Mercurial > repos > marie-tremblay-metatoul > 2dnmrannotation
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/.shed.yml Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,7 @@ +categories: [Metabolomics] +description: '[Metabolomics][W4M][NMR] BARSA - BidimensionAl nmR Spectra Annotation' +homepage_url: http://workflow4metabolomics.org +long_description: 'Part of the W4M project: http://workflow4metabolomics.org' +name: 2DNmrAnnotation +owner: marie-tremblay-metatoul +remote_repository_url: https://github.com/workflow4metabolomics/nmr_annotation2d
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/.travis.yml Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,17 @@ + +# This is a special configuration file to run tests on Travis-CI via +# GitHub notifications when changes are committed. +# +# See http://travis-ci.org/ for details +language: python + +before_install: + - sudo apt-get install -y python-virtualenv + - virtualenv planemo-venv + - . planemo-venv/bin/activate + - pip install --upgrade pip setuptools + - pip install planemo==0.37.0 + +script: + - planemo lint ${TRAVIS_BUILD_DIR}/galaxy/2DNmrAnnotation/ +# - planemo test --conda_auto_init --conda_auto_install --conda_dependency_resolution --galaxy_branch release_17.01 --no_cache_galaxy ${TRAVIS_BUILD_DIR}/galaxy/2DNmrAnnotation/
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/README.md Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,54 @@ +Bidimensional NMR annotation for Galaxy +======================================= + +[](http://bioconda.github.io) [](https://travis-ci.org/workflow4metabolomics/2DNmrAnnotation) + +Our project +----------- +The [Workflow4Metabolomics](http://workflow4metabolomics.org), W4M in short, is a French infrastructure offering software tool processing, analyzing and annotating metabolomics data. It is based on the Galaxy platform. + + +BARSA +----- + +Algorithm for Bidimensional NMR Spectra Annotation + +Galaxy +------ +Galaxy is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses. + +Homepage: [https://galaxyproject.org/](https://galaxyproject.org/) + + +Dependencies using Conda +------------------------ +[](http://bioconda.github.io) + +The main recipe: [https://github.com/bioconda/bioconda-recipes/tree/master/recipes/r-ptw](https://github.com/bioconda/bioconda-recipes/tree/master/recipes/r-ptw) + +``` +#To install miniconda2 +#http://conda.pydata.org/miniconda.html +#To install the needed R library using conda: +conda install r-batch r-dplyr r-ggplot2 r-openxlsx r-stringr r-tidyr + +#To set an environment: +conda create -n 2DNmrAnnotation r-dplyr r-ggplot2 r-openxlsx r-stringr r-tidyr + +#To activate the environment: +. activate 2DNmrAnnotation +``` + +[Conda](http://conda.pydata.org/) is package manager that among many other things can be used to manage Python packages. + +Travis +------ +[](https://travis-ci.org/workflow4metabolomics/2DNmrAnnotation) + +Test and Deploy with Confidence. Easily sync your GitHub projects with Travis CI and you'll be testing your code in minutes! + +Historic contributors +--------------------- + - Marie Tremblay-Franco @mtremblayfr - [French Metabolomics and Fluxomics Infrastructure (MetaboHUB)](http://www.metabohub.fr/en) - [MetaToul](http://www.metatoul.fr/) + - Coline Gardou +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/README.txt Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,53 @@ +2D-NMR annotation for Galaxy +============================ + +[](http://bioconda.github.io) [](https://travis-ci.org/workflow4metabolomics/nmr_annotation2d) + +Our project +----------- +The [Workflow4Metabolomics](http://workflow4metabolomics.org), W4M in short, is a French infrastructure offering software tool processing, analyzing and annotating metabolomics data. It is based on the Galaxy platform. + + +2D-NMR annotation +----------------- + +Annotation of 2D NMR spectra + +Galaxy +------ +Galaxy is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses. + +Homepage: [https://galaxyproject.org/](https://galaxyproject.org/) + + +Dependencies using Conda +------------------------ +[](http://bioconda.github.io) + +The main recipe: [https://github.com/bioconda/bioconda-recipes/tree/master/recipes/r-ptw](https://github.com/bioconda/bioconda-recipes/tree/master/recipes/r-ptw) + +``` +#To install miniconda2 +#http://conda.pydata.org/miniconda.html +#To install the needed R library using conda: +conda install r-batch r-ptw +#To set an environment: +conda create -n nmr_annotation2d r-batch openxlsx dplyr tidyr ggplot2 colormap stringr` + +#To activate the environment: +. activate nmr_annotation2d +``` + +[Conda](http://conda.pydata.org/) is package manager that among many other things can be used to manage Python packages. + +Travis +------ +[](https://travis-ci.org/workflow4metabolomics/nmr_annotation2d) + +Test and Deploy with Confidence. Easily sync your GitHub projects with Travis CI and you'll be testing your code in minutes! + +Historic contributors +--------------------- + - Marie Tremblay-Franco @mtremblayfr - [French Metabolomics and Fluxomics Infrastructure (MetaboHUB)](http://www.metabohub.fr/en) - [MetaToul](http://www.metatoul.fr/) + - Coline Gardou +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/annotationRmn2D.R Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,246 @@ +########################################################################################################################################### +# 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_séquence : 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 : préciser le nombre total de ligne de la feuille de calcul à 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 1:nbMetabolitesBdD) + { + ## Infos metabolite en cours + iMetabolite <- BdDStandards[[i]] + ppm1M <- iMetabolite[,1] + ppm2M <- iMetabolite[,2] + nbPeakMetabolite <- length(ppm1M) + MetaboliteName <- names(BdDStandards[i]) +## print(MetaboliteName) + ## 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 1: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 1: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 <- annotatedPeakLength/nbPeakMetabolite + } + + ## 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() +# metabolite_ref <- 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 1:length(allMetabolitesList$ppm1)) + { + ## Boucle sur metabolites dans BdD composes standards + for (i in 1: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) +# metabolite_ref <- data.frame(nom_metabolite=allMetabolitesList[j,3]) + 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 1: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 <- filter(unicityAllList, unicityAllList$score_unicite > seuil_score) + unicityAllList <- unicityAllList[unicityAllList$score_unicite > seuil_score,] + + listeTotale_metabo <- data.frame() + if (nrow(commonPpmList) !