Nothing
# idNEG
#' Lipids annotation for ESI-
#'
#' Lipids annotation based on fragmentation patterns for LC-MS/MS DIA or DDA data
#' acquired in negative mode. This function compiles all functions writen for
#' ESI- annotations.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 5 seconds.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param lipidClasses classes of interest to run the identification functions.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification); and the annotatedPeaklist element shows the original
#' MS1 peaklist with the annotations on it.
#'
#' @examples
#' \dontrun{
#' msobject <- idNEG(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maribel_alcoriza@iislafe.es>
idNEG <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 5,
coelCutoff = 0.8,
lipidClasses = c("FA", "FAHFA", "LPC", "LPE", "LPG", "LPI",
"LPS", "PC", "PCo", "PCp", "PE", "PEo", "PEp",
"PG", "PI", "PS", "Sph", "SphP", "Cer", "CerP",
"AcylCer", "SM", "CL", "BA"),
dbs,
verbose = TRUE){
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if ("results" %in% names(msobject$annotation)){
if(verbose){cat("\n Removing previous results...")}
msobject$annotation$results <- NULL
msobject$annotation$detailsAnnotation <- NULL
msobject$annotatedPeaklist <- NULL
if(verbose){cat("OK")}
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(lipidClasses %in% c("FA", "FAHFA", "LPC", "LPE", "LPG", "LPI",
"LPS", "PC", "PCo", "PCp", "PE", "PEo", "PEp",
"PG", "PI", "PS", "Sph", "SphP", "Cer", "CerP",
"AcylCer", "SM", "CL", "BA"))){
stop("Lipid classes allowed for negative annotation are: FA, FAHFA, LPC, LPE,
LPG, LPI, LPS, PC, PCo, PCp, PE, PEo, PEp, PG, PI, PS, Sph, SphP, Cer,
CerP, AcylCer, SM, CL and BA")
}
if(verbose){cat("\n Starting annotation...")}
if ("FA" %in% lipidClasses){
if(verbose){cat("\n Searching for FA...")}
msobject <- idFAneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("FAHFA" %in% lipidClasses){
if(verbose){cat("\n Searching for FAHFA...")}
msobject <- idFAHFAneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("LPC" %in% lipidClasses){
if(verbose){cat("\n Searching for LPC...")}
msobject <- idLPCneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("LPE" %in% lipidClasses){
if(verbose){cat("\n Searching for LPE...")}
msobject <- idLPEneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("LPG" %in% lipidClasses){
if(verbose){cat("\n Searching for LPG...")}
msobject <- idLPGneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("LPI" %in% lipidClasses){
if(verbose){cat("\n Searching for LPI...")}
msobject <- idLPIneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("LPS" %in% lipidClasses){
if(verbose){cat("\n Searching for LPS...")}
msobject <- idLPSneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PC" %in% lipidClasses){
if(verbose){cat("\n Searching for PC...")}
msobject <- idPCneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PCo" %in% lipidClasses){
if(verbose){cat("\n Searching for PCo...")}
msobject <- idPConeg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PCp" %in% lipidClasses){
if(verbose){cat("\n Searching for PCp...")}
msobject <- idPCpneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PE" %in% lipidClasses){
if(verbose){cat("\n Searching for PE...")}
msobject <- idPEneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PEo" %in% lipidClasses){
if(verbose){cat("\n Searching for PEo...")}
msobject <- idPEoneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PEp" %in% lipidClasses){
if(verbose){cat("\n Searching for PEp...")}
msobject <- idPEpneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PG" %in% lipidClasses){
if(verbose){cat("\n Searching for PG...")}
msobject <- idPGneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PI" %in% lipidClasses){
if(verbose){cat("\n Searching for PI...")}
msobject <- idPIneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("PS" %in% lipidClasses){
if(verbose){cat("\n Searching for PS...")}
msobject <- idPSneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("Sph" %in% lipidClasses){
if(verbose){cat("\n Searching for Sph...")}
msobject <- idSphneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("SphP" %in% lipidClasses){
if(verbose){cat("\n Searching for SphP...")}
msobject <- idSphPneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("Cer" %in% lipidClasses){
if(verbose){cat("\n Searching for Cer...")}
msobject <- idCerneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("CerP" %in% lipidClasses){
if(verbose){cat("\n Searching for CerP...")}
msobject <- idCerPneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("AcylCer" %in% lipidClasses){
if(verbose){cat("\n Searching for AcylCer...")}
msobject <- idAcylCerneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("SM" %in% lipidClasses){
if(verbose){cat("\n Searching for SM...")}
msobject <- idSMneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("CL" %in% lipidClasses){
if(verbose){cat("\n Searching for CL...")}
msobject <- idCLneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if ("BA" %in% lipidClasses){
if(verbose){cat("\n Searching for Bile acids...")}
msobject <- idBAneg(msobject = msobject, ppm_precursor = ppm_precursor,
ppm_products = ppm_products, rttol = rttol,
coelCutoff = coelCutoff, dbs = dbs, verbose = verbose)
if(verbose){cat("OK")}
}
if(verbose){cat("\n Preparing output...")}
msobject <- crossTables(msobject,
ppm = ppm_precursor,
rttol = rttol,
dbs = dbs)
if(verbose){cat("OK\n")}
return(msobject)
}
# idFAneg
#' Fatty Acids (FA) annotation for ESI-
#'
#' FA identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for FA in ESI-. Adducts allowed can
#' be modified in addutcsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idFAneg} function involves 2 steps. 1) FullMS-based
#' identification of candidate FA as M-H or 2M-H. 2) Search of FA class
#' fragments: neutral loss of H2O coeluting with the precursor ion or the
#' molecular ion.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, just MS-only or Subclass level (if any class fragment is defined) are
#' possible) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idFAneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maribel_alcoriza@iislafe.es>
idFAneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H", "2M-H"),
clfrags = c("fa_M-H", "fa_M-H-H2O"),
clrequired = c(FALSE, FALSE),
ftype = c("BB", "BB"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "FA",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("FA" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious FA annotations removed")}
msobject$annotation$detailsAnnotation$FA <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$fadb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb = list(),
intrules = c(), intConf = list(), nchains = 0,
class="FA",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$FA <- list()
msobject$annotation$detailsAnnotation$FA$candidates <- candidates
msobject$annotation$detailsAnnotation$FA$classfragments <- classConf$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$FA$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$FA <- list()
}
return(msobject)
}
# idFAHFAneg
#' FAHFA annotation for ESI-
#'
#' FAHFA identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for FAHFA in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idFAHFAneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate FAHFA as M-H. 2) Search of FAHFA class fragments:
#' there is't any class fragment by default. 3) Search of specific fragments
#' that inform about chain composition in sn1 (HFA as M-H resulting from the
#' loss of the FA chain) and sn2 (FA chain as M-H). 4) Look for possible
#' chains structure based on the combination of chain fragments. 5) Check
#' intensity rules to confirm chains position. In this case, HFA intensity has
#' to be higher than FA.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idFAHFAneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idFAHFAneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(),
clrequired = c(),
ftype = c(),
chainfrags_sn1 = c("hfa_M-H"),
chainfrags_sn2 = c("fa_M-H"),
intrules = c("hfa_sn1/fa_sn2"),
rates = c("3/1"),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous FAHFA annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "FAHFA",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("FAHFA" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious FAHFA annotations removed")}
msobject$annotation$detailsAnnotation$FAHFA <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$fahfadb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="FAHFA",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$FAHFA <- list()
msobject$annotation$detailsAnnotation$FAHFA$candidates <- candidates
msobject$annotation$detailsAnnotation$FAHFA$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$FAHFA$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$FAHFA$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$FAHFA <- list()
}
return(msobject)
}
# idLPCneg
#' Lysophosphocholines (LPC) annotation for ESI-
#'
#' LPC identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for LPC in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments. See \link{chainFrags} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idLPCneg} function involves 3 steps. 1) FullMS-based
#' identification of candidate LPC as M+CH3COO, M-CH3 and M+CH3COO-CH3. To avoid
#' incorrect annotations of PE as PC, candidates which are present just as M-CH3
#' will be ignored. 2) Search of LPC class fragments: 168.0426, 224.0688, lysoPA
#' as M-H or lysoPC as M-CH3 coeluting with the precursor ion. 3) Search of
#' specific fragments that confirm chain composition (FA as M-H).
