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

comparison nmr_annotation2d/annotationRmn2D.R @ 0:8035235e46c7 draft

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author marie-tremblay-metatoul
date Mon, 23 Dec 2019 09:26:20 -0500
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1 ###########################################################################################################################################
2 # ANNOTATION SPECTRE 2D MATRICE COMPLEXE BASEE SUR UNE SEQUENCE RMN #
3 # matriceComplexe : data.frame liste couples ppm de la matrice a annoter #
4 # BdDStandards : objet contenant la base de donnees des composes standards #
5 # nom_séquence : nom sequence 2D a utiliser pour annotation ("JRES","COSY","TOCSY","HMBC","HSQC") #
6 # ppm1Tol : tolerance ppm axe abscisses #
7 # ppm2Tol : tolerance ppm axe ordonnees #
8 # nb_ligne_template : préciser le nombre total de ligne de la feuille de calcul à annoter #
9 ###########################################################################################################################################
10 annotationRmn2D <- function(matriceComplexe, BdDStandards, nom_sequence, ppm1Tol=0.01, ppm2Tol=0.01,
11 seuil=0, unicite="NO")
12 {
13 ## Longueur de la peak-list de la matrice a annoter
14 PeakListLength <- length(matriceComplexe[, 1])
15
16 ## Nombre de metabolites inclus dans BdD de composes standards
17 nbMetabolitesBdD <- length(BdDStandards)
18 matrixAnnotation <- data.frame()
19 allMetabolitesList <- data.frame()
20 seuil_score <- seuil
21
22 ## Boucle sur les metabolites inclus dans BdD
23 for (i in 1:nbMetabolitesBdD)
24 {
25 ## Infos metabolite en cours
26 iMetabolite <- BdDStandards[[i]]
27 ppm1M <- iMetabolite[,1]
28 ppm2M <- iMetabolite[,2]
29 nbPeakMetabolite <- length(ppm1M)
30 MetaboliteName <- names(BdDStandards[i])
31 ## print(MetaboliteName)
32 ## Initialisation
33 k <- 0
34 presenceScore <- 0
35 annotatedPpmRef <- data.frame()
36 annotatedPpmList <- data.frame()
37 annotatedPeakLength <- 0
38 metabolites <- data.frame()
39 metabolitesList <- data.frame()
40
41 ## Boucle sur les couples de pics de la matrice a annoter
42 for (p in 1:PeakListLength)
43 {
44 ppmAnnotationF1 <- as.numeric(matriceComplexe[p, 3])
45 ppmAnnotationF2 <- as.numeric(matriceComplexe[p, 2])
46 e <- simpleMessage("end of file")
47 tryCatch({
48 if (!is.na(ppmAnnotationF1))
49 {
50 matrixAnnotation <- unique.data.frame(rbind.data.frame(matrixAnnotation, matriceComplexe[p, ]))
51 }
52 # Recherche du couple de pics de la matrice la liste des couples du metabolite standard
53 metaboliteIn <- (ppm1M >= (ppmAnnotationF2-ppm1Tol) & ppm1M <= (ppmAnnotationF2+ppm1Tol) &
54 ppm2M >= (ppmAnnotationF1-ppm2Tol) & ppm2M <= (ppmAnnotationF1+ppm2Tol))
55 WhichMetaboliteIn <- which(metaboliteIn)
56 # Si au moins un couple de la matrice a annoter dans liste couples metabolite standard
57 if (length(WhichMetaboliteIn) > 0)
58 {
59 for (a in 1:length(WhichMetaboliteIn))
60 {
61 annotatedPpmList <- data.frame(ppm1=ppm1M[WhichMetaboliteIn[a]], ppm2=ppm2M[WhichMetaboliteIn[a]], theoricalLength=nbPeakMetabolite)
62 annotatedPpmRef <- rbind(annotatedPpmRef,annotatedPpmList)
63 }
64 }
65 }, error=function(e){cat ("End of file \n");})
66 }
67
68 # Au - 1 couple de ppm de la matrice complexe annote
69 if (nrow(annotatedPpmRef) >= 1)
70 {
71 ## Nombre couples annotes
72 annotatedPeakLength <- nrow(annotatedPpmRef)
73
74 ## Recherche doublons
75 annotatedDoublons <- duplicated(annotatedPpmRef)
76 if (sum(duplicated(annotatedPpmRef)) > 0)
77 {
78 annotatedPeakLength <- nrow(annotatedPpmRef) - sum(duplicated(annotatedPpmRef))
