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1 ###########################################################################################################################################
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2 # ANNOTATION SPECTRE 2D MATRICE COMPLEXE BASEE SUR UNE (OU PLUSIEURS) SEQUENCE(s) RMN #
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3 # template : dataframe contenant la liste des couples de deplacements chimiques de la matrice complexe a annoter #
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4 # cosy : 1 si sequence a utiliser / 0 sinon #
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5 # hmbc : 1 si sequence a utiliser / 0 sinon #
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6 # hsqc : 1 si sequence a utiliser / 0 sinon #
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7 # jres : 1 si sequence a utiliser / 0 sinon #
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8 # tocsy : 1 si sequence a utiliser / 0 sinon #
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9 # tolPpm1 : tolerance autorisee autour de la valeur1 du couple de deplacements chimiques #
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10 # tolPpm2HJRes : tolerance autorisee autour de la valeur2 du couple de deplacements chimiques si H dans dimension 2 #
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11 # tolPpm2C : tolerance autorisee autour de la valeur2 du couple de deplacements chimiques si C dans dimension 2 #
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12 # seuil : valeur du score de presence en deça de laquelle les metabolites annotes ne sont pas retenus #
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13 # unicite : boolean pour ne retenir que les ... #
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14 ###########################################################################################################################################
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15 ## CALCUL MOYENNE SANS VALEUR(S) MANQUANTE(S)
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16 mean.rmNa <- function(x)
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17 {
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18 mean(x, na.rm=TRUE)
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19 }
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20
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21 annotationRmn2DGlobale <- function(template, tolPpm1=0.01, tolPpm2HJRes=0.002, tolPpm2C=0.5, cosy=1, hmbc=1, hsqc=1, jres=1, tocsy=1,
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22 seuil, unicite="NO")
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23 {
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24 ## Initialisation
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25 options (max.print=999999999)
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26 annotationCOSY <- data.frame()
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27 annotationHMBC <- data.frame()
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28 annotationHSQC <- data.frame()
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29 annotationJRES <- data.frame()
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30 annotationTOCSY <- data.frame()
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31
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32 dataCOSY <- "NA"
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33 dataHMBC <- "NA"
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34 dataHSQC <- "NA"
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35 dataJRES <- "NA"
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36 dataTOCSY <- "NA"
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37
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38 ## Application seuil seulement si annotation avec 1 seule sequence
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39 ## seuilPls2D <- 0
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40 ## if ((sum(cosy, hmbc, hsqc, jres, tocsy)) == 1)
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41 ## seuilPls2D <- seuil
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42 seuilPls2D <- seuil
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43
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44 if (cosy == 1)
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45 {
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46 matrice.cosy <- read.xlsx(template, sheet="COSY", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA")
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47 matrice.cosy <- matrice.cosy[matrice.cosy$peak.index != "x", ]
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48 annotationCOSY <- annotationRmn2D(matrice.cosy, BdDReference_COSY, "COSY", ppm1Tol=tolPpm1, ppm2Tol=tolPpm1, seuil=seuilPls2D,
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49 unicite=unicite)
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50 dataCOSY <- data.frame(Metabolite=str_to_lower(annotationCOSY$liste_resultat$Metabolite), score.COSY=annotationCOSY$liste_resultat$score)
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51 dataCOSY <- unique.data.frame(dataCOSY)
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52 }
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53
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54 if (hmbc == 1)
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55 {
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56 matrice.hmbc <- read.xlsx(template, sheet="HMBC", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA")
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57 matrice.hmbc <- matrice.hmbc[matrice.hmbc$peak.index != "x", ]
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58 annotationHMBC <- annotationRmn2D(matrice.hmbc, BdDReference_HMBC, "HMBC", ppm1Tol=tolPpm1, ppm2Tol=tolPpm2C, seuil=seuilPls2D,
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59 unicite=unicite)
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60 dataHMBC <- data.frame(Metabolite=str_to_lower(annotationHMBC$liste_resultat$Metabolite), score.HMBC=annotationHMBC$liste_resultat$score)
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61 dataHMBC <- unique.data.frame(dataHMBC)
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62 }