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, as LPC only have one chain, only Subclass and FA level are possible)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idLPCneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idLPCneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M+CH3COO", "M-CH3", "M+CH3COO-CH3"),
clfrags = c(168.0426, 224.0688, "lysopa_M-H", "lysopc_M-CH3"),
clrequired = c(F, F, F, F),
ftype = c("F", "F", "BB", "BB"),
chainfrags_sn1 = c("fa_M-H"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous LPC annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "LPC",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("LPC" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious LPC annotations removed")}
msobject$annotation$detailsAnnotation$LPC <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$lysopcdb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=1, sn1)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules = c(), rates = c(),
intrequired = c(), nchains=1,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb,
intrules = c(), intConf, nchains = 1, class="LPC",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPC <- list()
msobject$annotation$detailsAnnotation$LPC$candidates <- candidates
msobject$annotation$detailsAnnotation$LPC$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$LPC$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$LPC$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPC <- list()
}
return(msobject)
}
# idLPEneg
#' Lysophosphoethanolamines (LPE) annotation for ESI-
#'
#' LPE identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for LPE in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments. See \link{chainFrags} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idLPEneg} function involves 3 steps. 1) FullMS-based
#' identification of candidate LPE as M-H. 2) Search of
#' LPE class fragments: 140.0115, 196.038 and 214.048 coeluting with the
#' precursor ion. If a loss of CH3 group is found coeluting with any candidate,
#' this will be excluded as it is a characteristic fragment of LPC.3) Search of
#' specific fragments that confirm chain composition (FA as M-H).
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, as LPE only have one chain, only Subclass and FA level are possible)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idLPEneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idLPEneg <- function(msobject, ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(140.0115, 196.038, 214.048, "lysope_M-CH3"),
clrequired = c(F, F, F, "excluding"),
ftype = c("F", "F", "F", "BB"),
chainfrags_sn1 = c("fa_M-H"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "LPE",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("LPE" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious LPE annotations removed")}
msobject$annotation$detailsAnnotation$LPE <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$lysopedb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=1, sn1)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules = c(), rates = c(),
intrequired = c(), nchains=1,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb,
intrules = c(), intConf, nchains = 1, class="LPE",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPE <- list()
msobject$annotation$detailsAnnotation$LPE$candidates <- candidates
msobject$annotation$detailsAnnotation$LPE$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$LPE$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$LPE$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPE <- list()
}
return(msobject)
}
# idLPGneg
#' Lysophosphoglycerols (LPG) annotation for ESI-
#'
#' LPG identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for LPG in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments. See \link{chainFrags} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idLPGneg} function involves 3 steps. 1) FullMS-based
#' identification of candidate LPG as M-H. 2) Search of LPG class fragments:
#' 152.9958, 227.0326, 209.022 and neutral loss of 74.0359 coeluting with the
#' precursor ion. 3) Search of specific fragments that confirm chain composition
#' (FA as M-H).
#'
#' Results data frame shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, as LPG only have one chain, only Subclass and FA level are possible)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idLPGneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idLPGneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(152.9958, 227.0326, 209.022, 74.0359),
clrequired = c(F, F, F, F),
ftype = c("F", "F", "F", "NL"),
chainfrags_sn1 = c("fa_M-H"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "LPG",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("LPG" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious LPG annotations removed")}
msobject$annotation$detailsAnnotation$LPG <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$lysopgdb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=1, sn1)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules = c(), rates = c(),
intrequired = c(), nchains=1,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb,
intrules = c(), intConf, nchains = 1, class="LPG",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPG <- list()
msobject$annotation$detailsAnnotation$LPG$candidates <- candidates
msobject$annotation$detailsAnnotation$LPG$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$LPG$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$LPG$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPG <- list()
}
return(msobject)
}
# idLPIneg
#' Lysophosphoinositols (LPI) annotation for ESI-
#'
#' LPI identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for LPI in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments. See \link{chainFrags} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idLPIneg} function involves 3 steps. 1) FullMS-based
#' identification of candidate LPI as M-H. 2) Search of
#' LPI class fragments: 241.0115, 223.0008, 259.0219 and 297.0375 coeluting
#' with the precursor ion. 3) Search of specific fragments that confirm chain
#' composition (FA as M-H).
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, as LPI only have one chain, only Subclass and FA level are possible)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idLPIneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idLPIneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(241.0115, 223.0008, 259.0219, 297.0375),
clrequired = c(F, F, F, F),
ftype = c("F", "F", "F", "F"),
chainfrags_sn1 = c("fa_M-H"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "LPI",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("LPI" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious LPI annotations removed")}
msobject$annotation$detailsAnnotation$LPI <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$lysopidb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=1, sn1)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules = c(), rates = c(),
intrequired = c(), nchains=1,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb,
intrules = c(), intConf, nchains = 1, class="LPI",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPI <- list()
msobject$annotation$detailsAnnotation$LPI$candidates <- candidates
msobject$annotation$detailsAnnotation$LPI$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$LPI$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$LPI$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPI <- list()
}
return(msobject)
}
# idLPSneg
#' Lysophosphoserines (LPS) annotation for ESI-
#'
#' LPS identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for LPS in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments. See \link{chainFrags} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idLPSneg} function involves 3 steps. 1) FullMS-based
#' identification of candidate LPS as M-H and M+Na-2H. 2) Search of
#' LPS class fragments: neutral loss of 87.032 coeluting with the precursor ion.