79 annotatedPpmRef <- annotatedPpmRef[-duplicated(annotatedPpmRef), ]
80 }
81 presenceScore <- annotatedPeakLength/nbPeakMetabolite
82 }
83
84 ## Conservation metabolites dont score > seuil
85 if (presenceScore > seuil_score)
86 {
87 metabolites <- data.frame(Metabolite=MetaboliteName, score=presenceScore)
88 metabolitesList <- cbind.data.frame(annotatedPpmRef, metabolites)
89 allMetabolitesList <- rbind.data.frame(allMetabolitesList, metabolitesList)
90 }
91 }
92
93 # Initialisation
94 commonPpm <- data.frame()
95 commonPpmList <- data.frame()
96 metaboliteAdd <- data.frame()
97 metaboliteAddList <- data.frame()
98 # metabolite_ref <- data.frame()
99 commonMetabolitesList <- data.frame()
100 commonMetabolitesPpmList <- data.frame()
101 commonMetabolitesPpmAllList1 <- data.frame()
102 commonMetabolitesPpmAllList <- data.frame()
103 listeTotale_2D_unicite <- allMetabolitesList[, 1:4]
104 allMetabolitesList <- allMetabolitesList[, -3]
105 metabolitesAllUnicite <- data.frame()
106
107 ## Boucle sur tous couples annotes
108 for (j in 1:length(allMetabolitesList$ppm1))
109 {
110 ## Boucle sur metabolites dans BdD composes standards
111 for (i in 1:nbMetabolitesBdD)
112 {
113 ppmMetaboliteBdD <- BdDStandards[[i]]
114 ppm1M <- ppmMetaboliteBdD[,1]
115 ppm2M <- ppmMetaboliteBdD[,2]
116 # Nombre de couples metabolite
117 nbPeakMetabolite <- length(ppm1M)
118 MetaboliteName <- names(BdDStandards[i])
119
120 metabolitesInAll <- (ppm1M >= (allMetabolitesList[j,1]-ppm1Tol) & ppm1M <= (allMetabolitesList[j,1]+ppm1Tol) &
121 ppm2M >= (allMetabolitesList[j,2]-ppm2Tol) & ppm2M <= (allMetabolitesList[j,2]+ppm2Tol))
122 WhichMetabolitesInAll <- which(metabolitesInAll)
123
124 if (MetaboliteName != allMetabolitesList[j, 3] & length(WhichMetabolitesInAll) > 0)
125 {
126 metabolitesAllUnicite <- rbind.data.frame(metabolitesAllUnicite, listeTotale_2D_unicite[j,])
127 commonPpm <- data.frame(ppm1=allMetabolitesList[j,1], ppm2=allMetabolitesList[j,2])
128 commonPpmList <- rbind.data.frame(commonPpmList, commonPpm)
129 commonPpmList <- unique(commonPpmList)
130 metaboliteAdd <- data.frame(nom_metabolite=MetaboliteName)
131 metaboliteAddList <- rbind.data.frame(metaboliteAddList, metaboliteAdd)
132 # metabolite_ref <- data.frame(nom_metabolite=allMetabolitesList[j,3])
133 commonMetabolitesList <- rbind.data.frame(data.frame(nom_metabolite=allMetabolitesList[j, 3]), metaboliteAddList)
134 commonMetabolitesPpmList <- cbind.data.frame(commonPpm, commonMetabolitesList)
135 commonMetabolitesPpmAllList1 <- rbind.data.frame(commonMetabolitesPpmAllList1, commonMetabolitesPpmList)
136 commonMetabolitesPpmAllList1 <- unique.data.frame(commonMetabolitesPpmAllList1)
137 }
138 }
139 commonMetabolitesPpmAllList <- rbind.data.frame(commonMetabolitesPpmAllList, commonMetabolitesPpmAllList1)
140 commonMetabolitesPpmAllList <- unique.data.frame(commonMetabolitesPpmAllList)
141
142 #initialisation des data.frame
143 commonPpm <- data.frame()
144 metaboliteAdd <- data.frame()
145 metaboliteAddList <- data.frame()
146 metabolite_ref <- data.frame()
147 commonMetabolitesList <- data.frame()
148 commonMetabolitesPpmList <- data.frame()
149 commonMetabolitesPpmAllList1 <- data.frame()
150 }
151
152 unicityAllList <- listeTotale_2D_unicite
153 if (nrow(listeTotale_2D_unicite)!=0 & nrow(metabolitesAllUnicite)!=0)
154 unicityAllList <- setdiff(listeTotale_2D_unicite, metabolitesAllUnicite)
155
156 unicitynbCouplesRectif <- data.frame()
157 for (g in 1:nrow(unicityAllList))
158 {
159 metaboliteUnicity <- (unicityAllList$Metabolite == unicityAllList$Metabolite[g])