=0) + { + for (o in 1:length(commonPpmList[, 1])) + { + tf6 <- (commonMetabolitesPpmAllList$ppm1 == commonPpmList[o,1] & commonMetabolitesPpmAllList$ppm2 == commonPpmList[o,2]) + w6 <- which(tf6) + + for (s in 1: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)) +## scale_color_colormap('Annotation', discrete=T, reverse=T) + print(sp) + } + + # Liste des résultats (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)) + } +} \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/annotationRmn2DGlobale.R Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,121 @@ +########################################################################################################################################### +# ANNOTATION SPECTRE 2D MATRICE COMPLEXE BASEE SUR UNE (OU PLUSIEURS) SEQUENCE(s) RMN # +# template : dataframe contenant la liste des couples de deplacements chimiques de la matrice complexe a annoter # +# cosy : 1 si sequence a utiliser / 0 sinon # +# hmbc : 1 si sequence a utiliser / 0 sinon # +# hsqc : 1 si sequence a utiliser / 0 sinon # +# jres : 1 si sequence a utiliser / 0 sinon # +# tocsy : 1 si sequence a utiliser / 0 sinon # +# tolPpm1 : tolerance autorisee autour de la valeur1 du couple de deplacements chimiques # +# tolPpm2HJRes : tolerance autorisee autour de la valeur2 du couple de deplacements chimiques si H dans dimension 2 # +# tolPpm2C : tolerance autorisee autour de la valeur2 du couple de deplacements chimiques si C dans dimension 2 # +# seuil : valeur du score de presence en deça de laquelle les metabolites annotes ne sont pas retenus # +# unicite : boolean pour ne retenir que les ... # +########################################################################################################################################### +## CALCUL MOYENNE SANS VALEUR(S) MANQUANTE(S) +mean.rmNa <- function(x) +{ + mean(x, na.rm=TRUE) +} + +annotationRmn2DGlobale <- function(template, tolPpm1=0.01, tolPpm2HJRes=0.002, tolPpm2C=0.5, cosy=1, hmbc=1, hsqc=1, jres=1, tocsy=1, + seuil, unicite="NO") +{ + ## Initialisation + options (max.print=999999999) + annotationCOSY <- data.frame() + annotationHMBC <- data.frame() + annotationHSQC <- data.frame() + annotationJRES <- data.frame() + annotationTOCSY <- data.frame() + + dataCOSY <- "NA" + dataHMBC <- "NA" + dataHSQC <- "NA" + dataJRES <- "NA" + dataTOCSY <- "NA" + + ## Application seuil seulement si annotation avec 1 seule sequence +## seuilPls2D <- 0 +## if ((sum(cosy, hmbc, hsqc, jres, tocsy)) == 1) +## seuilPls2D <- seuil + seuilPls2D <- seuil + + if (cosy == 1) + { + matrice.cosy <- read.xlsx(template, sheet="COSY", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA") + matrice.cosy <- matrice.cosy[matrice.cosy$peak.index != "x", ] + annotationCOSY <- annotationRmn2D(matrice.cosy, BdDReference_COSY, "COSY", ppm1Tol=tolPpm1, ppm2Tol=tolPpm1, seuil=seuilPls2D, + unicite=unicite) + dataCOSY <- data.frame(Metabolite=str_to_lower(annotationCOSY$liste_resultat$Metabolite), score.COSY=annotationCOSY$liste_resultat$score) + dataCOSY <- unique.data.frame(dataCOSY) + } + + if (hmbc == 1) + { + matrice.hmbc <- read.xlsx(template, sheet="HMBC", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA") + matrice.hmbc <- matrice.hmbc[matrice.hmbc$peak.index != "x", ] + annotationHMBC <- annotationRmn2D(matrice.hmbc, BdDReference_HMBC, "HMBC", ppm1Tol=tolPpm1, ppm2Tol=tolPpm2C, seuil=seuilPls2D, + unicite=unicite) + dataHMBC <- data.frame(Metabolite=str_to_lower(annotationHMBC$liste_resultat$Metabolite), score.HMBC=annotationHMBC$liste_resultat$score) + dataHMBC <- unique.data.frame(dataHMBC) + } + + if (hsqc == 1) + { + matrice.hsqc <- read.xlsx(template, sheet="HSQC", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA") + matrice.hsqc <- matrice.hsqc[matrice.hsqc$peak.index != "x", ] + annotationHSQC <- annotationRmn2D(matrice.hsqc, BdDReference_HSQC, "HSQC", ppm1Tol=tolPpm1, ppm2Tol=tolPpm2C, seuil=seuilPls2D, + unicite=unicite) + dataHSQC <- data.frame(Metabolite=str_to_lower(annotationHSQC$liste_resultat$Metabolite), score.HSQC=annotationHSQC$liste_resultat$score) + dataHSQC <- unique.data.frame(dataHSQC) + } + + if (jres == 1) + { + matrice.jres <- read.xlsx(template, sheet="JRES", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA") + matrice.jres <- matrice.jres[matrice.jres$peak.index != "x", ] + annotationJRES <- annotationRmn2D(matrice.jres, BdDReference_JRES, "JRES", ppm1Tol=tolPpm1, ppm2Tol=tolPpm2HJRes, seuil=seuilPls2D, + unicite=unicite) + dataJRES <- data.frame(Metabolite=str_to_lower(annotationJRES$liste_resultat$Metabolite), score.JRES=annotationJRES$liste_resultat$score) + dataJRES <- unique.data.frame(dataJRES) + } + + if (tocsy == 1) + { + matrice.tocsy <- read.xlsx(template, sheet="TOCSY", startRow=2, colNames=TRUE, rowNames=FALSE, cols=1:3, na.strings="NA") + matrice.tocsy <- matrice.tocsy[matrice.tocsy$peak.index != "x", ] + annotationTOCSY <- annotationRmn2D(matrice.tocsy, BdDReference_TOCSY, "TOCSY", ppm1Tol=tolPpm1, ppm2Tol=tolPpm1, seuil=seuilPls2D, + unicite=unicite) + dataTOCSY <- data.frame(Metabolite=str_to_lower(annotationTOCSY$liste_resultat$Metabolite), score.TOCSY=annotationTOCSY$liste_resultat$score) + dataTOCSY <- unique.data.frame(dataTOCSY) + } + + sequencesCombinationAverageScoreSeuil <- data.frame() + sequencesCombinationAverageScoreSeuilFiltre <- data.frame() + + ## CONCATENATION RESULTATS DIFFERENTES SEQUENCES + data2D <- list(dataCOSY, dataHMBC, dataHSQC, dataJRES, dataTOCSY) + whichSequenceNaN <- which((data2D != "NA")) + data2D <- data2D[whichSequenceNaN] + sequencesCombination <- data.frame(data2D[1]) + sequencesCombinationAverageScore <- sequencesCombination + + ## Si une seule sequence et seuil sur score = filtre applique dans la fonction annotationRmn2D + if (length(data2D) >= 2) + { + ## CONCATENATION SCORE PAR SEQUENCE + for (l in 2:length(data2D)) + sequencesCombination <- merge.data.frame(sequencesCombination, data2D[l], by="Metabolite", all.x=TRUE, all.y=TRUE) + + ## SCORE MOYEN (sans prise en compte valeurs manquantes) + meanScore <- apply(sequencesCombination[, -1], 1, FUN=mean.rmNa) + sequencesCombinationAverageScore <- cbind.data.frame(sequencesCombination, averageScore=meanScore) + ## SUPPRESSION METABOLITE AVEC SCORE MOYEN < SEUIL +## sequencesCombinationAverageScoreSeuilFiltre <- filter(sequencesCombinationAverageScore, averageScore >= seuil) + sequencesCombinationAverageScoreSeuilFiltre <- sequencesCombinationAverageScore[sequencesCombinationAverageScore$averageScore > seuil, ] + } + + return(list(COSY=annotationCOSY, HMBC=annotationHMBC, HSQC=annotationHSQC, JRES=annotationJRES, TOCSY=annotationTOCSY, + combination=sequencesCombinationAverageScoreSeuilFiltre)) +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/annotationRmn2DWrapper.R Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,227 @@ +#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file + +## 201919016 2DNmrAnnotation_1.0.0.R +## Marie Tremblay-Franco +## MetaboHUB: The French Infrastructure for Metabolomics and Fluxomics +## www.metabohub.fr/en +## marie.tremblay-franco@toulouse.inra.fr + +runExampleL <- FALSE + +if(runExampleL) { +##------------------------------ +## Example of arguments +##------------------------------ +} + + +##------------------------------ +## Options +##------------------------------ +strAsFacL <- options()$stringsAsFactors +options(stringsAsFactors = FALSE) + +##------------------------------ +## Constants +##------------------------------ +topEnvC <- environment() +flagC <- "\n" + + +##------------------------- +## Input parameters reading +##------------------------- + +##------------------------------ +## R libraries laoding +##------------------------------ +library(batch) +library(dplyr) +library(ggplot2) +library(openxlsx) +library(stringr) +library(tidyr) + +if(!runExampleL) + argLs <- parseCommandArgs(evaluate=FALSE) +logFile <- argLs[["logOut"]] +sink(logFile) + +cat("\tPACKAGE INFO\n") +sessionInfo() + +##------------------------------ +## Functions +##------------------------------ +source_local <- function(fname) +{ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +#Import the different functions +source_local("annotationRmn2D.R") +source_local("annotationRmn2DGlobale.R") +source_local("viridis.R") + +## Input parameter values +fileToAnnotate <- argLs[[1]] + # Chosen sequence(s) +cosy <- 0 +hmbc <- 0 +hsqc <- 0 +jres <- 0 +tocsy <- 0 +## sequences <- str_split(argLs[[2]], ",")[[1]] +## for (s in 1:length(sequences)) +## { +## argv <- commandArgs(trailingOnly = FALSE) +## currentDir <- dirname(substring(argv[grep("--file=", argv)], 8)) +## if (sequences[s]=="cosy"){ +## cosy <- 1 +## load(paste(currentDir, "BdDReference_COSY.RData", sep="/")) +## }else if(sequences[s]=="hmbc"){ +## hmbc <- 1 +## load(paste(currentDir, "BdDReference_HMBC.RData", sep="/")) +## }else if(sequences[s]=="hsqc"){ +## hsqc <- 1 +## load(paste(currentDir, "BdDReference_HSQC.RData", sep="/")) +## }else if(sequences[s]=="jres"){ +## jres <- 1 +## load(paste(currentDir, "BdDReference_JRES.RData", sep="/")) +## }else if(sequences[s]=="tocsy"){ +## tocsy <- 1 +## load(paste(currentDir, "BdDReference_TOCSY.RData", sep="/")) +## }else +## stop("No chosen sequence", call.