#' 3) Search of specific fragments that confirm chain composition (FA as M-H).
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, as LPS only have one chain, only Subclass and FA level are possible)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idLPSneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idLPSneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H", "M+Na-2H"),
clfrags = c(87.032),
clrequired = c(F),
ftype = c("NL"),
chainfrags_sn1 = c("fa_M-H"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "LPS",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("LPS" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious LPS annotations removed")}
msobject$annotation$detailsAnnotation$LPS <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$lysopsdb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=1, sn1)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules = c(), rates = c(),
intrequired = c(), nchains=1,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb,
intrules = c(), intConf, nchains = 1, class="LPS",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPS <- list()
msobject$annotation$detailsAnnotation$LPS$candidates <- candidates
msobject$annotation$detailsAnnotation$LPS$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$LPS$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$LPS$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$LPS <- list()
}
return(msobject)
}
# idPCneg
#' Phosphocholines (PC) annotation for ESI-
#'
#' PC identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PC in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPCneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PC as M+CH3COO, M-CH3 or M+CH3COO-CH3. To avoid
#' incorrect annotations of PE as PC, candidates which are present just as M-CH3
#' will be ignored. 2) Search of PC class fragments: 168.0426, 224.0688 or loss
#' of CH3 coeluting with the precursor ion. 3) Search of specific fragments that
#' inform about chain composition in sn1 (lysoPC as M-CH3 resulting from the
#' loss of the FA chain at sn2) and sn2 (lysoPC as M-CH3 resulting from the loss
#' of sn1 or FA as M-H). 4) Look for possible chains structure based on the
#' combination of chain fragments. 5) Check intensity rules to confirm chains
#' position. In this case, lysoPC from sn1 is at least 3 times more intense than
#' lysoPC from sn2.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPCneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPCneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M+CH3COO", "M-CH3", "M+CH3COO-CH3"),
clfrags = c(168.0426, 224.0688, "pc_M-CH3"),
clrequired = c(F, F, F),
ftype = c("F", "F", "BB"),
chainfrags_sn1 = c("lysopc_M-CH3"),
chainfrags_sn2 = c("fa_M-H", "lysopc_M-CH3"),
intrules = c("lysopc_sn1/lysopc_sn2"),
rates = c("3/1"),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PC",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PC" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PC annotations removed")}
msobject$annotation$detailsAnnotation$PC <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$pcdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
# remove PC which ony appear as M-CH3
if(length(adducts) > 1 & "M-CH3" %in% adducts){
candidates <- candidates[candidates$adducts != "M-CH3",]
}
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains = 2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains = 2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class = "PC",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PC <- list()
msobject$annotation$detailsAnnotation$PC$candidates <- candidates
msobject$annotation$detailsAnnotation$PC$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PC$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PC$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PC <- list()
}
return(msobject)
}
# idPConeg
#' Plasmanyl Phosphocholines (PCo) annotation for ESI-
#'
#' PCo identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PCo in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPConeg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PCo as M+CH3COO, M-CH3 or M+CH3COO-CH3. To avoid
#' incorrect annotations of PEo as PCo, candidates which are present just as M-CH3
#' will be ignored. 2) Search of PCo class fragments: 168.0426, 224.0688 or loss
#' of CH3 coeluting with the precursor ion. 3) Search of specific fragments that
#' inform about chain composition in sn1 (LPCo as M-CH3 and M-CH3-H2O resulting
#' from the loss of the FA chain at sn2) and sn2 (FA as M-H and M-CO2-H).
#' 4) Look for possible chains structure based on the combination of chain
#' fragments. 5) Check intensity rules to confirm chains position. In this case,
#' FA fragments from sn2 are at least 3 times more intense than LPCo from sn1.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPCneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPConeg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M+CH3COO", "M-CH3", "M+CH3COO-CH3"),
clfrags = c(168.0426, 224.0688, "pco_M-CH3"),
clrequired = c(F, F, F),
ftype = c("F", "F", "BB"),
chainfrags_sn1 = c("lysopco_M-CH3", "lysopco_M-CH3-H2O"),
chainfrags_sn2 = c("fa_M-H", "fa_M-CO2-H"),
intrules = c("lysopco_sn1/fa_sn2"),
rates = c(1/3),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PCo",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PCo" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PCo annotations removed")}
msobject$annotation$detailsAnnotation$PCo <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$pcodb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
# remove PCo which ony appear as M-CH3 to avoid wrong annotations of PEo
if(length(adducts) > 1 & "M-CH3" %in% adducts){
candidates <- candidates[candidates$adducts != "M-CH3",]
}
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PCo",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PCo <- list()
msobject$annotation$detailsAnnotation$PCo$candidates <- candidates
msobject$annotation$detailsAnnotation$PCo$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PCo$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PCo$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PCo <- list()
}
return(msobject)
}
# idPCpneg
#' Plasmenyl Phosphocholines (PCp) annotation for ESI-
#'
#' PCp identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PCp in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPCpneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PCp as M+CH3COO, M-CH3 or M+CH3COO-CH3. To avoid
#' incorrect annotations of PEp as PCp, candidates which are present just as M-CH3
#' will be ignored. 2) Search of PCp class fragments: 168.0426, 224.0688 or loss
#' of CH3 coeluting with the precursor ion. 3) Search of specific fragments that
#' inform about chain composition in sn1 (LPCp as M-CH3 and M-CH3-H2O resulting
#' from the loss of the FA chain at sn2) and sn2 (FA as M-H and M-CO2-H).
