 ppm1M <- ppmMetaboliteBdD[, 1]
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108 ppm2M <- ppmMetaboliteBdD[, 2]
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109 # Nombre de couples metabolite
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110 nbPeakMetabolite <- length(ppm1M)
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111 MetaboliteName <- names(BdDStandards[i])
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112
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113 metabolitesInAll <- (ppm1M >= (allMetabolitesList[j, 1] - ppm1Tol) & ppm1M <= (allMetabolitesList[j, 1] + ppm1Tol) &
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114 ppm2M >= (allMetabolitesList[j, 2] - ppm2Tol) & ppm2M <= (allMetabolitesList[j, 2] + ppm2Tol))
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115 WhichMetabolitesInAll <- which(metabolitesInAll)
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116
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117 if (MetaboliteName != allMetabolitesList[j, 3] & length(WhichMetabolitesInAll) > 0) {
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118 metabolitesAllUnicite <- rbind.data.frame(metabolitesAllUnicite, listeTotale_2D_unicite[j, ])
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119 commonPpm <- data.frame(ppm1 = allMetabolitesList[j, 1], ppm2 = allMetabolitesList[j, 2])
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120 commonPpmList <- rbind.data.frame(commonPpmList, commonPpm)
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121 commonPpmList <- unique(commonPpmList)
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122 metaboliteAdd <- data.frame(nom_metabolite = MetaboliteName)
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123 metaboliteAddList <- rbind.data.frame(metaboliteAddList, metaboliteAdd)
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124 commonMetabolitesList <- rbind.data.frame(data.frame(nom_metabolite = allMetabolitesList[j, 3]), metaboliteAddList)
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125 commonMetabolitesPpmList <- cbind.data.frame(commonPpm, commonMetabolitesList)
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126 commonMetabolitesPpmAllList1 <- rbind.data.frame(commonMetabolitesPpmAllList1, commonMetabolitesPpmList)
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127 commonMetabolitesPpmAllList1 <- unique.data.frame(commonMetabolitesPpmAllList1)
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128 }
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129 }
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130 commonMetabolitesPpmAllList <- rbind.data.frame(commonMetabolitesPpmAllList, commonMetabolitesPpmAllList1)
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131 commonMetabolitesPpmAllList <- unique.data.frame(commonMetabolitesPpmAllList)
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132
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133 # initialisation des data.frame
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134 commonPpm <- data.frame()
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135 metaboliteAdd <- data.frame()
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136 metaboliteAddList <- data.frame()
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137 metabolite_ref <- data.frame()
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138 commonMetabolitesList <- data.frame()
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139 commonMetabolitesPpmList <- data.frame()
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140 commonMetabolitesPpmAllList1 <- data.frame()
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141 }
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142
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143 unicityAllList <- listeTotale_2D_unicite
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144 if (nrow(listeTotale_2D_unicite) != 0 & nrow(metabolitesAllUnicite) != 0) {
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145 unicityAllList <- setdiff(listeTotale_2D_unicite, metabolitesAllUnicite)
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146 }
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147
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148 unicitynbCouplesRectif <- data.frame()
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149 for (g in seq_len(nrow(unicityAllList))) {
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150 metaboliteUnicity <- (unicityAllList$Metabolite == unicityAllList$Metabolite[g])
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151 WhichMetaboliteUnicity <- which(metaboliteUnicity)
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152 nb_occurence <- length(WhichMetaboliteUnicity)
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153 unicitynbCouplesRectif <- rbind.data.frame(unicitynbCouplesRectif, nb_occurence)
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154 }
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155 names(unicitynbCouplesRectif) <- "NbCouplesAnnotes"
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156 unicityAllList <- cbind.data.frame(unicityAllList, unicitynbCouplesRectif)
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157
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158 unicityAllList <- cbind.data.frame(unicityAllList, score_unicite = unicityAllList$NbCouplesAnnotes / unicityAllList$theoricalLength)
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159 unicityAllList <- unicityAllList[, -3]
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160 unicityAllList <- unicityAllList[, -4]
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161
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162 unicityAllList <- unicityAllList[unicityAllList$score_unicite > seuil_score, ]
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163
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164 listeTotale_metabo <- data.frame()
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165 if (nrow(commonPpmList) != 0) {
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166 for (o in seq_len(length(commonPpmList[, 1]))) {
