Mercurial > repos > marie-tremblay-metatoul > 2dnmrannotation
diff annotationRmn2D.R @ 4:cf11fa0c47c8 draft default tip
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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--- a/annotationRmn2D.R Fri Feb 04 09:01:11 2022 +0000 +++ b/annotationRmn2D.R Thu Jan 23 15:28:44 2025 +0000 @@ -1,223 +1,229 @@ -########################################################################## -# ANNOTATION SPECTRE 2D MATRICE COMPLEXE BASEE SUR UNE SEQUENCE RMN # -# matriceComplexe : data.frame liste couples ppm de la matrice a annoter # -# BdDStandards : objet contenant la base de donnees des composes standards # -# nom_sequence : nom sequence 2D a utiliser pour annotation ("JRES", "COSY", "TOCSY", "HMBC", "HSQC") # -# ppm1Tol : tolerance ppm axe abscisses # -# ppm2Tol : tolerance ppm axe ordonnees # -# nb_ligne_template : preciser le nombre total de ligne de la feuille de calcul a annoter # -####################################################################################################### -annotationRmn2D <- function(matriceComplexe, BdDStandards, nom_sequence, ppm1Tol = 0.01, ppm2Tol = 0.01, - seuil = 0, unicite = "NO") { - ## Longueur de la peak-list de la matrice a annoter - PeakListLength <- length(matriceComplexe[, 1]) - - ## Nombre de metabolites inclus dans BdD de composes standards - nbMetabolitesBdD <- length(BdDStandards) - matrixAnnotation <- data.frame() - allMetabolitesList <- data.frame() - seuil_score <- seuil - - ## Boucle sur les metabolites inclus dans BdD - for (i in seq_len(nbMetabolitesBdD)) { - ## Infos metabolite en cours - iMetabolite <- BdDStandards[[i]] - ppm1M <- iMetabolite[, 1] - ppm2M <- iMetabolite[, 2] - nbPeakMetabolite <- length(ppm1M) - MetaboliteName <- names(BdDStandards[i]) - - ## Initialisation - k <- 0 - presenceScore <- 0 - annotatedPpmRef <- data.frame() - annotatedPpmList <- data.frame() - annotatedPeakLength <- 0 - metabolites <- data.frame() - metabolitesList <- data.frame() - - ## Boucle sur les couples de pics de la matrice a annoter - for (p in seq_len(PeakListLength)) { - ppmAnnotationF1 <- as.numeric(matriceComplexe[p, 3]) - ppmAnnotationF2 <- as.numeric(matriceComplexe[p, 2]) - e <- simpleMessage("end of file") - tryCatch({ - if (!is.na(ppmAnnotationF1)) { - matrixAnnotation <- unique.data.frame(rbind.data.frame(matrixAnnotation, matriceComplexe[p, ])) - } - # Recherche du couple de pics de la matrice la liste des couples du metabolite standard - metaboliteIn <- (ppm1M >= (ppmAnnotationF2 - ppm1Tol) & ppm1M <= (ppmAnnotationF2 + ppm1Tol) & - ppm2M >= (ppmAnnotationF1 - ppm2Tol) & ppm2M <= (ppmAnnotationF1 + ppm2Tol)) - WhichMetaboliteIn <- which(metaboliteIn) - # Si au moins un couple de la matrice a annoter dans liste couples metabolite standard - if (length(WhichMetaboliteIn) > 0) { - for (a in seq_len(length(WhichMetaboliteIn))) { - annotatedPpmList <- data.frame(ppm1 = ppm1M[WhichMetaboliteIn[a]], ppm2 = ppm2M[WhichMetaboliteIn[a]], theoricalLength = nbPeakMetabolite) - annotatedPpmRef <- rbind(annotatedPpmRef, annotatedPpmList) - } - } - }, error = function(e) { - cat("End of file \n"); - }) - } - - # Au - 1 couple de ppm de la matrice complexe annote - if (nrow(annotatedPpmRef) >= 1) { - ## Nombre couples annotes - annotatedPeakLength <- nrow(annotatedPpmRef) - - ## Recherche doublons - annotatedDoublons <- duplicated(annotatedPpmRef) - if (sum(duplicated(annotatedPpmRef)) > 0) { - annotatedPeakLength <- nrow(annotatedPpmRef) - sum(duplicated(annotatedPpmRef)) - annotatedPpmRef <- annotatedPpmRef[-duplicated(annotatedPpmRef), ] - } - presenceScore <- round(annotatedPeakLength / nbPeakMetabolite, 2) - } - - ## Conservation metabolites dont score > seuil - if (presenceScore > seuil_score) { - metabolites <- data.frame(Metabolite = MetaboliteName, score = presenceScore) - metabolitesList <- cbind.data.frame(annotatedPpmRef, metabolites) - allMetabolitesList <- rbind.data.frame(allMetabolitesList, metabolitesList) - } - } - - # Initialisation - commonPpm <- data.frame() - commonPpmList <- data.frame() - metaboliteAdd <- data.frame() - metaboliteAddList <- data.frame() - commonMetabolitesList <- data.frame() - commonMetabolitesPpmList <- data.frame() - commonMetabolitesPpmAllList1 <- data.frame() - commonMetabolitesPpmAllList <- data.frame() - listeTotale_2D_unicite <- allMetabolitesList[, 1:4] - allMetabolitesList <- allMetabolitesList[, -3] - metabolitesAllUnicite <- data.frame() - - ## Boucle sur tous couples annotes - for (j in seq_len(length(allMetabolitesList$ppm1))) { - ## Boucle sur metabolites dans BdD composes standards - for (i in seq_len(nbMetabolitesBdD)) { - ppmMetaboliteBdD <- BdDStandards[[i]] - ppm1M <- ppmMetaboliteBdD[, 1] - ppm2M <- ppmMetaboliteBdD[, 2] - # Nombre de couples metabolite - nbPeakMetabolite <- length(ppm1M) - MetaboliteName <- names(BdDStandards[i]) - - metabolitesInAll <- (ppm1M >= (allMetabolitesList[j, 1] - ppm1Tol) & ppm1M <= (allMetabolitesList[j, 1] + ppm1Tol) & - ppm2M >= (allMetabolitesList[j, 2] - ppm2Tol) & ppm2M <= (allMetabolitesList[j, 2] + ppm2Tol)) - WhichMetabolitesInAll <- which(metabolitesInAll) - - if (MetaboliteName != allMetabolitesList[j, 3] & length(WhichMetabolitesInAll) > 0) { - metabolitesAllUnicite <- rbind.data.frame(metabolitesAllUnicite, listeTotale_2D_unicite[j, ]) - commonPpm <- data.frame(ppm1 = allMetabolitesList[j, 1], ppm2 = allMetabolitesList[j, 2]) - commonPpmList <- rbind.data.frame(commonPpmList, commonPpm) - commonPpmList <- unique(commonPpmList) - metaboliteAdd <- data.frame(nom_metabolite = MetaboliteName) - metaboliteAddList <- rbind.data.frame(metaboliteAddList, metaboliteAdd) - commonMetabolitesList <- rbind.data.frame(data.frame(nom_metabolite = allMetabolitesList[j, 3]), metaboliteAddList) - commonMetabolitesPpmList <- cbind.data.frame(commonPpm, commonMetabolitesList) - commonMetabolitesPpmAllList1 <- rbind.data.frame(commonMetabolitesPpmAllList1, commonMetabolitesPpmList) - commonMetabolitesPpmAllList1 <- unique.data.frame(commonMetabolitesPpmAllList1) - } - } - commonMetabolitesPpmAllList <- rbind.data.frame(commonMetabolitesPpmAllList, commonMetabolitesPpmAllList1) - commonMetabolitesPpmAllList <- unique.data.frame(commonMetabolitesPpmAllList) - - #initialisation des data.frame - commonPpm <- data.frame() - metaboliteAdd <- data.frame() - metaboliteAddList <- data.frame() - metabolite_ref <- data.frame() - commonMetabolitesList <- data.frame() - commonMetabolitesPpmList <- data.frame() - commonMetabolitesPpmAllList1 <- data.frame() - } - - unicityAllList <- listeTotale_2D_unicite - if (nrow(listeTotale_2D_unicite) != 0 & nrow(metabolitesAllUnicite) != 0) - unicityAllList <- setdiff(listeTotale_2D_unicite, metabolitesAllUnicite) - - unicitynbCouplesRectif <- data.frame() - for (g in seq_len(nrow(unicityAllList))) { - metaboliteUnicity <- (unicityAllList$Metabolite == unicityAllList$Metabolite[g]) - WhichMetaboliteUnicity <- which(metaboliteUnicity) - nb_occurence <- length(WhichMetaboliteUnicity) - unicitynbCouplesRectif <- rbind.data.frame(unicitynbCouplesRectif, nb_occurence) - } - names(unicitynbCouplesRectif) <- "NbCouplesAnnotes" - unicityAllList <- cbind.data.frame(unicityAllList, unicitynbCouplesRectif) - - unicityAllList <- cbind.data.frame(unicityAllList, score_unicite = unicityAllList$NbCouplesAnnotes / unicityAllList$theoricalLength) - unicityAllList <- unicityAllList[, -3] - unicityAllList <- unicityAllList[, -4] - - unicityAllList <- unicityAllList[unicityAllList$score_unicite > seuil_score, ] - - listeTotale_metabo <- data.frame() - if (nrow(commonPpmList) != 0) { - for (o in seq_len(length(commonPpmList[, 1]))) { - tf6 <- (commonMetabolitesPpmAllList$ppm1 == commonPpmList[o, 1] & commonMetabolitesPpmAllList$ppm2 == commonPpmList[o, 2]) - w6 <- which(tf6) - - for (s in seq_len(length(w6))) { - metaboliteAdd <- data.frame(nom_metabolite = commonMetabolitesPpmAllList[w6[s], 3]) - commonMetabolitesList <- paste(commonMetabolitesList, metaboliteAdd[1, ], sep = " ") - } - liste_metabo_ppm <- cbind.data.frame(ppm1 = commonPpmList[o, 1], ppm2 = commonPpmList[o, 2], commonMetabolitesList) - listeTotale_metabo <- rbind.data.frame(listeTotale_metabo, liste_metabo_ppm) - commonMetabolitesList <- data.frame() - } - } - - # Representation graphique - if (nom_sequence == "HSQC" | nom_sequence == "HMBC") { - atome <- "13C" - indice_positif <- 1 - indice_negatif <- -10 - } else { - atome <- "1H" - indice_positif <- 0.5 - indice_negatif <- -0.5 - } - - matriceComplexe <- matrixAnnotation - ppm1 <- as.numeric(matriceComplexe[, 2]) - ppm2 <- as.numeric(matriceComplexe[, 3]) - - if (unicite == "NO") { - listeTotale_2D_a_utiliser <- allMetabolitesList - d1.ppm <- allMetabolitesList$ppm1 - d2.ppm <- allMetabolitesList$ppm2 - } else { - listeTotale_2D_a_utiliser <- unicityAllList - d1.ppm <- listeTotale_2D_a_utiliser$ppm1 - d2.ppm <- listeTotale_2D_a_utiliser$ppm2 - } - - if (nrow(listeTotale_2D_a_utiliser) > 0) { - ## Taches de correlations - # Matrice biologique + Annotations - maxX <- max(round(max(as.numeric(matriceComplexe[, 2]))) + 0.5, round(max(as.numeric(matriceComplexe[, 2])))) - maxY <- max(round(max(as.numeric(matriceComplexe[, 3]))) + indice_positif, round(max(as.numeric(matriceComplexe[, 3])))) - probability.score <- as.factor(round(listeTotale_2D_a_utiliser[, 4], 2)) - lgr <- length(unique(probability.score)) - sp <- ggplot(matriceComplexe, aes(x = ppm1, y = ppm2)) - sp <- sp + geom_point(size = 2) + scale_x_reverse(breaks = seq(maxX, 0, -0.5)) + - scale_y_reverse(breaks = seq(maxY, 0, indice_negatif)) + - xlab("1H chemical shift (ppm)") + ylab(paste(atome, " chemical shift (ppm)")) + ggtitle(nom_sequence) + - geom_text(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), - size = 4, hjust = 0, nudge_x = 0.02, vjust = 0, nudge_y = 0.2) + scale_colour_manual(values = viridis(lgr)) - print(sp) - } - - # Liste des resultats (couples pmm / metabolite / score) + liste ppms metabolites communs - if (unicite == "NO") { - return(list(liste_resultat = allMetabolitesList, listing_ppm_commun = listeTotale_metabo)) - } else { - return(list(liste_resultat_unicite = unicityAllList, listing_ppm_commun_affichage = listeTotale_metabo)) - } -} +########################################################################## +# ANNOTATION SPECTRE 2D MATRICE COMPLEXE BASEE SUR UNE SEQUENCE RMN # +# matriceComplexe : data.frame liste couples ppm de la matrice a annoter # +# BdDStandards : objet contenant la base de donnees des composes standards # +# nom_sequence : nom sequence 2D a utiliser pour annotation ("JRES", "COSY", "TOCSY", "HMBC", "HSQC") # +# ppm1Tol : tolerance ppm axe abscisses # +# ppm2Tol : tolerance ppm axe ordonnees # +# nb_ligne_template : preciser le nombre total de ligne de la feuille de calcul a annoter # +####################################################################################################### +annotationRmn2D <- function(matriceComplexe, BdDStandards, nom_sequence, ppm1Tol = 0.01, ppm2Tol = 0.01, + seuil = 0, unicite = "NO") { + ## Longueur de la peak-list de la matrice a annoter + PeakListLength <- length(matriceComplexe[, 1]) + + ## Nombre de metabolites inclus dans BdD de composes standards + nbMetabolitesBdD <- length(BdDStandards) + matrixAnnotation <- data.frame() + allMetabolitesList <- data.frame() + seuil_score <- seuil + + ## Boucle sur les metabolites inclus dans BdD + for (i in seq_len(nbMetabolitesBdD)) { + ## Infos metabolite en cours + iMetabolite <- BdDStandards[[i]] + ppm1M <- iMetabolite[, 1] + ppm2M <- iMetabolite[, 2] + nbPeakMetabolite <- length(ppm1M) + MetaboliteName <- names(BdDStandards[i]) + + ## Initialisation + k <- 0 + presenceScore <- 0 + annotatedPpmRef <- data.frame() + annotatedPpmList <- data.frame() + annotatedPeakLength <- 0 + metabolites <- data.frame() + metabolitesList <- data.frame() + + ## Boucle sur les couples de pics de la matrice a annoter + for (p in seq_len(PeakListLength)) { + ppmAnnotationF1 <- as.numeric(matriceComplexe[p, 3]) + ppmAnnotationF2 <- as.numeric(matriceComplexe[p, 2]) + e <- simpleMessage("end of file") + tryCatch( + { + if (!is.na(ppmAnnotationF1)) { + matrixAnnotation <- unique.data.frame(rbind.data.frame(matrixAnnotation, matriceComplexe[p, ])) + } + # Recherche du couple de pics de la matrice la liste des couples du metabolite standard + metaboliteIn <- (ppm1M >= (ppmAnnotationF2 - ppm1Tol) & ppm1M <= (ppmAnnotationF2 + ppm1Tol) & + ppm2M >= (ppmAnnotationF1 - ppm2Tol) & ppm2M <= (ppmAnnotationF1 + ppm2Tol)) + WhichMetaboliteIn <- which(metaboliteIn) + # Si au moins un couple de la matrice a annoter dans liste couples metabolite standard + if (length(WhichMetaboliteIn) > 0) { + for (a in seq_len(length(WhichMetaboliteIn))) { + annotatedPpmList <- data.frame(ppm1 = ppm1M[WhichMetaboliteIn[a]], ppm2 = ppm2M[WhichMetaboliteIn[a]], theoricalLength = nbPeakMetabolite) + annotatedPpmRef <- rbind(annotatedPpmRef, annotatedPpmList) + } + } + }, + error = function(e) { + cat("End of file \n") + } + ) + } + + # Au - 1 couple de ppm de la matrice complexe annote + if (nrow(annotatedPpmRef) >= 1) { + ## Nombre couples annotes + annotatedPeakLength <- nrow(annotatedPpmRef) + + ## Recherche doublons + annotatedDoublons <- duplicated(annotatedPpmRef) + if (sum(duplicated(annotatedPpmRef)) > 0) { + annotatedPeakLength <- nrow(annotatedPpmRef) - sum(duplicated(annotatedPpmRef)) + annotatedPpmRef <- annotatedPpmRef[-duplicated(annotatedPpmRef), ] + } + presenceScore <- round(annotatedPeakLength / nbPeakMetabolite, 2) + } + + ## Conservation metabolites dont score > seuil + if (presenceScore > seuil_score) { + metabolites <- data.frame(Metabolite = MetaboliteName, score = presenceScore) + metabolitesList <- cbind.data.frame(annotatedPpmRef, metabolites) + allMetabolitesList <- rbind.data.frame(allMetabolitesList, metabolitesList) + } + } + + # Initialisation + commonPpm <- data.frame() + commonPpmList <- data.frame() + metaboliteAdd <- data.frame() + metaboliteAddList <- data.frame() + commonMetabolitesList <- data.frame() + commonMetabolitesPpmList <- data.frame() + commonMetabolitesPpmAllList1 <- data.frame() + commonMetabolitesPpmAllList <- data.frame() + listeTotale_2D_unicite <- allMetabolitesList[, 1:4] + allMetabolitesList <- allMetabolitesList[, -3] + metabolitesAllUnicite <- data.frame() + + ## Boucle sur tous couples annotes + for (j in seq_len(length(allMetabolitesList$ppm1))) { + ## Boucle sur metabolites dans BdD composes standards + for (i in seq_len(nbMetabolitesBdD)) { + ppmMetaboliteBdD <- BdDStandards[[i]] + ppm1M <- ppmMetaboliteBdD[, 1] + ppm2M <- ppmMetaboliteBdD[, 2] + # Nombre de couples metabolite + nbPeakMetabolite <- length(ppm1M) + MetaboliteName <- names(BdDStandards[i]) + + metabolitesInAll <- (ppm1M >= (allMetabolitesList[j, 1] - ppm1Tol) & ppm1M <= (allMetabolitesList[j, 1] + ppm1Tol) & + ppm2M >= (allMetabolitesList[j, 2] - ppm2Tol) & ppm2M <= (allMetabolitesList[j, 2] + ppm2Tol)) + WhichMetabolitesInAll <- which(metabolitesInAll) + + if (MetaboliteName != allMetabolitesList[j, 3] & length(WhichMetabolitesInAll) > 0) { + metabolitesAllUnicite <- rbind.data.frame(metabolitesAllUnicite, listeTotale_2D_unicite[j, ]) + commonPpm <- data.frame(ppm1 = allMetabolitesList[j, 1], ppm2 = allMetabolitesList[j, 2]) + commonPpmList <- rbind.data.frame(commonPpmList, commonPpm) + commonPpmList <- unique(commonPpmList) + metaboliteAdd <- data.frame(nom_metabolite = MetaboliteName) + metaboliteAddList <- rbind.data.frame(metaboliteAddList, metaboliteAdd) + commonMetabolitesList <- rbind.data.frame(data.frame(nom_metabolite = allMetabolitesList[j, 3]), metaboliteAddList) + commonMetabolitesPpmList <- cbind.data.frame(commonPpm, commonMetabolitesList) + commonMetabolitesPpmAllList1 <- rbind.data.frame(commonMetabolitesPpmAllList1, commonMetabolitesPpmList) + commonMetabolitesPpmAllList1 <- unique.data.frame(commonMetabolitesPpmAllList1) + } + } + commonMetabolitesPpmAllList <- rbind.data.frame(commonMetabolitesPpmAllList, commonMetabolitesPpmAllList1) + commonMetabolitesPpmAllList <- unique.data.frame(commonMetabolitesPpmAllList) + + # initialisation des data.frame + commonPpm <- data.frame() + metaboliteAdd <- data.frame() + metaboliteAddList <- data.frame() + metabolite_ref <- data.frame() + commonMetabolitesList <- data.frame() + commonMetabolitesPpmList <- data.frame() + commonMetabolitesPpmAllList1 <- data.frame() + } + + unicityAllList <- listeTotale_2D_unicite + if (nrow(listeTotale_2D_unicite) != 0 & nrow(metabolitesAllUnicite) != 0) { + unicityAllList <- setdiff(listeTotale_2D_unicite, metabolitesAllUnicite) + } + + unicitynbCouplesRectif <- data.frame() + for (g in seq_len(nrow(unicityAllList))) { + metaboliteUnicity <- (unicityAllList$Metabolite == unicityAllList$Metabolite[g]) + WhichMetaboliteUnicity <- which(metaboliteUnicity) + nb_occurence <- length(WhichMetaboliteUnicity) + unicitynbCouplesRectif <- rbind.data.frame(unicitynbCouplesRectif, nb_occurence) + } + names(unicitynbCouplesRectif) <- "NbCouplesAnnotes" + unicityAllList <- cbind.data.frame(unicityAllList, unicitynbCouplesRectif) + + unicityAllList <- cbind.data.frame(unicityAllList, score_unicite = unicityAllList$NbCouplesAnnotes / unicityAllList$theoricalLength) + unicityAllList <- unicityAllList[, -3] + unicityAllList <- unicityAllList[, -4] + + unicityAllList <- unicityAllList[unicityAllList$score_unicite > seuil_score, ] + + listeTotale_metabo <- data.frame() + if (nrow(commonPpmList) != 0) { + for (o in seq_len(length(commonPpmList[, 1]))) { + tf6 <- (commonMetabolitesPpmAllList$ppm1 == commonPpmList[o, 1] & commonMetabolitesPpmAllList$ppm2 == commonPpmList[o, 2]) + w6 <- which(tf6) + + for (s in seq_len(length(w6))) { + metaboliteAdd <- data.frame(nom_metabolite = commonMetabolitesPpmAllList[w6[s], 3]) + commonMetabolitesList <- paste(commonMetabolitesList, metaboliteAdd[1, ], sep = " ") + } + liste_metabo_ppm <- cbind.data.frame(ppm1 = commonPpmList[o, 1], ppm2 = commonPpmList[o, 2], commonMetabolitesList) + listeTotale_metabo <- rbind.data.frame(listeTotale_metabo, liste_metabo_ppm) + commonMetabolitesList <- data.frame() + } + } + + # Representation graphique + if (nom_sequence == "HSQC" | nom_sequence == "HMBC") { + atome <- "13C" + indice_positif <- 1 + indice_negatif <- -10 + } else { + atome <- "1H" + indice_positif <- 0.5 + indice_negatif <- -0.5 + } + + matriceComplexe <- matrixAnnotation + ppm1 <- as.numeric(matriceComplexe[, 2]) + ppm2 <- as.numeric(matriceComplexe[, 3]) + + if (unicite == "NO") { + listeTotale_2D_a_utiliser <- allMetabolitesList + d1.ppm <- allMetabolitesList$ppm1 + d2.ppm <- allMetabolitesList$ppm2 + } else { + listeTotale_2D_a_utiliser <- unicityAllList + d1.ppm <- listeTotale_2D_a_utiliser$ppm1 + d2.ppm <- listeTotale_2D_a_utiliser$ppm2 + } + + if (nrow(listeTotale_2D_a_utiliser) > 0) { + ## Taches de correlations + # Matrice biologique + Annotations + maxX <- max(round(max(as.numeric(matriceComplexe[, 2]))) + 0.5, round(max(as.numeric(matriceComplexe[, 2])))) + maxY <- max(round(max(as.numeric(matriceComplexe[, 3]))) + indice_positif, round(max(as.numeric(matriceComplexe[, 3])))) + probability.score <- as.factor(round(listeTotale_2D_a_utiliser[, 4], 2)) + lgr <- length(unique(probability.score)) + sp <- ggplot(matriceComplexe, aes(x = ppm1, y = ppm2)) + sp <- sp + geom_point(size = 2) + scale_x_reverse(breaks = seq(maxX, 0, -0.5)) + + scale_y_reverse(breaks = seq(maxY, 0, indice_negatif)) + + xlab("1H chemical shift (ppm)") + ylab(paste(atome, " chemical shift (ppm)")) + ggtitle(nom_sequence) + + geom_text( + 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), + size = 4, hjust = 0, nudge_x = 0.02, vjust = 0, nudge_y = 0.2 + ) + scale_colour_manual(values = viridis(lgr)) + print(sp) + } + + # Liste des resultats (couples pmm / metabolite / score) + liste ppms metabolites communs + if (unicite == "NO") { + return(list(liste_resultat = allMetabolitesList, listing_ppm_commun = listeTotale_metabo)) + } else { + return(list(liste_resultat_unicite = unicityAllList, listing_ppm_commun_affichage = listeTotale_metabo)) + } +}