#' 4) Look for possible chains structure based on the combination of chain
#' fragments. 5) Check intensity rules to confirm chains position. In this case,
#' FA fragments from sn2 are at least 3 times more intense than LPCp from sn1.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPCpneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPCpneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M+CH3COO", "M-CH3", "M+CH3COO-CH3"),
clfrags = c(168.0426, 224.0688, "pcp_M-CH3"),
clrequired = c(F, F, F),
ftype = c("F", "F", "BB"),
chainfrags_sn1 = c("lysopcp_M-CH3", "lysopcp_M-CH3-H2O"),
chainfrags_sn2 = c("fa_M-H", "fa_M-CO2-H"),
intrules = c("lysopcp_sn1/fa_sn2"),
rates = c(1/3),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PCp",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PCp" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PC annotations removed")}
msobject$annotation$detailsAnnotation$PCp <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$pcpdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
# remove PCp which ony appear as M-CH3 to avoid wrong annotations of PEp
if(length(adducts) > 1 & "M-CH3" %in% adducts){
candidates <- candidates[candidates$adducts != "M-CH3",]
}
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PCp",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PCp <- list()
msobject$annotation$detailsAnnotation$PCp$candidates <- candidates
msobject$annotation$detailsAnnotation$PCp$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PCp$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PCp$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PCp <- list()
}
return(msobject)
}
# idPEneg
#' Phosphoethanolamines (PE) annotation for ESI-
#'
#' PE identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PE in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPEneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PE as M-H. 2) Search of PE class fragments:
#' 140.0115, 196.038, 214.048 ion coeluting with the precursor ion. If a loss of
#' CH3 group is found coeluting with any candidate, this will be excluded as it
#' is a characteristic fragment of PC. 3) Search of specific fragments that
#' inform about chain composition in sn1 (lysoPE as M-H resulting from the loss
#' of the FA chain at sn2) and sn2 (lysoPE as M-H resulting from the loss
#' of the FA chain at sn1 or FA chain as M-H). 4) Look for possible
#' chains structure based on the combination of chain fragments. 5) Check
#' intensity rules to confirm chains position. In this case, lysoPE from sn1 is
#' at least 3 times more intense than lysoPE from sn2.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPEneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPEneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 5,
rt,
adducts = c("M-H"),
clfrags = c(140.0118, 196.038, 214.048, "pe_M-CH3"),
clrequired = c(F, F, F, "excluding"),
ftype = c("F", "F", "F", "BB"),
chainfrags_sn1 = c("lysope_M-H"),
chainfrags_sn2 = c("lysope_M-H", "fa_M-H"),
intrules = c("lysope_sn1/lysope_sn2"),
rates = c("3/1"),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PE",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PE" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PE annotations removed")}
msobject$annotation$detailsAnnotation$PE <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$pedb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PE",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PE <- list()
msobject$annotation$detailsAnnotation$PE$candidates <- candidates
msobject$annotation$detailsAnnotation$PE$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PE$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PE$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PE <- list()
}
return(msobject)
}
# idPEoneg
#' Plasmanyl Phosphoethanolamines (PEo) annotation for ESI-
#'
#' PEo identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PEo in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPEoneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PEo as M-H and M+NaCH3COO. 2) Search
#' of PEo class fragments: 140.0115, 196.038, 214.048 ion coeluting with the
#' precursor ion. If a loss of CH3 group is found coeluting with any candidate,
#' this will be excluded as it is a characteristic fragment of PCo. 3) Search of
#' specific fragments that inform about chain composition in sn1 (lysoPEo as M-H
#' and M-H-H2O resulting from the loss of the FA chain at sn2) and sn2 (FA chain
#' as M-H). 4) Look for possible chains structure based on the combination of
#' chain fragments. 5) Check intensity rules to confirm chains position. In this
#' case, FA fragments from sn2 are at least 3 times more intense than LPEo from
#' sn1.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPEoneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPEoneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 5,
rt,
adducts = c("M-H", "M+NaCH3COO"),
clfrags = c(140.0118, 196.038, 214.048, "peo_M-CH3"),
clrequired = c(F, F, F, "excluding"),
ftype = c("F", "F", "F", "BB"),
chainfrags_sn1 = c("lysopeo_M-H", "lysopeo_M-H-H2O"),
chainfrags_sn2 = c("fa_M-H"),
intrules = c("lysopeo_sn1/fa_sn2"),
rates = c(1/3),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PEo",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PEo" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PEo annotations removed")}
msobject$annotation$detailsAnnotation$PEo <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$peodb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PEo",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PEo <- list()
msobject$annotation$detailsAnnotation$PEo$candidates <- candidates
msobject$annotation$detailsAnnotation$PEo$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PEo$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PEo$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PEo <- list()
}
return(msobject)
}
# idPEpneg
#' Plasmenyl Phosphoethanolamines (PEp) annotation for ESI-
#'
#' PEp identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PEp in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPEpneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PEp as M-H and M+NaCH3COO. 2) Search
#' of PEp class fragments: 140.0115, 196.038, 214.048 ion coeluting with the
#' precursor ion. If a loss of CH3 group is found coeluting with any candidate,
#' this will be excluded as it is a characteristic fragment of PCp. 3) Search of
#' specific fragments that inform about chain composition in sn1 (lysoPEp as M-H
#' and M-H-H2O resulting from the loss of the FA chain at sn2) and sn2 (FA chain
#' as M-H). 4) Look for possible chains structure based on the combination of
#' chain fragments. 5) Check intensity rules to confirm chains position. In this
#' case, FA fragments from sn2 are at least 3 times more intense than LPEp from
#' sn1.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPEoneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPEpneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 5,
rt,
adducts = c("M-H", "M+NaCH3COO"),
clfrags = c(140.0118, 196.038, 214.048, "pep_M-CH3"),
clrequired = c(F, F, F, "excluding"),
ftype = c("F", "F", "F", "BB"),
chainfrags_sn1 = c("lysopep_M-H", "lysopep_M-H-H2O"),
chainfrags_sn2 = c("fa_M-H"),
intrules = c("lysopep_sn1/fa_sn2"),
rates = c(1/3),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PEp",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PEp" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PEp annotations removed")}
msobject$annotation$detailsAnnotation$PEp <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$pepdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PEp",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PEp <- list()
msobject$annotation$detailsAnnotation$PEp$candidates <- candidates
msobject$annotation$detailsAnnotation$PEp$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PEp$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PEp$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PEp <- list()
}
return(msobject)
}
# idPGneg
#' Phosphoglycerols (PG) annotation for ESI-
#'
#' PG identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PG in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPGneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PG as M-H. 2) Search of PG class fragments:
#' 152.9958, 227.0326, 209.022 and neutral loss of 74.0359 coeluting with the
#' precursor ion. 3) Search of specific fragments that inform about chain
#' composition at sn1 (lysoPG as M-H resulting from the loss of the FA chain
#' at sn2) and sn2 (lysoPG as M-H resulting from the loss of the FA chain
#' at sn1 or FA chain as M-H). 4) Look for possible chains structure
#' based on the combination of chain fragments. 5) Check intensity rules to
#' confirm chains position. In this case, lysoPG from sn1 is at least 3 times
#' more intense than lysoPG from sn2.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPGneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPGneg <- function(msobject, ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(152.9958, 227.0326, 209.022, 74.0359),
clrequired = c(F, F, F, F),
ftype = c("F", "F", "F", "NL"),
chainfrags_sn1 = c("lysopg_M-H"),
chainfrags_sn2 = c("lysopg_M-H", "fa_M-H"),
intrules = c("lysopg_sn1/lysopg_sn2"),
rates = c("2/1"),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PG",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PG" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PG annotations removed")}
msobject$annotation$detailsAnnotation$PG <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$pgdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PG",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PG <- list()
msobject$annotation$detailsAnnotation$PG$candidates <- candidates
msobject$annotation$detailsAnnotation$PG$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PG$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PG$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PG <- list()
}
return(msobject)
}
# idPIneg
#' Phosphoinositols (PI) annotation for ESI-
#'
#' PI identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PI in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPIneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PI as M-H. 2) Search of PI class fragments:
#' 241.0115, 223.0008, 259.0219 and 297.0375 coeluting with the precursor
#' ion. 3) Search of specific fragments that inform about chain composition at
#' sn1 (lysoPI as M-H resulting from the loss of the FA chain at sn2 or lysoPA
#' as M-H if it also losses the head group) and sn2 (lysoPI or lysoPA as M-H
#' resulting from the loss of the FA chain at sn1 or FA chain as M-H). 4) Look
#' for possible chains structure based on the combination of chain fragments.