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167 tf6 <- (commonMetabolitesPpmAllList$ppm1 == commonPpmList[o, 1] & commonMetabolitesPpmAllList$ppm2 == commonPpmList[o, 2])
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168 w6 <- which(tf6)
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169
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170 for (s in seq_len(length(w6))) {
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171 metaboliteAdd <- data.frame(nom_metabolite = commonMetabolitesPpmAllList[w6[s], 3])
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172 commonMetabolitesList <- paste(commonMetabolitesList, metaboliteAdd[1, ], sep = " ")
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173 }
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174 liste_metabo_ppm <- cbind.data.frame(ppm1 = commonPpmList[o, 1], ppm2 = commonPpmList[o, 2], commonMetabolitesList)
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175 listeTotale_metabo <- rbind.data.frame(listeTotale_metabo, liste_metabo_ppm)
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176 commonMetabolitesList <- data.frame()
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177 }
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178 }
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179
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180 # Representation graphique
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181 if (nom_sequence == "HSQC" | nom_sequence == "HMBC") {
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182 atome <- "13C"
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183 indice_positif <- 1
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184 indice_negatif <- -10
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185 } else {
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186 atome <- "1H"
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187 indice_positif <- 0.5
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188 indice_negatif <- -0.5
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189 }
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190
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191 matriceComplexe <- matrixAnnotation
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192 ppm1 <- as.numeric(matriceComplexe[, 2])
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193 ppm2 <- as.numeric(matriceComplexe[, 3])
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194
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195 if (unicite == "NO") {
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196 listeTotale_2D_a_utiliser <- allMetabolitesList
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197 d1.ppm <- allMetabolitesList$ppm1
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198 d2.ppm <- allMetabolitesList$ppm2
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199 } else {
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200 listeTotale_2D_a_utiliser <- unicityAllList
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201 d1.ppm <- listeTotale_2D_a_utiliser$ppm1
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202 d2.ppm <- listeTotale_2D_a_utiliser$ppm2
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203 }
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204
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205 if (nrow(listeTotale_2D_a_utiliser) > 0) {
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206 ## Taches de correlations
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207 # Matrice biologique + Annotations
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208 maxX <- max(round(max(as.numeric(matriceComplexe[, 2]))) + 0.5, round(max(as.numeric(matriceComplexe[, 2]))))
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209 maxY <- max(round(max(as.numeric(matriceComplexe[, 3]))) + indice_positif, round(max(as.numeric(matriceComplexe[, 3]))))
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210 probability.score <- as.factor(round(listeTotale_2D_a_utiliser[, 4], 2))
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211 lgr <- length(unique(probability.score))
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212 sp <- ggplot(matriceComplexe, aes(x = ppm1, y = ppm2))
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213 sp <- sp + geom_point(size = 2) + scale_x_reverse(breaks = seq(maxX, 0, -0.5)) +
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214 scale_y_reverse(breaks = seq(maxY, 0, indice_negatif)) +
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215 xlab("1H chemical shift (ppm)") + ylab(paste(atome, " chemical shift (ppm)")) + ggtitle(nom_sequence) +
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216 geom_text(
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217 data = listeTotale_2D_a_utiliser, aes(d1.ppm, d2.ppm, label = str_to_lower(substr(listeTotale_2D_a_utiliser[, 3], 1, 3)), col = probability.score),
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218 size = 4, hjust = 0, nudge_x = 0.02, vjust = 0, nudge_y = 0.2
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219 ) + scale_colour_manual(values = viridis(lgr))
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220 print(sp)
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221 }
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222
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223 # Liste des resultats (couples pmm / metabolite / score) + liste ppms metabolites communs
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224 if (unicite == "NO") {
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225 return(list(liste_resultat = allMetabolitesList, listing_ppm_commun = listeTotale_metabo))
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226 } else {
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227 return(list(liste_resultat_unicite = unicityAllList, listing_ppm_commun_affichage = listeTotale_metabo))
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228 }
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229 }