160 WhichMetaboliteUnicity <- which(metaboliteUnicity)
161 nb_occurence <- length(WhichMetaboliteUnicity)
162 unicitynbCouplesRectif <- rbind.data.frame(unicitynbCouplesRectif, nb_occurence)
163 }
164 names(unicitynbCouplesRectif) <- "NbCouplesAnnotes"
165 unicityAllList <- cbind.data.frame(unicityAllList, unicitynbCouplesRectif)
166
167 unicityAllList <- cbind.data.frame(unicityAllList, score_unicite=unicityAllList$NbCouplesAnnotes/unicityAllList$theoricalLength)
168 unicityAllList <- unicityAllList[, -3]
169 unicityAllList <- unicityAllList[, -4]
170
171 ## unicityAllList <- filter(unicityAllList, unicityAllList$score_unicite > seuil_score)
172 unicityAllList <- unicityAllList[unicityAllList$score_unicite > seuil_score,]
173
174 listeTotale_metabo <- data.frame()
175 if (nrow(commonPpmList) !=0)
176 {
177 for (o in 1:length(commonPpmList[, 1]))
178 {
179 tf6 <- (commonMetabolitesPpmAllList$ppm1 == commonPpmList[o,1] & commonMetabolitesPpmAllList$ppm2 == commonPpmList[o,2])
180 w6 <- which(tf6)
181
182 for (s in 1:length(w6))
183 {
184 metaboliteAdd <- data.frame(nom_metabolite=commonMetabolitesPpmAllList[w6[s],3])
185 commonMetabolitesList <- paste(commonMetabolitesList, metaboliteAdd[1,], sep = " ")
186 }
187 liste_metabo_ppm <- cbind.data.frame(ppm1=commonPpmList[o,1],ppm2=commonPpmList[o,2], commonMetabolitesList)
188 listeTotale_metabo <- rbind.data.frame(listeTotale_metabo, liste_metabo_ppm)
189 commonMetabolitesList <- data.frame()
190 }
191 }
192
193 # Representation graphique
194 if (nom_sequence == "HSQC" | nom_sequence == "HMBC")
195 {
196 atome <- "13C"
197 indice_positif <- 1
198 indice_negatif <- -10
199 }else{
200 atome <- "1H"
201 indice_positif <- 0.5
202 indice_negatif <- -0.5
203 }
204
205 matriceComplexe <- matrixAnnotation
206 ppm1 <- as.numeric(matriceComplexe[,2])
207 ppm2 <- as.numeric(matriceComplexe[,3])
208
209 if (unicite == "NO")
210 {
211 listeTotale_2D_a_utiliser <- allMetabolitesList
212 d1.ppm <- allMetabolitesList$ppm1
213 d2.ppm <- allMetabolitesList$ppm2
214 }else{
215 listeTotale_2D_a_utiliser <- unicityAllList
216 d1.ppm <- listeTotale_2D_a_utiliser$ppm1
217 d2.ppm <- listeTotale_2D_a_utiliser$ppm2
218 }
219
220 if (nrow(listeTotale_2D_a_utiliser) > 0)
221 {
222 ## Taches de correlations
223 # Matrice biologique + Annotations
224 maxX <- max(round(max(as.numeric(matriceComplexe[,2])))+0.5, round(max(as.numeric(matriceComplexe[,2]))))
225 maxY <- max(round(max(as.numeric(matriceComplexe[,3])))+indice_positif, round(max(as.numeric(matriceComplexe[,3]))))
226 probability.score <- as.factor(round(listeTotale_2D_a_utiliser[,4],2))
227 lgr <- length(unique(probability.score))
228 sp <- ggplot(matriceComplexe, aes(x=ppm1, y=ppm2))
229 sp <- sp + geom_point(size=2) + scale_x_reverse(breaks=seq(maxX, 0, -0.5)) +
230 scale_y_reverse(breaks=seq(maxY, 0, indice_negatif)) +
231 xlab("1H chemical shift (ppm)") + ylab(paste(atome, " chemical shift (ppm)")) + ggtitle(nom_sequence) +
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)),
233 col=probability.score),
234 size=4, hjust=0, nudge_x=0.02, vjust=0, nudge_y=0.2) + scale_colour_manual(values=viridis(lgr))
235 ## scale_color_colormap('Annotation', discrete=T, reverse=T)
236 print(sp)
237 }
238
239 # Liste des résultats (couples pmm / metabolite / score) + liste ppms metabolites communs
240 if (unicite == "NO")
241 {
242 return(list(liste_resultat=allMetabolitesList, listing_ppm_commun=listeTotale_metabo))
243 }else{
244 return(list(liste_resultat_unicite=unicityAllList, listing_ppm_commun_affichage=listeTotale_metabo))
245 }
246 }