#' 5) Check intensity rules to confirm chains position. In this case, lysoPI or
#' lysoPA from sn1 is at least 3 times more intense than lysoPI or lysoPA from
#' sn2.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPIneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPIneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(241.0115, 223.0008, 259.0219, 297.0375),
clrequired = c(F, F, F, F),
ftype = c("F", "F", "F", "F"),
chainfrags_sn1 = c("lysopi_M-H", "lysopa_M-H"),
chainfrags_sn2 = c("lysopi_M-H", "lysopa_M-H", "fa_M-H"),
intrules = c("lysopi_sn1/lysopi_sn2", "lysopa_sn1/lysopa_sn2"),
rates = c("3/1", "3/1"),
intrequired = c(F, F),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PI",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PI" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PI annotations removed")}
msobject$annotation$detailsAnnotation$Cer <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$pidb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PI",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PI <- list()
msobject$annotation$detailsAnnotation$PI$candidates <- candidates
msobject$annotation$detailsAnnotation$PI$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PI$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PI$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PI <- list()
}
return(msobject)
}
# idPSneg
#' Phosphoserines (PS) annotation for ESI-
#'
#' PS identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PS in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idPSneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate PS as M-H or M+Na-2H. 2) Search of PS class
#' fragments: neutral loss of 87.032 (serine) coeluting with the precursor ion.
#' 3) Search of specific fragments that inform about chain composition at sn1
#' (lysoPA as M-H or M-H-H2O resulting from the loss of the FA chain at sn2 and
#' the head group) and sn2 (lysoPA as M-H or M-H-H2O resulting from the loss of
#' the FA chain at sn1 and the head group or FA chain as M-H). 4) Look for
#' possible chains structure based on the combination of chain fragments.
#' 5) Check intensity rules to confirm chains position. In this case, lysoPA
#' from sn1 is at least 3 times more intense than lysoPA from sn2.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idPSneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idPSneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H", "M+Na-2H"),
clfrags = c(87.032, 152.9958),
clrequired = c(F, F),
ftype = c("NL", "F"),
chainfrags_sn1 = c("lysopa_M-H", "lysopa_M-H-H2O"),
chainfrags_sn2 = c("lysopa_M-H", "lysopa_M-H-H2O", "fa_M-H"),
intrules = c("lysopa_sn1/lysopa_sn2"),
rates = c("3/1"),
intrequired = c(T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "PS",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("PS" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious PS annotations removed")}
msobject$annotation$detailsAnnotation$PS <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$psdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="PS",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PS <- list()
msobject$annotation$detailsAnnotation$PS$candidates <- candidates
msobject$annotation$detailsAnnotation$PS$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$PS$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$PS$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$PS <- list()
}
return(msobject)
}
# idSphneg
#' Sphingoid bases (Sph) annotation for ESI-
#'
#' Sph identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for Sph in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idSphneg} function involves 2 steps. 1) FullMS-based
#' identification of candidate Sph as M-H. 2) Search of Sph class fragments:
#' neutral loss of 1 or 2 H2O molecules.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, as Sph only have one chain, only Subclass and FA level are possible)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idSphneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idSphneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3, rt,
adducts = c("M-H"),
clfrags = c("sph_M-H-H2O", "sph_M-H-2H2O"),
clrequired = c(F, F),
ftype = c("BB", "BB"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "Sph",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("Sph" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious Sph annotations removed")}
msobject$annotation$detailsAnnotation$Sph <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$sphdb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb = list(),
intrules = c(), intConf = list(), nchains = 0,
class="Sph",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$Sph <- list()
msobject$annotation$detailsAnnotation$Sph$candidates <- candidates
msobject$annotation$detailsAnnotation$Sph$classfragments <- classConf$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$Sph$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$Sph <- list()
}
return(msobject)
}
# idSphPpneg
#' Sphingoid bases phosphate (SphP) annotation for ESI-
#'
#' SphP identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for SphP in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idSphpos} function involves 2 steps. 1) FullMS-based
#' identification of candidate SphP as M-H. 2) Search of SphP class fragments:
#' 78.9585, 96.969 or neutral loss of 1 H2O molecule.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (in this
#' case, as SphP only have one chain, only Subclass and FA level are possible)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idSphPneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idSphPneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(78.9585, 96.9691, "sphP_M-H-H2O"),
clrequired = c(F, F, F),
ftype = c("F", "F", "BB"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "SphP",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("SphP" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious SphP annotations removed")}
msobject$annotation$detailsAnnotation$SphP <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$sphPdb, ppm = ppm_precursor,
rt = rt, adducts = adducts, rttol = rttol,
dbs = dbs, rawData = rawData,
coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb = list(),
intrules = c(), intConf = list(), nchains = 0,
class="SphP",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$SphP <- list()
msobject$annotation$detailsAnnotation$SphP$candidates <- candidates
msobject$annotation$detailsAnnotation$SphP$classfragments <- classConf$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$SphP$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$SphP <- list()
}
return(msobject)
}
# idCerneg
#' Ceramides (Cer) annotation for ESI-
#'
#' Cer identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for Cer in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected ratesbetween fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idCerneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate Cer as M-H and M+CH3COO. 2) Search of Cer class
#' fragments: there are no class fragment by default. 3) Search of specific
#' fragments that inform about the sphingoid base (Sph as M-H-2H2O resulting
#' from the loss of the FA chain or loss of part of the sphingoid base) and the
#' FA chain (FA as M-H but with a N instead of an O, what means a mass difference
#' of 1.9918 from the exact mass of the FA or FA as M-H-H2O). 4) Look for
#' possible chains structure based on the combination of chain fragments.