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63
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64 if (hsqc == 1)
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65 {
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66 matrice.hsqc <- read.xlsx(template, sheet="HSQC", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA")
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67 matrice.hsqc <- matrice.hsqc[matrice.hsqc$peak.index != "x", ]
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68 annotationHSQC <- annotationRmn2D(matrice.hsqc, BdDReference_HSQC, "HSQC", ppm1Tol=tolPpm1, ppm2Tol=tolPpm2C, seuil=seuilPls2D,
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69 unicite=unicite)
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70 dataHSQC <- data.frame(Metabolite=str_to_lower(annotationHSQC$liste_resultat$Metabolite), score.HSQC=annotationHSQC$liste_resultat$score)
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71 dataHSQC <- unique.data.frame(dataHSQC)
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72 }
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73
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74 if (jres == 1)
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75 {
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76 matrice.jres <- read.xlsx(template, sheet="JRES", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA")
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77 matrice.jres <- matrice.jres[matrice.jres$peak.index != "x", ]
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78 annotationJRES <- annotationRmn2D(matrice.jres, BdDReference_JRES, "JRES", ppm1Tol=tolPpm1, ppm2Tol=tolPpm2HJRes, seuil=seuilPls2D,
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79 unicite=unicite)
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80 dataJRES <- data.frame(Metabolite=str_to_lower(annotationJRES$liste_resultat$Metabolite), score.JRES=annotationJRES$liste_resultat$score)
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81 dataJRES <- unique.data.frame(dataJRES)
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82 }
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83
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84 if (tocsy == 1)
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85 {
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86 matrice.tocsy <- read.xlsx(template, sheet="TOCSY", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA")
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87 matrice.tocsy <- matrice.tocsy[matrice.tocsy$peak.index != "x", ]
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88 annotationTOCSY <- annotationRmn2D(matrice.tocsy, BdDReference_TOCSY, "TOCSY", ppm1Tol=tolPpm1, ppm2Tol=tolPpm1, seuil=seuilPls2D,
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89 unicite=unicite)
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90 dataTOCSY <- data.frame(Metabolite=str_to_lower(annotationTOCSY$liste_resultat$Metabolite), score.TOCSY=annotationTOCSY$liste_resultat$score)
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91 dataTOCSY <- unique.data.frame(dataTOCSY)
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92 }
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93
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94 sequencesCombinationAverageScoreSeuil <- data.frame()
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95 sequencesCombinationAverageScoreSeuilFiltre <- data.frame()
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96
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97 ## CONCATENATION RESULTATS DIFFERENTES SEQUENCES
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98 data2D <- list(dataCOSY, dataHMBC, dataHSQC, dataJRES, dataTOCSY)
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99 whichSequenceNaN <- which((data2D != "NA"))
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100 data2D <- data2D[whichSequenceNaN]
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101 sequencesCombination <- data.frame(data2D[1])
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102 sequencesCombinationAverageScore <- sequencesCombination
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103
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104 ## Si une seule sequence et seuil sur score = filtre applique dans la fonction annotationRmn2D
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105 if (length(data2D) >= 2)
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106 {
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107 ## CONCATENATION SCORE PAR SEQUENCE
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108 for (l in 2:length(data2D))
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109 sequencesCombination <- merge.data.frame(sequencesCombination, data2D[l], by="Metabolite", all.x=TRUE, all.y=TRUE)
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110
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111 ## SCORE MOYEN (sans prise en compte valeurs manquantes)
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112 meanScore <- apply(sequencesCombination[, -1], 1, FUN=mean.rmNa)
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113 sequencesCombinationAverageScore <- cbind.data.frame(sequencesCombination, averageScore=meanScore)
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114 ## SUPPRESSION METABOLITE AVEC SCORE MOYEN < SEUIL
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115 ## sequencesCombinationAverageScoreSeuilFiltre <- filter(sequencesCombinationAverageScore, averageScore >= seuil)
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116 sequencesCombinationAverageScoreSeuilFiltre <- sequencesCombinationAverageScore[sequencesCombinationAverageScore$averageScore > seuil, ]
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117 }
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118
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119 return(list(COSY=annotationCOSY, HMBC=annotationHMBC, HSQC=annotationHSQC, JRES=annotationJRES, TOCSY=annotationTOCSY,
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120 combination=sequencesCombinationAverageScoreSeuilFiltre))
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121 }
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