=FALSE) +## } + +if (argLs[[2]]=='yes') +{ + argv <- commandArgs(trailingOnly = FALSE) + currentDir <- dirname(substring(argv[grep("--file=", argv)], 8)) + cosy <- 1 + load(paste(currentDir, "BdDReference_COSY.RData", sep="/")) +} + +if (argLs[[3]]=='yes') +{ + argv <- commandArgs(trailingOnly = FALSE) + currentDir <- dirname(substring(argv[grep("--file=", argv)], 8)) + jres <- 1 + load(paste(currentDir, "BdDReference_JRES.RData", sep="/")) +} + +if (argLs[[4]]=='yes') +{ + argv <- commandArgs(trailingOnly = FALSE) + currentDir <- dirname(substring(argv[grep("--file=", argv)], 8)) + hmbc <- 1 + load(paste(currentDir, "BdDReference_HMBC.RData", sep="/")) +} + +if (argLs[[5]]=='yes') +{ + argv <- commandArgs(trailingOnly = FALSE) + currentDir <- dirname(substring(argv[grep("--file=", argv)], 8)) + hsqc <- 1 + load(paste(currentDir, "BdDReference_HSQC.RData", sep="/")) +} + +if (argLs[[6]]=='yes') +{ + argv <- commandArgs(trailingOnly = FALSE) + currentDir <- dirname(substring(argv[grep("--file=", argv)], 8)) + tocsy <- 1 + load(paste(currentDir, "BdDReference_TOCSY.RData", sep="/")) +} + +if (argLs[[2]]=='no' & argLs[[3]]=='no' & argLs[[4]]=='no' & argLs[[5]]=='no' & argLs[[6]]=='no') + stop("No chosen sequence", call.=FALSE) + + + # User database + + + # Allowed chemical shifts +tolPpm1 <- argLs$tolppm1 +tolPpm2HJRes <- argLs$tolppmJRES +tolPpm2C <- argLs$tolppm2 + # Threshold to remove metabolites (probability score < threshold) +seuil <- argLs$threshold +# Remove metabolites when multiple assignations? +unicite <- str_to_upper(argLs$unicity) + +## Output paramater values +AnnotationGraph <- argLs[["AnnotationGraph"]] + +print(argLs) + +## ANNOTATION +st0=Sys.time() +pdf(AnnotationGraph,onefile=TRUE) +annotationMelange <- annotationRmn2DGlobale(fileToAnnotate, tolPpm1=tolPpm1, tolPpm2HJRes=tolPpm2HJRes, + tolPpm2C=tolPpm2C, cosy=cosy, hmbc=hmbc, hsqc=hsqc, + jres=jres, tocsy=tocsy, seuil=seuil, unicite=unicite) +dev.off() + +if (cosy==1) +{ + write.table(annotationMelange$COSY$liste_resultat, file=argLs[["annotationCOSY"]], quote=FALSE, + row.names=FALSE,sep="\t") + if (nrow(annotationMelange$COSY$listing_ppm_commun) != 0) + write.table(annotationMelange$COSY$listing_ppm_commun, file=argLs[["ppmCommunCOSY"]], quote=FALSE, + row.names=FALSE,sep="\t") +} + +if (hmbc==1) +{ + write.table(annotationMelange$HMBC$liste_resultat, file=argLs[["annotationHMBC"]], quote=FALSE, + row.names=FALSE,sep="\t") + if (nrow(annotationMelange$HMBC$listing_ppm_commun) != 0) + write.table(annotationMelange$HMBC$listing_ppm_commun, file=argLs[["ppmCommunHMBC"]], quote=FALSE, + row.names=FALSE,sep="\t") +} + +if (hsqc==1) +{ + write.table(annotationMelange$HSQC$liste_resultat, file=argLs[["annotationHSQC"]], quote=FALSE, + row.names=FALSE,sep="\t") + if (nrow(annotationMelange$HSQC$listing_ppm_commun) != 0) + write.table(annotationMelange$HSQC$listing_ppm_commun, file=argLs[["ppmCommunHSQC"]], quote=FALSE, + row.names=FALSE,sep="\t") +} + +if (jres==1) +{ + write.table(annotationMelange$JRES$liste_resultat, file=argLs[["annotationJRES"]], quote=FALSE, + row.names=FALSE,sep="\t") + if (nrow(annotationMelange$JRES$listing_ppm_commun) != 0) + write.table(annotationMelange$JRES$listing_ppm_commun, file=argLs[["ppmCommunJRES"]], quote=FALSE, + row.names=FALSE,sep="\t") +} + +if (tocsy==1) +{ + write.table(annotationMelange$TOCSY$liste_resultat, file=argLs[["annotationTOCSY"]], quote=FALSE, + row.names=FALSE,sep="\t") + if (nrow(annotationMelange$TOCSY$listing_ppm_commun) != 0) + write.table(annotationMelange$TOCSY$listing_ppm_commun, file=argLs[["ppmCommunTOCSY"]], quote=FALSE, + row.names=FALSE,sep="\t") +} + +## Combinaison de sequences +if (cosy + jres + hmbc + hsqc + tocsy > 1) +{ + write.table(annotationMelange$combination, file=argLs[["annotationCombination"]], quote=FALSE, + row.names=FALSE,sep="\t") +} +st1=Sys.time() +print(st1-st0) + +## Ending +##-------- +cat("\nEnd of '2D NMR annotation' Galaxy module call: ", as.character(Sys.time()), sep = "") +sink() +options(stringsAsFactors = strAsFacL) +rm(list = ls())
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/annotationRmn2D_xml.xml Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,376 @@ +<tool id="2DNmrAnnotation" name="2DNMR_Annotation" version="1.0.0"> + + <description> Annotation of complex mixture bidimensional NMR spectra </description> + + <stdio> + <exit_code range="1:" level="fatal" /> + </stdio> + + <command> + ## Wrapper + Libraries of 2D-NMR sequences for reference compounds + Rscript '$__tool_directory__/annotationRmn2DWrapper.R' + + + ## XLS file + xlsfile $zip_xlsfile + + ## 2D-NMR sequences to annotate + cosy_2dsequences $cosy_2dsequences + jres_2dsequences $jres_2dsequences + hmbc_2dsequences $hmbc_2dsequences + hsqc_2dsequences $hsqc_2dsequences + tocsy_2dsequences $tocsy_2dsequences + + ## In-house databases + inHouse_DB_choices.choice ${inHouse_DB_choices.choice} + #if str($inHouse_DB_choices.choice) == 'yes': + inHouse_DB_cosy.choice ${inHouse_DB_cosy.choice} + #if str($inHouse_DB_cosy.choice) == 'yes': + cosyDB $cosyDB + #end if + inHouse_DB_hmbc.choice ${inHouse_DB_hmbc.choice} + #if str($inHouse_DB_hmbc.choice) == 'yes': + hmbcDB $hmbcDB + #end if + inHouse_DB_hsqc.choice ${inHouse_DB_hsqc.choice} + #if str($inHouse_DB_hsqc.choice) == 'yes': + hsqcDB $hsqcDB + #end if + inHouse_DB_jres.choice ${inHouse_DB_jres.choice} + #if str($inHouse_DB_jres.choice) == 'yes': + jresDB $jresDB + #end if + inHouse_DB_tocsy.choice ${inHouse_DB_tocsy.choice} + #if str($inHouse_DB_tocsy.choice) == 'yes': + tocsyDB $tocsyDB + #end if + #end if + + ## Tolerances + tolppm1 $tolppm1 + tolppm2 $tolppm2 + tolppmJRES $tolppmJRES + + + ## Treshold (probability score) + threshold $threshold + + ## Unicity + unicity $unicity + + ## Outputs + logOut $logOut + annotationCOSY $annotationCOSY + ppmCommunCOSY $ppmCommunCOSY + annotationJRES $annotationJRES + ppmCommunJRES $ppmCommunJRES + annotationHMBC $annotationHMBC + ppmCommunHMBC $ppmCommunHMBC + annotationHSQC $annotationHSQC + ppmCommunHSQC $ppmCommunHSQC + annotationTOCSY $annotationTOCSY + ppmCommunTOCSY $ppmCommunTOCSY + annotationCombination $annotationCombination + AnnotationGraph $AnnotationGraph + + </command> + + <inputs> + <param name="zip_xlsfile" type="data" format="xlsx" label="File to annotate in xlsx format" /> + + <param name="cosy_2dsequences" type="select" label="2D-NMR COSY sequence"> + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <param name="jres_2dsequences" type="select" label="2D-NMR JRES sequence"> + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <param name="hmbc_2dsequences" type="select" label="2D-NMR HMBC sequence"> + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <param name="hsqc_2dsequences" type="select" label="2D-NMR HSQC sequence"> + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <param name="tocsy_2dsequences" type="select" label="2D-NMR TOCSY sequence"> + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + + <conditional name="inHouse_DB_choices"> + <param name="choice" type="select" label="In-house