#' 5) Check intensity rules to confirm chains position. In this case, there are
#' no intensity rules by default.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idCerneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idCerneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H","M+CH3COO"),
clfrags = c(),
clrequired = c(),
ftype = c(),
chainfrags_sn1 = c("NL-nlsph_M-H", "sph_M-H-2H2O", "sph_M-H-H2O"),
chainfrags_sn2 = c("fa_Mn-1.9918", "fa_M-H-H2O"),
intrules = c(),
rates = c(),
intrequired = c(),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "Cer",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("Cer" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious Ceramide annotations removed")}
msobject$annotation$detailsAnnotation$Cer <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$cerdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="Cer",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$Cer <- list()
msobject$annotation$detailsAnnotation$Cer$candidates <- candidates
msobject$annotation$detailsAnnotation$Cer$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$Cer$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$Cer$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$Cer <- list()
}
return(msobject)
}
# idCerPneg
#' Ceramides phosphate (CerP) annotation for ESI-
#'
#' CerP identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for CerP in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected ratesbetween fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idCerPneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate CerP as M-H. 2) Search of CerP class
#' fragments: 78.9585 and 96.9691. 3) Search of specific fragments that inform
#' about the sphingoid base (SphP as M-H resulting from the loss of the FA chain)
#' and the FA chain (FA as M-H but with a N instead of an O, what results in a
#' mass difference of 1.9918 from the exact mass of the FA, or the difference
#' between precursor and sn1 chain fragments). 4) Look for possible chains
#' structure based on the combination of chain fragments. 5) Check intensity
#' rules to confirm chains position. In this case, there are no intensity rules
#' by default.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idCerPneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idCerPneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
clfrags = c(78.9585, 96.9691),
clrequired = c(F, F),
ftype = c("F", "F"),
chainfrags_sn1 = c("sphP_M-H"),
chainfrags_sn2 = c("fa_Mn-1.9918", ""),
intrules = c(),
rates = c(),
intrequired = c(),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "CerP",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("CerP" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious CeramideP annotations removed")}
msobject$annotation$detailsAnnotation$CerP <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$cerPdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="CerP",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$CerP <- list()
msobject$annotation$detailsAnnotation$CerP$candidates <- candidates
msobject$annotation$detailsAnnotation$CerP$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$CerP$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$CerP$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$CerP <- list()
}
return(msobject)
}
# idAcylCerneg
#' Acylceramides (AcylCer) annotation for ESI-
#'
#' AcylCer identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for AcylCer in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the sphingoid base. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param chainfrags_sn3 character vector containing the fragmentation rules for
#' the acyl chain. See \link{chainFrags} for details.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected ratesbetween fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idAcylCerneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate AcylCer as M-H and M+CH3COO. 2) Search of AcylCer
#' class fragments: no class fragments by default. 3) Search of specific fragments
#' that inform about the acyl chain (Cer as M-H), the sphingoid base (neutral
#' loss of 62.0600 of the Sph) and the FA chain (FA as M-H and M-H2O but with a N
#' instead of an O, what results in a mass differences of 1.9918 and 19.0179
#' respectively). 4) Look for possible chains structure based on the combination
#' of chain fragments. 5) Check intensity rules to confirm chains position. In
#' this case, the fragment coming from the loss of the acyl chain must be at least
#' 5 times more intense the fragment from the sphingoid base and this one, two
#' times more intense than the FA chain from sn3.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idAcylCerneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idAcylCerneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H", "M+CH3COO"),
clfrags = c(),
clrequired = c(),
ftype = c(),
chainfrags_sn1 = c("cbdiff-cer_M-H"),
chainfrags_sn2 = c("sph_Mn-62.06001", "sph_M-H-H2O"),
chainfrags_sn3 = c("fa_Mn-1.9918", "fa_Mn-19.0179"),
intrules = c("cbdiff-cer_sn1/sph_sn2", "sph_sn2/fa_sn3"),
rates = c("5/1", "2/1"),
intrequired = c(T, T),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "AcylCer",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("AcylCer" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious AcylCer annotations removed")}
msobject$annotation$detailsAnnotation$AcylCer <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$acylcerdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
sn3 <- chainFrags(coelfrags, chainfrags_sn3, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=3, sn1, sn2, sn3)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 3, class="AcylCer",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$AcylCer <- list()
msobject$annotation$detailsAnnotation$AcylCer$candidates <- candidates
msobject$annotation$detailsAnnotation$AcylCer$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$AcylCer$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$AcylCer$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$AcylCer <- list()
}
return(msobject)
}
# idCLneg
#' Cardiolipines (CL) annotation for ESI-
#'
#' CL identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for CL in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details.
#' @param chainfrags_sn3 character vector containing the fragmentation rules for
#' the chain fragments in sn3 position. See \link{chainFrags} for details.
#' @param chainfrags_sn4 character vector containing the fragmentation rules for
#' the chain fragments in sn4 position. See \link{chainFrags} for details.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}. If some intensity rules should be employed to
#' identify the chains position but they are't known yet, use "Unknown". If it
#' isn't required, leave an empty vector.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idCLneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate CL as M-H or M-2H. 2) Search of CL class fragments:
#' no class fragments are searched by defaults as they use to have bad coelution
#' scores. 3) Search of specific fragments that inform about chain composition
#' at sn1 (lysoPA as M-H-H2O), sn2 (lysoPA as M-H-H2O), sn3 (lysoPA as M-H-H2O)
#' and sn4 (lysoPA as M-H-H2O). 4) Look for possible chains structure based on
#' the combination of chain fragments. 5) Check intensity rules to confirm
#' chains position. For CL there are no intensity rules by default.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idCLneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idCLneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 5,
rt,
adducts = c("M-H", "M+Na-2H"),
clfrags = c(),
clrequired = c(),
ftype = c(),
chainfrags_sn1 = c("lysopa_M-H-H2O"),
chainfrags_sn2 = c("lysopa_M-H-H2O"),
chainfrags_sn3 = c("lysopa_M-H-H2O"),
chainfrags_sn4 = c("lysopa_M-H-H2O"),
intrules = c("Unknown"),
rates = c(),
intrequired = c(),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "CL",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("CL" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious CL annotations removed")}
msobject$annotation$detailsAnnotation$CL <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$cldb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
sn3 <- chainFrags(coelfrags, chainfrags_sn3, ppm_products, candidates, sn1,
dbs)
sn4 <- chainFrags(coelfrags, chainfrags_sn4, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=4, sn1, sn2, sn3, sn4)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=4,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 4, class="CL",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$CL <- list()
msobject$annotation$detailsAnnotation$CL$candidates <- candidates
msobject$annotation$detailsAnnotation$CL$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$CL$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$CL$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$CL <- list()
}
return(msobject)
}
# idBAneg
#' Bile Acids (BA) annotation for ESI-
#'
#' BA identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for BA in ESI-. Adducts allowed can
#' be modified in the adducsTable (dbs argument).
#' @param conjfrag character vector containing the fragmentation rules for
#' the BA-conjugates. By default just taurine and glycine are considered,
#' but baconjdb can be modified to add more possible conjugates.
#' See \link{chainFrags} for details. It can also be an empty vector.
