annotate annotationRmn2DGlobale.R @ 2:dff7bde22102 draft

"planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics commit b3abcb650e9b38458aa0ac5f7d838811d982ff65"

###########################################################################################################################################
# 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))
}