database" help="Choose if you want to use use in-house database to annotate" > + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <when value="yes"> + <conditional name="inHouse_DB_cosy"> + <param name="choice" type="select" label="COSY In-house database" help="Choose if you want to use use in-house database to annotate COSY sequence" > + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <when value="yes"> + <param name="cosyDB" type="data" format="no_unzip.zip" label="Zip file of the COSY RData object" /> + </when> + </conditional> + <conditional name="inHouse_DB_hmbc"> + <param name="choice" type="select" label="HMBC In-house database" help="Choose if you want to use use in-house database to annotate HMBC sequence" > + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <when value="yes"> + <param name="hmbcDB" type="data" format="no_unzip.zip" label="Zip file of the HMBC RData object" /> + </when> + </conditional> <conditional name="inHouse_DB_hsqc"> + <param name="choice" type="select" label="HSQC In-house database" help="Choose if you want to use use in-house database to annotate HSQC sequence" > + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <when value="yes"> + <param name="hsqcDB" type="data" format="no_unzip.zip" label="Zip file of the HSQC RData object" /> + </when> + </conditional> <conditional name="inHouse_DB_jres"> + <param name="choice" type="select" label="JRES In-house database" help="Choose if you want to use use in-house database to annotate JRES sequence" > + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <when value="yes"> + <param name="jresDB" type="data" format="no_unzip.zip" label="Zip file of the JRES RData object" /> + </when> + </conditional> + <conditional name="inHouse_DB_tocsy"> + <param name="choice" type="select" label="TOCSY In-house database" help="Choose if you want to use use in-house database to annotate TOCSY sequence" > + <option value="yes" > yes </option> + <option value="no" selected="true"> no </option> + </param> + <when value="yes"> + <param name="tocsyDB" type="data" format="no_unzip.zip" label="Zip file of the TOCSY RData object" /> + </when> + </conditional> + </when> + <when value="no" /> + </conditional> + + <param name="tolppm1" type="float" value="0.01" help="Tolerance on chemical shift for the x-axis (H). Default value is 0.01ppm" /> + <param name="tolppm2" type="float" value="0.5" help="Tolerance on chemical shift for the y-axis (C). Default value is 0.01ppm" /> + <param name="tolppmJRES" type="float" value="0.002" help="Tolerance on chemical shift for the y-axis for the JRES sequence. Default value is 0.002 (Hz)" /> + + <param name="threshold" type="float" value="0" help="Treshold on score of presence. Default value is 0" /> + + <param name="unicity" label="Unicity of annotation" type="select" display="radio" help=""> + <option value="no">No</option> + <option value="yes"></option> + </param> + + </inputs> + + <outputs> + <data format="txt" name="logOut" label="${tool.name}_log" /> + <data format="tabular" name="annotationCOSY" label="annotationCosy" > + <filter> cosy_2dsequences != "no" </filter> + </data> + <data format="tabular" name="ppmCommunCOSY" label="duplicateCosy" > + <filter> cosy_2dsequences != "no" </filter> + </data> + + <data format="tabular" name="annotationJRES" label="annotationJres" > + <filter> jres_2dsequences != "no" </filter> + </data> + <data format="tabular" name="ppmCommunJRES" label="duplicateJres" > + <filter> jres_2dsequences != "no" </filter> + </data> + + <data format="tabular" name="annotationHMBC" label="annotationHmbc" > + <filter> hmbc_2dsequences != "no" </filter> + </data> + <data format="tabular" name="ppmCommunHMBC" label="duplicateHmbc" > + <filter> hmbc_2dsequences != "no" </filter> + </data> + + <data format="tabular" name="annotationHSQC" label="annotationHsqc" > + <filter> hsqc_2dsequences != "no" </filter> + </data> + <data format="tabular" name="ppmCommunHSQC" label="duplicateHsqc" > + <filter> hsqc_2dsequences != "no" </filter> + </data> + + <data format="tabular" name="annotationTOCSY" label="annotationTocsy" > + <filter> tocsy_2dsequences != "no" </filter> + </data> + <data format="tabular" name="ppmCommunTOCSY" label="duplicateTocsy" > + <filter> tocsy_2dsequences != "no" </filter> + </data> + + <data format="tabular" name="annotationCombination" label="${tool.name}_annotationCombination" /> + <data format="pdf" name="AnnotationGraph" label="${tool.name}_graph" /> + </outputs> + +<help> + +.. class:: infomark + +**Authors** Marie Tremblay-Franco (marie.tremblay-franco@inra.fr), Coline Gardou + +.. class:: infomark + + +--------------------------------------------------- + +============================ +Bidimensional NMR Annotation +============================ + +----------- +Description +----------- + +BARSA is an automatic algorithm for bi-dimensional NMR spectra annotation + +----------------- +Workflow position +----------------- + +**Upstream tools** + +========================= ================= ======= ========= +Name output file format parameter +========================= ================= ======= ========= +NA NA NA NA +========================= ================= ======= ========= + + +**Downstream tools** + +========================= ================= ======= ========= +Name output file format parameter +========================= ================= ======= ========= +NA NA NA NA +========================= ================= ======= ========= + + + +----------- +Input files +----------- + ++---------------------------+------------+ +| Parameter : num + label | Format | ++===========================+============+ +| 1 : Choose your inputs | xlsx | ++---------------------------+------------+ + +**Choose your inputs** + | xlsx file can include several peak lists, coming from several 2D NMR sequences + | + +.. image:: ./static/images/2DNmr_FileToAnnotate_xlsxFormat.png + +---------- +Parameters +---------- + +Bi-dimensional NMR peak list(s) to annotate; select one or more sequence(s) + | COSY: yes/no + | JRES: yes/no + | HMBC: yes/no + | HSQC: yes/no + | TOCSY: yes/no + | Default value is no + | + +In-house databases + | Use of your own databases to annotate peak list(s) + | If YES: parameters **COSY In-house database**, **JRES In-house database**, ** HMBC In-house database**, **HSQC In-house database** and **TOCSY In-house database** are visible + | Select one or more in-house database + | + + +Tolerances + | tolppm1: Maximum variation of the chemical shift (due to experimental conditions) of a peak along the x-axis + | tolppm2: Maximum variation of the chemical shift (due to experimental conditions) of a peak along the y-axis + | tolppmJRES: Maximum variation of the chemical shift (due to experimental conditions) of a peak for the JRES sequence + | Default values: 0.01 and 0.01 ppm; 0.002 Hz + | + + +Threshold + | All metabolites with a presence probability (number of detected peak(s)/number of theoretical peak(s)) under this threshold are removed + | Default value: 0 + | + + +Unicity of annotation + | All the peaks assigned to more than one metabolite are removed + | + + +------------ +Output files +------------ +COSY + | tabular outputs + | annotationCOSY: Array with p rows (corresponding to the identified metabolites) and 4 columns containing the chemical shift on the x-axis, the chemical shift on the y-axis, the metabolite name and the presence probability + | ppmCommunCOSY: Array containing for all the peaks assigned to more than one metabolite: the chemical shift on the x-axis, the chemical shift on the y-axis and the list of assigned metabolites + | Only display if COSY was chosen + | + + +JRES + | tabular outputs + | annotationJRES: Array with p rows (corresponding to the identified metabolites) and 4 columns containing the chemical shift on the x-axis, the chemical shift on the y-axis, the metabolite name and the presence probability + | ppmCommunJRES: Array containing for all the peaks assigned to more than one metabolite: the chemical shift on the x-axis, the chemical shift on the y-axis and the list of assigned metabolites + | Only display if JRES was chosen + | + + +HMBC + | tabular outputs + | annotationHMBC: Array with p rows (corresponding to the identified metabolites) and 4 columns containing the chemical shift on the x-axis, the chemical shift on the y-axis, the metabolite name and the presence probability + | ppmCommunHMBC: Array containing for all the peaks assigned to more than one metabolite: the chemical shift on the x-axis, the chemical shift on the y-axis and the list of assigned metabolites + | Only display if HMBC was chosen + | + + +HSQC + | tabular outputs + | annotationHSQC: Array with p rows (corresponding to the identified metabolites) and 4 columns containing the chemical shift on the x-axis, the chemical shift on the y-axis, the metabolite name and the presence probability + | ppmCommunHSQC: Array containing for all the peaks assigned to more than one metabolite: the chemical shift on the x-axis, the chemical shift on the y-axis and the list of assigned metabolites + | Only display if HSQC was chosen + | + + +TOCSY + | tabular outputs + | annotationTOCSY: Array with p rows (corresponding to the identified metabolites) and 4 columns containing the chemical shift on the x-axis, the chemical shift on the y-axis, the metabolite name and the presence probability + | ppmCommunTOCSY: Array containing for all the peaks assigned to more than one metabolite: the chemical shift on the x-axis, the chemical shift on the y-axis and the list of assigned metabolites + | Only display if TOCSY was chosen + | + + +annotationCombination + | tabular outputs + | Array with p rows (corresponding to the identified metabolites) including the Metabolite name, the COSY presence probability, the JRES presence probability, the HMBC presence probability, the HSQC presence probability, the TOCSY presence probability and the averageScore + | Depends on the chosen sequences + | Only display if 2 or more sequences have be chosen + + +AnnotationGraph.pdf + | pdf output + | Bi-dimensional graphical chart of real pairs of chemical shifts, with name of identified metabolites + + + +--------------------------------------------------- + +------- +Example +------- +Example of output files obtaining wehn running the algorithm on a mix of 23 known compounds + +.. image:: ./static/images/OutputsExampleMix.png + :width: 500 + + </help> + +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/test-data/2DNMR_Annotation_annotationCombination.tabular Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,34 @@ +Metabolite score.HSQC score.JRES averageScore +4_hydroxyphenylpropionic_acid NA 0.5 0.5 +alanine 1 1 1 +arabinose NA 0.348837209302326 0.348837209302326 +asparagine 1 1 1 +aspartic_acid 1 1 1 +betaine 1 1 1 +butyric acid 0.333333333333333 0.916666666666667 0.625 +cadaverine 0.333333333333333 0.615384615384615 0.474358974358974 +carnitine 1 0.611111111111111 0.805555555555556 +cholinechloride 0.666666666666667 0.714285714285714 0.69047619047619 +creatine NA 0.5 0.5 +desaminotyrosine NA 0.4 0.4 +dimethylamine NA 1 1 +dimethylglycine NA 0.333333333333333 0.333333333333333 +fumaric acid 1 1 1 +gaba 0.333333333333333 NA 0.333333333333333 +galactose 0.833333333333333 0.473684210526316 0.653508771929825 +glucose 0.666666666666667 0.8125 0.739583333333333 +glycerol NA 0.666666666666667 0.666666666666667 +glycine 1 1 1 +hippuric_acid 1 1 1 +histidine 1 0.428571428571429 0.714285714285714 +indoxylsulfate NA 0.545454545454545 0.545454545454545 +isoleucine 1 0.379310344827586 0.689655172413793 +lactic acid 1 1 1 +mannose NA 0.3125 0.3125 +myo_inositol NA 0.384615384615385 0.384615384615385 +proline 1 0.409090909090909 0.704545454545455 +taurine NA 0.333333333333333 0.333333333333333 +threonine 1 1 1 +tryptophan 1 0.521739130434783 0.760869565217391 +uracil NA 0.5 0.5 +valine 0.75 0.75 0.75
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/test-data/2DNMR_Annotation_log.txt Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,112 @@ + PACKAGE INFO +R version 3.4.3 (2017-11-30) +Platform: x86_64-pc-linux-gnu (64-bit) +Running under: Ubuntu 14.04.5 LTS + +Matrix products: default +BLAS: /usr/lib/libblas/libblas.so.3.0 +LAPACK: /usr/lib/lapack/liblapack.so.3.0 + +locale: + [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C + [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 + [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 + [7] LC_PAPER=en_US.UTF-8 LC_NAME=C + [9] LC_ADDRESS=C LC_TELEPHONE=C +[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C + +attached base packages: +[1] stats graphics grDevices utils datasets base + +other attached packages: +[1] tidyr_0.7.2 stringr_1.2.0 openxlsx_4.1.3 ggplot2_2.2.1 dplyr_0.7.4 +[6] batch_1.1-4 + +loaded via a namespace (and not attached): + [1] Rcpp_0.12.14 bindr_0.1 magrittr_1.5 munsell_0.4.3 + [5] colorspace_1.3-2 R6_2.2.2 rlang_0.4.2 plyr_1.8.4 + [9] tools_3.4.3 grid_3.4.3 gtable_0.2.0 cli_1.1.0 +[13] lazyeval_0.2.1 assertthat_0.2.0 tibble_1.3.4 crayon_1.3.4 +[17] bindrcpp_0.2 zip_1.0.0 purrr_0.3.3 glue_1.2.0 +[21] stringi_1.1.6 compiler_3.4.3 methods_3.4.3 scales_0.5.0 +[25] pkgconfig_2.0.1 +$xlsfile +[1] "/home/vagrant/galaxy/database/datasets/001/dataset_1825.dat" + +$cosy_2dsequences +[1] "no" + +$jres_2dsequences +[1] "yes" + +$hmbc_2dsequences +[1] "no" + +$hsqc_2dsequences +[1] "yes" + +$tocsy_2dsequences +[1] "no" + +$inHouse_DB_choices.choice +[1] "no" + +$tolppm1 +[1] 0.01 + +$tolppm2 +[1] 0.5 + +$tolppmJRES +[1] 0.002 + +$threshold +[1] 0.3 + +$unicity +[1] "no" + +$logOut +[1] "/home/vagrant/galaxy/database/datasets/002/dataset_2767.dat" + +$annotationCOSY +[1] "None" + +$ppmCommunCOSY +[1] "None" + +$annotationJRES +[1] "/home/vagrant/galaxy/database/datasets/002/dataset_2768.dat" + +$ppmCommunJRES +[1] "/home/vagrant/galaxy/database/datasets/002/dataset_2769.dat" + +$annotationHMBC +[1] "None" + +$ppmCommunHMBC +[1] "None" + +$annotationHSQC +[1] "/home/vagrant/galaxy/database/datasets/002/dataset_2770.dat" + +$ppmCommunHSQC +[1] "/home/vagrant/galaxy/database/datasets/002/dataset_2771.dat" + +$annotationTOCSY +[1] "None" + +$ppmCommunTOCSY +[1] "None" + +$annotationCombination +[1] "/home/vagrant/galaxy/database/datasets/002/dataset_2772.dat" + +$AnnotationGraph +[1] "/home/vagrant/galaxy/database/datasets/002/dataset_2773.dat" + +null device + 1 +Time difference of 1.566586 mins + +End of '2D NMR annotation' Galaxy module call: 2019-12-23 10:55:29 \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/test-data/annotationHsqc.tabular Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,77 @@ +ppm1 ppm2 Metabolite score +1.487 19.022 alanine 1 +3.791 53.343 alanine 1 +2.883 37.372 asparagine 1 +2.964 37.382 asparagine 1 +4.016 54.04 asparagine 1 +2.694 39.367 Aspartic_acid 1 +2.816 39.387 Aspartic_acid 1 +3.905 54.962 Aspartic_acid 1 +3.264 56.272 betaine 1 +3.901 69.074 betaine 1 +2.164 42.369 Butyric acid 0.333333333333333 +3.024 41.961 Cadaverine 0.333333333333333 +2.444 45.792 carnitine 1 +3.232 56.932 carnitine 1 +3.44 72.954 carnitine 1 +4.571 66.903 carnitine 1 +3.208 56.704 CholineChloride 0.666666666666667 +4.072 58.227 CholineChloride 0.666666666666667 +6.526 138.157 Fumaric acid 1 +3.015 42.093 gaba 0.333333333333333 +3.502 74.756 galactose 0.833333333333333 +3.661 75.593 galactose 0.833333333333333 +3.717 78.019 galactose 0.833333333333333 +3.815 71.175 galactose 0.833333333333333 +3.866 71.993 galactose 0.833333333333333 +3.942 71.619 galactose 0.833333333333333 +4 72.162 galactose 0.833333333333333 +4.096 73.292 galactose 0.833333333333333 +4.598 99.277 galactose 0.833333333333333 +5.277 95.132 galactose 0.833333333333333 +3.425 72.307 glucose 0.666666666666667 +3.46 78.647 glucose 0.666666666666667 +3.549 74.169 glucose 0.666666666666667 +3.745 63.514 glucose 0.666666666666667 +3.841 74.223 glucose 0.666666666666667 +3.847 63.4 glucose 0.666666666666667 +4.66 98.737 glucose 0.666666666666667 +5.252 94.768 glucose 0.666666666666667 +3.566 44.267 glycine 1 +3.967 46.611 hippuric_acid 1 +7.556 131.578 hippuric_acid 1 +7.643 135.065 hippuric_acid 1 +7.837 130.019 hippuric_acid 1 +3.209 30.164 Histidine 1 +3.29 30.194 Histidine 1 +4.014 57.269 Histidine 1 +7.155 119.969 Histidine 1 +8.04 138.39 Histidine 1 +0.944 14.001 Isoleucine 1 +1.017 17.526 Isoleucine 1 +1.27 27.262 Isoleucine 1 +1.479 27.34 Isoleucine 1 +1.987 38.709 Isoleucine 1 +3.68 62.433 Isoleucine 1 +1.336 22.913 Lactic acid 1 +4.12 71.318 Lactic acid 1 +2.009 26.543 Proline 1 +2.062 31.789 Proline 1 +2.357 31.817 Proline 1 +3.346 48.831 Proline 1 +3.422 48.867 Proline 1 +4.14 63.947 Proline 1 +1.342 22.349 threonine 1 +3.609 63.354 threonine 1 +4.261 68.825 threonine 1 +3.321 29.248 tryptophan 1 +3.492 29.268 tryptophan 1 +4.066 57.824 tryptophan 1 +7.209 122.251 tryptophan 1 +7.292 124.963 tryptophan 1 +7.337 127.891 tryptophan 1 +7.554 114.838 tryptophan 1 +7.743 121.238 tryptophan 1 +1 19.497 valine 0.75 +1.049 20.77 valine 0.75 +2.281 31.893 valine 0.75
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/test-data/annotationJres.tabular Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,314 @@ +ppm1 ppm2 Metabolite score +2.452 0 4_hydroxyphenylpropionic_acid 0.5 +2.452 -0.013 4_hydroxyphenylpropionic_acid 0.5 +2.452 0.013 4_hydroxyphenylpropionic_acid 0.5 +2.818 -0.013 4_hydroxyphenylpropionic_acid 0.5 +2.818 0.013 4_hydroxyphenylpropionic_acid 0.5 +1.487 0.006 alanine 1 +1.487 -0.006 alanine 1 +3.791 -0.006 alanine 1 +3.791 -0.018 alanine 1 +3.791 0.006 alanine 1 +3.791 0.018 alanine 1 +3.517 0.002 arabinose 0.348837209302326 +3.655 -0.013 arabinose 0.348837209302326 +3.655 0.013 arabinose 0.348837209302326 +3.671 -0.005 arabinose 0.348837209302326 +3.824 -0.011 arabinose 0.348837209302326 +3.824 0.005 arabinose 0.348837209302326 +3.824 -0.005 arabinose 0.348837209302326 +3.824 0.011 arabinose 0.348837209302326 +3.905 -0.012 arabinose 0.348837209302326 +3.905 -0.009 arabinose 0.348837209302326 +3.905 0.009 arabinose 0.348837209302326 +3.905 0.009 arabinose 0.348837209302326 +3.905 -0.012 arabinose 0.348837209302326 +3.905 -0.009 arabinose 0.348837209302326 +4.013 0.004 arabinose 0.348837209302326 +5.248 -0.002 arabinose 0.348837209302326 +5.248 0.003 arabinose 0.348837209302326 +2.881 -0.008 asparagine 1 +2.881 0.02 asparagine 1 +2.881 0.008 asparagine 1 +2.881 -0.02 asparagine 1 +2.961 0.01 asparagine 1 +2.961 -0.018 asparagine 1 +2.961 -0.011 asparagine 1 +2.961 0.018 asparagine 1 +4.014 -0.01 asparagine 1 +4.014 0.01 asparagine 1 +4.014 -0.002 asparagine 1 +4.014 0.002 asparagine 1 +2.694 0.007 Aspartic_acid 1 +2.694 0.022 Aspartic_acid 1 +2.694 -0.008 Aspartic_acid 1 +2.817 -0.011 Aspartic_acid 1 +2.817 0.011 Aspartic_acid 1 +2.817 0.018 Aspartic_acid 1 +2.817 -0.018 Aspartic_acid 1 +3.906 -0.01 Aspartic_acid 1 +3.906 0.01 Aspartic_acid 1 +3.906 -0.004 Aspartic_acid 1 +3.906 0.004 Aspartic_acid 1 +3.906 0.01 Aspartic_acid 1 +3.906 -0.01 Aspartic_acid 1 +3.273 0 betaine 1 +3.908 0 betaine 1 +0.898 -0.012 Butyric acid 0.916666666666667 +0.902 0 Butyric acid 0.916666666666667 +0.907 0.013 Butyric acid 0.916666666666667 +1.565 0.007 Butyric acid 0.916666666666667 +1.57 0.019 Butyric acid 0.916666666666667 +1.565 -0.03 Butyric acid 0.916666666666667 +1.565 -0.006 Butyric acid 0.916666666666667 +1.57 -0.018 Butyric acid 0.916666666666667 +2.165 0 Butyric acid 0.916666666666667 +2.17 0.013 Butyric acid 0.916666666666667 +2.17 -0.012 Butyric acid 0.916666666666667 +1.726 0.025 Cadaverine 0.615384615384615 +1.73 -0.026 Cadaverine 0.615384615384615 +1.729 0 Cadaverine 0.615384615384615 +1.729 0.013 Cadaverine 0.615384615384615 +1.731 -0.013 Cadaverine 0.615384615384615 +3.022 0.012 Cadaverine 0.615384615384615 +3.022 -0.012 Cadaverine 0.615384615384615 +3.024 0 Cadaverine 0.615384615384615 +2.426 -0.018 carnitine 0.611111111111111 +2.426 0.007 carnitine 0.611111111111111 +2.426 0.018 carnitine 0.611111111111111 +2.446 0.013 carnitine 0.611111111111111 +2.446 -0.013 carnitine 0.611111111111111 +2.445 0.027 carnitine 0.611111111111111 +2.445 0 carnitine 0.611111111111111 +2.445 -0.027 carnitine 0.611111111111111 +2.445 0 carnitine 0.611111111111111 +2.446 -0.038 carnitine 0.611111111111111 +2.445 -0.027 carnitine 0.611111111111111 +2.445 0.027 carnitine 0.611111111111111 +2.446 0.038 carnitine 0.611111111111111 +2.446 -0.013 carnitine 0.611111111111111 +2.446 0.013 carnitine 0.611111111111111 +2.465 -0.007 carnitine 0.611111111111111 +2.465 0.007 carnitine 0.611111111111111 +2.465 0.019 carnitine 0.611111111111111 +2.465 0.019 carnitine 0.611111111111111 +2.465 -0.007 carnitine 0.611111111111111 +2.465 -0.019 carnitine 0.611111111111111 +2.465 0.007 carnitine 0.611111111111111 +3.234 0 carnitine 0.611111111111111 +3.422 0.015 carnitine 0.611111111111111 +3.422 -0.015 carnitine 0.611111111111111 +3.434 0 carnitine 0.611111111111111 +3.422 -0.009 carnitine 0.611111111111111 +3.438 -0.008 carnitine 0.611111111111111 +3.438 0.008 carnitine 0.611111111111111 +3.209 -0.001 CholineChloride 0.714285714285714 +3.529 0.008 CholineChloride 0.714285714285714 +3.529 -0.008 CholineChloride 0.714285714285714 +4.069 0 CholineChloride 0.714285714285714 +4.069 0.009 CholineChloride 0.714285714285714 +3.937 0 creatine 0.5 +2.454 -0.013 Desaminotyrosine 0.4 +2.454 0.013 Desaminotyrosine 0.4 +2.822 -0.013 Desaminotyrosine 0.4 +2.822 0.012 Desaminotyrosine 0.4 +2.729 0 Dimethylamine 1 +3.741 0 Dimethylglycine 0.333333333333333 +6.519 0 Fumaric acid 1 +3.5 -0.002 galactose 0.473684210526316 +3.498 0.015 galactose 0.473684210526316 +3.658 -0.011 galactose 0.473684210526316 +3.658 -0.005 galactose 0.473684210526316 +3.658 0.005 galactose 0.473684210526316 +3.658 0.011 galactose 0.473684210526316 +3.723 -0.016 galactose 0.473684210526316 +3.723 0.016 galactose 0.473684210526316 +3.723 0.016 galactose 0.473684210526316 +3.723 -0.004 galactose 0.473684210526316 +3.723 -0.016 galactose 0.473684210526316 +3.723 0.004 galactose 0.473684210526316 +3.736 0 galactose 0.473684210526316 +3.76 -0.002 galactose 0.473684210526316 +3.762 0.008 galactose 0.473684210526316 +3.763 -0.009 galactose 0.473684210526316 +3.812 -0.012 galactose 0.473684210526316 +3.812 0.005 galactose 0.473684210526316 +3.812 -0.006 galactose 0.473684210526316 +3.812 0.012 galactose 0.473684210526316 +3.863 -0.012 galactose 0.473684210526316 +3.863 -0.006 galactose 0.473684210526316 +3.863 0.006 galactose 0.473684210526316 +3.863 0.012 galactose 0.473684210526316 +4.595 -0.007 galactose 0.473684210526316 +4.595 0.007 galactose 0.473684210526316 +5.274 -0.004 galactose 0.473684210526316 +5.274 0.004 galactose 0.473684210526316 +3.256 -0.014 glucose 0.8125 +3.255 0 glucose 0.8125 +3.422 0.016 glucose 0.8125 +3.411 0.016 glucose 0.8125 +3.422 -0.016 glucose 0.8125 +3.411 -0.016 glucose 0.8125 +3.422 0 glucose 0.8125 +3.475 0 glucose 0.8125 +3.475 -0.011 glucose 0.8125 +3.475 -0.005 glucose 0.8125 +3.475 0.005 glucose 0.8125 +3.475 0.011 glucose 0.8125 +3.475 0.015 glucose 0.8125 +3.502 -0.015 glucose 0.8125 +3.502 0 glucose 0.8125 +3.502 0.015 glucose 0.8125 +3.545 0.011 glucose 0.8125 +3.545 -0.005 glucose 0.8125 +3.545 