#' @param bafrag character vector containing the fragmentation rules for
#' other BA fragments. See \link{chainFrags} for details. It can be an empty
#' vector.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idBAneg} function involves 3 steps. 1) FullMS-based
#' identification of candidate BA as M-H. 2) Search of BA-conjugate fragments if
#' required. 3) Search of fragments coming from the loss of H2O.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (MS-only
#' if no rules are defined, or Subclass level if they are supported by fragments)
#' and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idBAneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idBAneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M-H"),
conjfrag = c("baconj_M-H"),
bafrag = c("ba_M-H-H2O", "ba_M-H-2H2O"),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "BA",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("BA" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious BA annotations removed")}
msobject$annotation$detailsAnnotation$BA <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$badb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# search fragments
check <- rep(list(vector()), nrow(candidates))
conjugates <- rep(list(vector()), nrow(candidates))
bas <- rep(list(vector()), nrow(candidates))
if (length(conjfrag) > 0){
conjugates <- chainFrags(coelfrags, conjfrag, ppm_products, dbs = dbs,
candidates = candidates)
for (c in 1:nrow(candidates)){
if (nrow(conjugates[[c]]) > 0){
if (dbs$badb[dbs$badb$total ==
candidates$cb[c], "conjugate"] %in%
conjugates[[c]]$cb | dbs$badb[dbs$badb$total ==
candidates$cb[c],
"conjugate"] == ""){
check[[c]] <- append(check[[c]], TRUE)
} else {
check[[c]] <- append(check[[c]], FALSE)
}
} else if (dbs$badb[dbs$badb$total ==
candidates$cb[c],
"conjugate"] == ""){
check[[c]] <- append(check[[c]], TRUE)
conjugates[[c]] <- data.frame(0,0,0,0,0,0,0,0)
colnames(conjugates[[c]]) <- c("cb", "mz", "RT", "int",
"peakID", "coelScore", "db", "adduct")
} else {
check[[c]] <- append(check[[c]], FALSE)
conjugates[[c]] <- data.frame(0,0,0,0,0,0,0,0)
colnames(conjugates[[c]]) <- c("cb", "mz", "RT", "int",
"peakID", "coelScore", "db", "adduct")
}
}
classConf <- list()
}
if (length(bafrag) > 0){
bas <- chainFrags(coelfrags, bafrag, ppm_products, dbs = dbs,
candidates = candidates)
for (c in 1:nrow(candidates)){
if(nrow(bas[[c]]) > 0){
if (candidates$cb[c] %in% bas[[c]]$cb ||
dbs$badb[dbs$badb$total == candidates$cb[c], "base"]
%in% bas[[c]]$cb){
check[[c]] <- append(check[[c]], TRUE)
} else {
check[[c]] <- append(check[[c]], FALSE)
}
} else {
check[[c]] <- append(check[[c]], FALSE)
bas[[c]] <- data.frame(0,0,0,0,0,NA,0,0)
colnames(bas[[c]]) <- c("cb", "mz", "RT", "int",
"peakID", "coelScore", "db", "adduct")
}
}
}
check <- matrix(unlist(check), nrow = nrow(candidates), byrow = T)
classConf$presence <- check
classConf$passed <- unlist(apply(check, 1, sum)) > 0
classConf$fragments <- Map(rbind, conjugates, bas)
classConf$fragments <- lapply(classConf$fragments, function(x){
x[x$peakID != "0",,drop = FALSE]
})
# prepare output
if (length(bafrag) > 0 | length(conjfrag) > 0){
clfrags <- c("fragment")
} else {
clfrags <- c()
}
res <- organizeResults(candidates, coelfrags, clfrags = clfrags, classConf = classConf,
chainsComb = c(), intrules = c(),
intConf = c(), nchains = 0, class="BA",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$BA <- list()
msobject$annotation$detailsAnnotation$BA$candidates <- candidates
msobject$annotation$detailsAnnotation$BA$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$BA$chainfragments <- bas$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$BA$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$BA <- list()
}
return(msobject)
}
# idSMneg
#' Sphingomyelines (SM) annotation for ESI-
#'
#' SM identification based on fragmentation patterns for LC-MS/MS DIA or DDA
#' data acquired in negative mode.
#'
#' @param msobject an msobject returned by \link{dataProcessing}.
#' @param ppm_precursor mass tolerance for precursor ions. By default, 5 ppm.
#' @param ppm_products mass tolerance for product ions. By default, 10 ppm.
#' @param rttol total rt window for coelution between precursor and product
#' ions. By default, 3 seconds.
#' @param rt rt range where the function will look for candidates. By default,
#' it will search within all RT range in MS1.
#' @param adducts expected adducts for PC in ESI-. Adducts allowed can
#' be modified in adductsTable (dbs argument).
#' @param clfrags vector containing the expected fragments for a given lipid
#' class. See \link{checkClass} for details.
#' @param ftype character vector indicating the type of fragments in clfrags.
#' It can be: "F" (fragment), "NL" (neutral loss) or "BB" (building block).
#' See \link{checkClass} for details.
#' @param clrequired logical vector indicating if each class fragment is
#' required or not. If any of them is required, at least one of them must be
#' present within the coeluting fragments. See \link{checkClass} for details.
#' @param chainfrags_sn1 character vector containing the fragmentation rules for
#' the chain fragments in sn1 position. See \link{chainFrags} for details.
#' @param chainfrags_sn2 character vector containing the fragmentation rules for
#' the chain fragments in sn2 position. See \link{chainFrags} for details. If
#' empty, it will be estimated based on the difference between precursors and
#' sn1 chains.
#' @param intrules character vector specifying the fragments to compare. See
#' \link{checkIntensityRules}.
#' @param rates character vector with the expected rates between fragments given
#' as a string (e.g. "3/1"). See \link{checkIntensityRules}.
#' @param intrequired logical vector indicating if any of the rules is required.
#' If not, at least one must be verified to confirm the structure.
#' @param coelCutoff coelution score threshold between parent and fragment ions.
#' Only applied if rawData info is supplied. By default, 0.8.
#' @param dbs list of data bases required for annotation. By default, dbs
#' contains the required data frames based on the default fragmentation rules.
#' If these rules are modified, dbs may need to be supplied. See \link{createLipidDB}
#' and \link{assignDB}.
#' @param verbose print information messages.
#'
#' @return annotated msobject (list with several elements). The results element
#' is a data frame that shows: ID, lipid class, CDB (total number of carbons
#' and double bounds), FA composition (specific chains composition if it has
#' been confirmed), mz, RT (in seconds), I (intensity), Adducts, ppm (mz error),
#' confidenceLevel (Subclass, FA level, where chains are known but not their
#' positions, or FA position level), peakID, and Score (parent-fragment coelution
#' score mean in DIA data or relative sum intensity in DDA of all fragments used
#' for the identification).
#'
#' @details \code{idSMneg} function involves 5 steps. 1) FullMS-based
#' identification of candidate SM as M+CH3COO, M-CH3 or M+CH3COO-CH3. 2) Search
#' of SM class fragments: 168.0426, 224.0688 or loss of CH3 coeluting with the
#' precursor ion. 3) Search of specific fragments that inform about chain
#' composition in sn1 (Sph+phosphocholine as M-CH3-H2O which results in a mass
#' difference of Sph+150.032) and sn2 (difference between precursor and sn1 chain
#' fragments). 4) Look for possible chains structure based on the
#' combination of chain fragments. 5) Check intensity rules to confirm chains
#' position. In this case, there are no intensity rules by default.
#'
#' Results data frame shows: ID, lipid class, CDB (total number
#' of carbons and double bounds), FA composition (specific chains composition if
#' it has been confirmed), mz, RT (in seconds), I (intensity, which comes
#' directly from de input), Adducts, ppm (mz error), confidenceLevel (Subclass,
#' FA level, where chains are known but not their positions, or FA position
#' level) and Score (parent-fragment coelution score mean in DIA data or relative
#' sum intensity in DDA of all fragments used for the identification).
#'
#' @note This function has been writen based on fragmentation patterns
#' observed for three different platforms (QTOF 6550 from Agilent, Synapt G2-Si
#' from Waters and Q-exactive from Thermo), but it may need to be customized for
#' other platforms or acquisition settings.
#'
#' @examples
#' \dontrun{
#' msobject <- idSMneg(msobject)
#' }
#'
#' @author M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
idSMneg <- function(msobject,
ppm_precursor = 5,
ppm_products = 10,
rttol = 3,
rt,
adducts = c("M+CH3COO", "M-CH3", "M+CH3COO-CH3"),
clfrags = c(168.0426, 224.0688, "sm_M-CH3"),
clrequired = c(F, F, F),
ftype = c("F", "F", "BB"),
chainfrags_sn1 = c("sph_Mn+150.032"),
chainfrags_sn2 = c("fa_Mn-1.9918", ""),
intrules = c(),
rates = c(),
intrequired = c(),
coelCutoff = 0.8,
dbs,
verbose = TRUE){
##############################################################################
# check arguments
if (msobject$metaData$generalMetadata$polarity != "negative"){
stop("Data wasn't acquired in negative mode")
}
if (missing(dbs)){
dbs <- assignDB()
}
if (!all(c("metaData", "processing", "rawData", "peaklist") %in% names(msobject))){
stop("Wrong msobject format")
}
if (!all(c("MS1", "MS2") %in% names(msobject$rawData))){
stop("Wrong msobject format")
}
if (!msobject$metaData$generalMetadata$acquisitionmode %in% c("DIA", "DDA")){
stop("Acquisition mode must be DIA or DDA")
}
if (!all(adducts %in% dbs[["adductsTable"]]$adduct)){
stop("Some adducts can't be found at the adductsTable. Add them.")
}
if (length(clfrags) > 0){
if (length(clfrags) != length(clrequired) | length(clfrags) !=
length(ftype)){
stop("clfrags, clrequired and ftype should have the same length")
}
if (!all(ftype %in% c("F", "NL", "BB"))){
stop("ftype values allowed are: \"F\", \"NL\" or\"BB\"")
}
strfrag <- which(grepl("_", clfrags))
if (length(strfrag) > 0){
d <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 1))
a <- unlist(lapply(strsplit(clfrags[strfrag], "_"), "[[", 2))
if (!all(a %in% dbs[["adductsTable"]]$adduct)){
stop("Adducts employed in clfrags also need to be at adductsTable.")
}
if (!all(paste(d, "db", sep="") %in% names(dbs))){
stop("All required dbs must be supplied through dbs argument.")
}
}
}
##############################################################################
# extract data from msobject
# Peaklist MS1: remove isotopes
MS1 <- msobject$peaklist$MS1
MS1 <- MS1[MS1$isotope %in% c("[M+0]"),
!colnames(MS1) %in% c("isotope", "isoGroup")]
# Peaklist MS2:
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
MS2 <- msobject$rawData$MS2[,c("mz", "RT", "int", "peakID")]
} else {
MS2 <- msobject$peaklist$MS2[,c("mz", "RT", "int", "peakID")]
}
rawData <- rbind(msobject$rawData$MS1, msobject$rawData$MS2)
# if acquisition mode is DDA, extract precursors
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
precursors <- msobject$metaData$scansMetadata[msobject$metaData$scansMetadata$collisionEnergy > 0 &
msobject$metaData$scansMetadata$msLevel == 2,
c("RT", "precursor", "Scan")]
}
##############################################################################
# Remove previous ceramide annotations
if ("results" %in% names(msobject$annotation)){
if (nrow(msobject$annotation$results) > 0){
msobject$annotation$results <- msobject$annotation$results[msobject$annotation$results$Class != "SM",]
}
}
if ("detailsAnnotation" %in% names(msobject$annotation)){
if("SM" %in% names(msobject$annotation$detailsAnnotation)){
if(verbose){cat("\nPrevious SM annotations removed")}
msobject$annotation$detailsAnnotation$SM <- list()
}
}
##############################################################################
# set rt limits
if (missing(rt)){
rt <- c(min(MS1$RT), max(MS1$RT))
}
##############################################################################
# Start identification steps
# candidates search
candidates <- findCandidates(MS1, dbs$smdb, ppm = ppm_precursor, rt = rt,
adducts = adducts, rttol = rttol, dbs = dbs,
rawData = rawData, coelCutoff = coelCutoff)
if (nrow(candidates) > 0){
if (msobject$metaData$generalMetadata$acquisitionmode == "DIA"){
if (nrow(rawData) == 0){
coelCutoff <- 0 # if no rawData is supplied, coelution score between precursors and fragments will be ignored
}
# isolation of coeluting fragments
coelfrags <- coelutingFrags(candidates, MS2, rttol, rawData,
coelCutoff = coelCutoff)
} else if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
coelCutoff <- 0
coelfrags <- ddaFrags(candidates, precursors, rawData, ppm = ppm_products)
}
# check class fragments
classConf <- checkClass(candidates, coelfrags, clfrags, ftype, clrequired,
ppm_products, dbs)
# search chains fragments
sn1 <- chainFrags(coelfrags, chainfrags_sn1, ppm_products, dbs = dbs,
candidates = candidates)
sn2 <- chainFrags(coelfrags, chainfrags_sn2, ppm_products, candidates, sn1,
dbs)
# combine chain fragments
chainsComb <- combineChains(candidates, nchains=2, sn1, sn2)
# check chains position based on intensity ratios
intConf <- checkIntensityRules(intrules, rates, intrequired, nchains=2,
chainsComb)
# prepare output
res <- organizeResults(candidates, coelfrags, clfrags, classConf, chainsComb, intrules,
intConf, nchains = 2, class="SM",
acquisitionmode = msobject$metaData$generalMetadata$acquisitionmode)
# update msobject
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$SM <- list()
msobject$annotation$detailsAnnotation$SM$candidates <- candidates
msobject$annotation$detailsAnnotation$SM$classfragments <- classConf$fragments
msobject$annotation$detailsAnnotation$SM$chainfragments <- chainsComb$fragments
if (msobject$metaData$generalMetadata$acquisitionmode == "DDA"){
msobject$annotation$detailsAnnotation$SM$coelfrags <- coelfrags
}
} else {
res <- data.frame()
if ("results" %in% names(msobject$annotation)){
msobject$annotation$results <- rbind(msobject$annotation$results, res)
} else {
msobject$annotation$results <- res
}
msobject$annotation$detailsAnnotation$SM <- list()
}
return(msobject)
}
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