0.005 glucose 0.8125 +3.545 -0.012 glucose 0.8125 +3.731 -0.015 glucose 0.8125 +3.721 -0.016 glucose 0.8125 +3.732 0.015 glucose 0.8125 +3.721 0.016 glucose 0.8125 +3.732 0.015 glucose 0.8125 +3.732 -0.006 glucose 0.8125 +3.731 -0.015 glucose 0.8125 +3.732 0.005 glucose 0.8125 +3.843 0.009 glucose 0.8125 +3.839 0.011 glucose 0.8125 +3.844 -0.01 glucose 0.8125 +3.839 -0.011 glucose 0.8125 +3.901 -0.012 glucose 0.8125 +3.901 -0.009 glucose 0.8125 +3.901 0.008 glucose 0.8125 +3.902 0.012 glucose 0.8125 +3.901 -0.012 glucose 0.8125 +3.901 -0.009 glucose 0.8125 +4.655 0.007 glucose 0.8125 +4.655 -0.006 glucose 0.8125 +5.243 -0.003 glucose 0.8125 +5.243 0.003 glucose 0.8125 +3.656 -0.013 glycerol 0.666666666666667 +3.656 -0.006 glycerol 0.666666666666667 +3.656 0.006 glycerol 0.666666666666667 +3.791 -0.011 glycerol 0.666666666666667 +3.791 0 glycerol 0.666666666666667 +3.791 0.01 glycerol 0.666666666666667 +3.791 -0.007 glycerol 0.666666666666667 +3.791 -0.018 glycerol 0.666666666666667 +3.791 0.007 glycerol 0.666666666666667 +3.791 0.018 glycerol 0.666666666666667 +3.568 0 glycine 1 +3.969 0 hippuric_acid 1 +7.555 0.013 hippuric_acid 1 +7.555 0 hippuric_acid 1 +7.555 -0.013 hippuric_acid 1 +7.642 0 hippuric_acid 1 +7.642 -0.013 hippuric_acid 1 +7.642 0.012 hippuric_acid 1 +7.836 -0.007 hippuric_acid 1 +7.836 0.007 hippuric_acid 1 +4.015 -0.011 Histidine 0.428571428571429 +4.015 0.01 Histidine 0.428571428571429 +4.015 -0.002 Histidine 0.428571428571429 +4.015 0.002 Histidine 0.428571428571429 +7.156 0 Histidine 0.428571428571429 +8.043 0 Histidine 0.428571428571429 +7.21 0.013 indoxylsulfate 0.545454545454545 +7.21 -0.013 indoxylsulfate 0.545454545454545 +7.21 0 indoxylsulfate 0.545454545454545 +7.283 -0.013 indoxylsulfate 0.545454545454545 +7.283 0.013 indoxylsulfate 0.545454545454545 +7.283 0 indoxylsulfate 0.545454545454545 +0.946 -0.012 Isoleucine 0.379310344827586 +0.948 0.012 Isoleucine 0.379310344827586 +0.949 0 Isoleucine 0.379310344827586 +1.017 0.007 Isoleucine 0.379310344827586 +1.017 -0.006 Isoleucine 0.379310344827586 +1.269 0.025 Isoleucine 0.379310344827586 +1.269 -0.024 Isoleucine 0.379310344827586 +1.269 -0.011 Isoleucine 0.379310344827586 +1.269 0.011 Isoleucine 0.379310344827586 +3.687 -0.004 Isoleucine 0.379310344827586 +3.683 0.003 Isoleucine 0.379310344827586 +1.333 0.006 Lactic acid 1 +1.333 -0.006 Lactic acid 1 +1.333 0.006 Lactic acid 1 +4.117 -0.017 Lactic acid 1 +4.118 0.017 Lactic acid 1 +4.117 -0.006 Lactic acid 1 +4.117 0.006 Lactic acid 1 +3.741 -0.005 mannose 0.3125 +3.741 -0.015 mannose 0.3125 +3.741 0.005 mannose 0.3125 +3.823 0.004 mannose 0.3125 +3.823 -0.004 mannose 0.3125 +3.856 -0.011 mannose 0.3125 +3.856 -0.005 mannose 0.3125 +3.856 0.005 mannose 0.3125 +3.856 0.011 mannose 0.3125 +3.91 -0.012 mannose 0.3125 +3.91 0.009 mannose 0.3125 +3.91 0.009 mannose 0.3125 +3.91 0.012 mannose 0.3125 +3.91 -0.012 mannose 0.3125 +3.943 0 mannose 0.3125 +3.956 0 mannose 0.3125 +3.544 0.011 myo_inositol 0.384615384615385 +3.544 -0.006 myo_inositol 0.384615384615385 +3.544 0.006 myo_inositol 0.384615384615385 +3.544 -0.011 myo_inositol 0.384615384615385 +4.073 0 myo_inositol 0.384615384615385 +2.012 -0.021 Proline 0.409090909090909 +2.011 -0.01 Proline 0.409090909090909 +2.012 0.01 Proline 0.409090909090909 +2.012 0.021 Proline 0.409090909090909 +2.011 0 Proline 0.409090909090909 +2.356 -0.004 Proline 0.409090909090909 +2.356 -0.017 Proline 0.409090909090909 +2.356 0.004 Proline 0.409090909090909 +2.356 0.018 Proline 0.409090909090909 +3.347 -0.009 Proline 0.409090909090909 +3.347 0.01 Proline 0.409090909090909 +3.423 0.001 Proline 0.409090909090909 +3.423 -0.009 Proline 0.409090909090909 +3.423 0.01 Proline 0.409090909090909 +4.141 0.013 Proline 0.409090909090909 +4.141 -0.013 Proline 0.409090909090909 +4.14 -0.002 Proline 0.409090909090909 +4.142 0.002 Proline 0.409090909090909 +3.275 0 taurine 0.333333333333333 +3.43 0 taurine 0.333333333333333 +1.34 0.005 threonine 1 +1.339 -0.006 threonine 1 +1.34 0.005 threonine 1 +3.603 0.004 threonine 1 +3.604 -0.005 threonine 1 +4.26 -0.01 threonine 1 +4.258 -0.02 threonine 1 +4.26 0.01 threonine 1 +4.259 0 threonine 1 +4.259 0.021 threonine 1 +4.063 -0.002 tryptophan 0.521739130434783 +7.204 0.012 tryptophan 0.521739130434783 +7.204 -0.012 tryptophan 0.521739130434783 +7.204 0 tryptophan 0.521739130434783 +7.288 -0.012 tryptophan 0.521739130434783 +7.288 0.013 tryptophan 0.521739130434783 +7.288 0 tryptophan 0.521739130434783 +7.334 0 tryptophan 0.521739130434783 +7.548 -0.006 tryptophan 0.521739130434783 +7.549 0.007 tryptophan 0.521739130434783 +7.738 -0.006 tryptophan 0.521739130434783 +7.738 0.006 tryptophan 0.521739130434783 +7.552 -0.006 Uracil 0.5 +7.552 0.007 Uracil 0.5 +0.998 -0.006 valine 0.75 +0.996 0.006 valine 0.75 +1.047 -0.006 valine 0.75 +1.047 0.006 valine 0.75 +2.279 -0.004 valine 0.75 +2.28 0.003 valine 0.75 +2.28 0.016 valine 0.75 +2.281 -0.016 valine 0.75 +2.28 -0.008 valine 0.75 +2.28 0.008 valine 0.75 +3.62 -0.004 valine 0.75 +3.62 0.004 valine 0.75
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/test-data/duplicateHsqc.tabular Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,19 @@ +ppm1 ppm2 commonMetabolitesList +3.024 41.961 Cadaverine 5aminovalericacid gaba Lysine +3.232 56.932 carnitine gpc +4.072 58.227 CholineChloride tryptophan +3.015 42.093 gaba 5aminovalericacid Cadaverine +3.502 74.756 galactose cholic_acid +3.661 75.593 galactose mannose +3.866 71.993 galactose stachyose +3.942 71.619 galactose ribose +4 72.162 galactose stachyose +3.425 72.307 glucose maltose +3.549 74.169 glucose myo_inositol +4.66 98.737 glucose maltose +5.252 94.768 glucose maltose +4.12 71.318 Lactic acid ribose +4.066 57.824 tryptophan CholineChloride +7.209 122.251 tryptophan indoxylsulfate +7.292 124.963 tryptophan indoxylsulfate +1 19.497 valine cholic_acid
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nmr_annotation2d/test-data/duplicateJres.tabular Mon Dec 23 09:26:20 2019 -0500 @@ -0,0 +1,197 @@ +ppm1 ppm2 commonMetabolitesList +2.452 0 4_hydroxyphenylpropionic_acid carnitine Desaminotyrosine glutamine +2.452 -0.013 4_hydroxyphenylpropionic_acid carnitine Desaminotyrosine glutamine +2.452 0.013 4_hydroxyphenylpropionic_acid carnitine Desaminotyrosine +2.818 -0.013 4_hydroxyphenylpropionic_acid Aspartic_acid Desaminotyrosine +2.818 0.013 4_hydroxyphenylpropionic_acid Aspartic_acid Desaminotyrosine +3.791 -0.006 alanine glycerol raffinose stachyose +3.791 -0.018 alanine glycerol maltose raffinose stachyose +3.791 0.006 alanine glycerol raffinose stachyose +3.791 0.018 alanine glycerol raffinose stachyose +3.655 -0.013 arabinose galactose glycerol maltose ribose +3.655 0.013 arabinose galactose glycerol ribose +3.671 -0.005 arabinose mannose ribose +3.824 -0.011 arabinose ribose stachyose +3.824 0.005 arabinose mannose ribose stachyose +3.824 -0.005 arabinose mannose ribose stachyose +3.824 0.011 arabinose Ethanolamine ribose stachyose +3.905 -0.012 arabinose Aspartic_acid glucose mannose raffinose ribose stachyose +3.905 -0.009 arabinose Aspartic_acid glucose mannose raffinose ribose stachyose sucrose +3.905 0.009 arabinose Aspartic_acid glucose mannose raffinose ribose stachyose sucrose +4.013 0.004 arabinose asparagine Histidine ribose +5.248 -0.002 arabinose glucose maltose +5.248 0.003 arabinose glucose maltose +4.014 -0.01 asparagine Histidine +4.014 0.01 asparagine Histidine +4.014 -0.002 asparagine Histidine raffinose ribose +4.014 0.002 asparagine arabinose Histidine raffinose +2.817 -0.011 Aspartic_acid 4_hydroxyphenylpropionic_acid Desaminotyrosine +2.817 0.011 Aspartic_acid 4_hydroxyphenylpropionic_acid Desaminotyrosine +3.906 -0.01 Aspartic_acid arabinose glucose mannose raffinose stachyose +3.906 0.01 Aspartic_acid arabinose glucose mannose raffinose stachyose +3.906 -0.004 Aspartic_acid raffinose stachyose +3.906 0.004 Aspartic_acid raffinose stachyose +3.273 0 betaine taurine +3.908 0 betaine cholic_acid raffinose stachyose +0.898 -0.012 Butyric acid 2_hydroxybutyric_acid 3_methyl-2-oxovaleric acid valeric_acid +0.902 0 Butyric acid 2_hydroxybutyric_acid 3_methyl-2-oxovaleric acid valeric_acid +0.907 0.013 Butyric acid 2_hydroxybutyric_acid 3_methyl-2-oxovaleric acid +1.57 0.019 Butyric acid cholic_acid +1.57 -0.018 Butyric acid cholic_acid +2.17 0.013 Butyric acid octanoic_acid +2.17 -0.012 Butyric acid octanoic_acid +1.73 -0.026 Cadaverine Lysine +1.729 0 Cadaverine Lysine +1.729 0.013 Cadaverine Lysine +1.731 -0.013 Cadaverine Lysine +3.022 0.012 Cadaverine 5aminovalericacid gaba +3.022 -0.012 Cadaverine 5aminovalericacid gaba +3.024 0 Cadaverine 5aminovalericacid gaba Lysine +2.446 0.013 carnitine 4_hydroxyphenylpropionic_acid Desaminotyrosine +2.446 -0.013 carnitine 4_hydroxyphenylpropionic_acid Desaminotyrosine +2.445 0.027 carnitine glutamine +2.445 0 carnitine 4_hydroxyphenylpropionic_acid Desaminotyrosine +3.234 0 carnitine gpc +3.422 0.015 carnitine glucose +3.422 -0.015 carnitine glucose +3.434 0 carnitine maltose rahmnose taurine +3.422 -0.009 carnitine Proline taurine +3.529 0.008 CholineChloride ribose +3.529 -0.008 CholineChloride ribose +4.069 0 CholineChloride cholic_acid myo_inositol raffinose stachyose sucrose tryptophan +4.069 0.009 CholineChloride tryptophan +3.937 0 creatine mannose ribose +2.454 -0.013 Desaminotyrosine 4_hydroxyphenylpropionic_acid carnitine glutamine +2.454 0.013 Desaminotyrosine 4_hydroxyphenylpropionic_acid carnitine +2.822 -0.013 Desaminotyrosine 4_hydroxyphenylpropionic_acid Aspartic_acid +2.822 0.012 Desaminotyrosine 4_hydroxyphenylpropionic_acid Aspartic_acid +3.741 0 Dimethylglycine galactose +3.5 -0.002 galactose cholic_acid glucose +3.498 0.015 galactose glucose +3.658 -0.011 galactose arabinose glycerol +3.658 -0.005 galactose Ethanol glycerol ribose stachyose +3.658 0.005 galactose Ethanol glycerol ribose stachyose +3.658 0.011 galactose arabinose +3.723 -0.016 galactose glucose +3.723 0.016 galactose glucose +3.723 -0.004 galactose glucose +3.723 0.004 galactose glucose +3.736 0 galactose Dimethylglycine +3.76 -0.002 galactose Lysine phenylacetylglycine +3.762 0.008 galactose glucose Lysine maltose raffinose ribose +3.763 -0.009 galactose glutamic acid Lysine raffinose ribose +3.812 -0.012 galactose maltose rahmnose ribose +3.812 0.005 galactose maltose rahmnose sucrose +3.812 -0.006 galactose maltose rahmnose ribose sucrose +3.812 0.012 galactose maltose rahmnose ribose +3.863 -0.012 galactose maltose mannose Methionine rahmnose stachyose +3.863 -0.006 galactose Ethanolamine maltose mannose Serine stachyose +3.863 0.006 galactose maltose mannose ribose Serine stachyose +3.863 0.012 galactose maltose mannose Methionine rahmnose stachyose +3.255 0 glucose arginine +3.422 0.016 glucose carnitine +3.422 -0.016 glucose carnitine +3.422 0 glucose Proline taurine +3.475 0 glucose sucrose +3.475 0.015 glucose sucrose +3.502 -0.015 glucose galactose +3.502 0 glucose cholic_acid galactose +3.502 0.015 glucose galactose +3.545 0.011 glucose myo_inositol +3.545 -0.005 glucose myo_inositol ribose +3.545 0.005 glucose myo_inositol ribose +3.545 -0.012 glucose myo_inositol +3.731 -0.015 glucose galactose stachyose +3.721 -0.016 glucose galactose +3.732 0.015 glucose galactose mannose stachyose +3.721 0.016 glucose galactose +3.732 -0.006 glucose galactose mannose stachyose +3.732 0.005 glucose galactose mannose stachyose +3.843 0.009 glucose inosine raffinose sucrose +3.839 0.011 glucose raffinose ribose +3.844 -0.01 glucose Ethanolamine raffinose sucrose +3.839 -0.011 glucose raffinose ribose +3.901 -0.012 glucose arabinose Aspartic_acid mannose raffinose ribose stachyose +3.901 -0.009 glucose arabinose Aspartic_acid mannose raffinose ribose stachyose sucrose +3.901 0.008 glucose arabinose Aspartic_acid mannose raffinose ribose sucrose +3.902 0.012 glucose arabinose Aspartic_acid mannose raffinose ribose stachyose +5.243 -0.003 glucose arabinose maltose +5.243 0.003 glucose arabinose maltose +3.656 -0.013 glycerol arabinose galactose maltose ribose +3.656 -0.006 glycerol arabinose Ethanol galactose ribose stachyose +3.656 0.006 glycerol Ethanol galactose ribose stachyose +3.791 -0.011 glycerol arginine glutamine ornithine +3.791 0 glycerol arginine glutamine maltose ornithine +3.791 0.01 glycerol arginine glutamic acid glutamine ornithine +3.791 -0.007 glycerol alanine +3.791 0.007 glycerol alanine +3.969 0 hippuric_acid maltose raffinose +4.015 -0.011 Histidine asparagine +4.015 0.01 Histidine asparagine +4.015 -0.002 Histidine asparagine raffinose ribose +4.015 0.002 Histidine arabinose asparagine raffinose +7.21 0.013 indoxylsulfate tryptophan +7.21 -0.013 indoxylsulfate tryptophan +7.21 0 indoxylsulfate indole_3_propionic_acid tryptophan +7.283 -0.013 indoxylsulfate tryptophan +7.283 0.013 indoxylsulfate tryptophan +7.283 0 indoxylsulfate tryptophan +3.687 -0.004 Isoleucine raffinose ribose +3.683 0.003 Isoleucine raffinose sucrose +1.333 0.006 Lactic acid threonine +1.333 -0.006 Lactic acid threonine +4.117 -0.006 Lactic acid ribose +4.117 0.006 Lactic acid ribose +3.741 -0.005 mannose galactose glucose raffinose stachyose +3.741 -0.015 mannose galactose raffinose stachyose +3.741 0.005 mannose galactose glucose raffinose stachyose +3.823 0.004 mannose arabinose maltose ribose stachyose +3.823 -0.004 mannose arabinose maltose ribose stachyose +3.856 -0.011 mannose galactose maltose raffinose ribose stachyose +3.856 -0.005 mannose galactose hydroxyisovaleric inosine ribose stachyose +3.856 0.005 mannose galactose hydroxyisovaleric inosine ribose stachyose +3.856 0.011 mannose galactose maltose raffinose ribose stachyose sucrose +3.91 -0.012 mannose arabinose Aspartic_acid glucose maltose raffinose stachyose +3.91 0.009 mannose arabinose Aspartic_acid glucose maltose raffinose stachyose +3.91 0.012 mannose arabinose Aspartic_acid glucose maltose raffinose stachyose +3.943 0 mannose arabinose creatine ribose +3.956 0 mannose arabinose raffinose +3.544 0.011 myo_inositol glucose +3.544 -0.006 myo_inositol glucose ribose +3.544 0.006 myo_inositol glucose ribose +3.544 -0.011 myo_inositol glucose +4.073 0 myo_inositol cholic_acid CholineChloride raffinose stachyose +2.012 -0.021 Proline hydroxyisovaleric +2.011 -0.01 Proline hydroxyisovaleric +2.012 0.01 Proline hydroxyisovaleric +2.012 0.021 Proline hydroxyisovaleric +3.423 0.001 Proline glucose taurine +3.423 -0.009 Proline carnitine taurine +3.423 0.01 Proline carnitine taurine +4.141 0.013 Proline stachyose +4.141 -0.013 Proline ribose stachyose +4.14 -0.002 Proline ribose +4.142 0.002 Proline ribose stachyose +3.275 0 taurine betaine +3.43 0 taurine carnitine glucose maltose Proline +1.34 0.005 threonine Lactic acid +1.339 -0.006 threonine Lactic acid +3.603 0.004 threonine maltose rahmnose +3.604 -0.005 threonine rahmnose +4.063 -0.002 tryptophan cholic_acid CholineChloride raffinose stachyose sucrose +7.204 0.012 tryptophan indoxylsulfate +7.204 -0.012 tryptophan indoxylsulfate +7.204 0 tryptophan indoxylsulfate +7.288 -0.012 tryptophan indoxylsulfate +7.288 0.013 tryptophan indoxylsulfate +7.288 0 tryptophan indoxylsulfate +7.548 -0.006 tryptophan Uracil +7.549 0.007 tryptophan Uracil +7.552 -0.006 Uracil tryptophan +7.552 0.007 Uracil tryptophan +0.998 -0.006 valine cholic_acid +0.996 0.006 valine cholic_acid +1.047 -0.006 valine 2_methylbutyric_acid +1.047 0.006 valine 2_methylbutyric_acid +3.62 -0.004 valine gpc rahmnose +3.62 0.004 valine gpc rahmnose