R/do.findmain.R
In sneumann/RAMClustR: RAMClust: a novel feature clustering method enables spectral-matching based annotation for metabolomics data
#' do.findmain
#'
#' Cluster annotation function: inference of 'M' - molecular weight of the compound giving rise to each spectrum - using the InterpretMSSpectrum::findMain function
#'
#' @param ramclustObj ramclustR object to annotate.
#' @param cmpd integer: vector defining compound numbers to annotated. if NULL (default), all compounds
#' @param mode character: "positive" or "negative"
#' @param mzabs.error numeric: absolute mass deviation allowd
#' @param ppm.error numeric: ppm mass error added to mzabs.error
#' @param ads character: vector of allowed adducts, i.e. c("[M+H]+"). if NULL, default values of H+, Na+, K+, and NH4+, as monomer, dimer, and trimer, are assigned.
#' @param nls character: vector of allowed neutral losses, i.e. c("[M+H-H2O]+"). if NULL, an extensive list derived from CAMERA's will be used.
#' @param adwts numeric: vector of weights for adducts. length should match that of 'ads', else first value will be repeated. if NULL (default), value of 1 is assigned to all. Only used for ramclustR scoring of M.
#' @param nlwts numeric: vector of weights for neutral losses. length should match that of 'nls', else first value will be repeated. if NULL (default), value of 0.1 is assigned to all. Only used for ramclustR scoring of M.
#' @param plot.findmain logical: should pdf polts be generated for evaluation?
#' @param writeMat logical: should indidual .mat files (for MSFinder) be generated in a 'mat' subdirectory in the 'spectra' folder? default = TRUE.
#' @details a partially annotated ramclustR object. base structure is that of a standard R heirarchical clustering output, with additional slots described in ramclustR documentation (?ramclustR). New slots added after using the interpretMSSpectrum functionality include those described below. .mat files written in new directory 'spectra/mat' in working directory
#' @return $M: The inferred molecular weight of the compound giving rise to the each spectrum
#' @return $M.ppm: The ppm error of all the MS signals annotated, high error values should be considered 'red flags'
#' @return $M.ann: The annotated spectrum supporting the intepretation of M
#' @return $use.findmain: Logical vector indicating whether findmain scoring (TRUE) or ramclustR scoring (FALSE) was used to support inference of M. By default, findmain scoring is used. When ramclustR scoring differs from findmain scoring, the scoring metric which predicts higher M is selected.
#' @return $M.ramclustr: M selected using ramclustR scoring
#' @return $M.ppm.ramclustr: ppm error of M selected using ramclustR scoring
#' @return $M.ann.ramclustr: annotated spectrum supporing M using ramclustR scoring
#' @return $M.findmain: M selected using findmain scoring
#' @return $M.ppm.findmain: ppm error of M selected using findmain scoring
#' @return $M.ann.findmain: annotated spectrum supporing M using findmain scoring
#' @references Jaeger C, Méret M, Schmitt CA, Lisec J. Compound annotation in liquid chromatography/high-resolution mass spectrometry based metabolomics: robust adduct ion determination as a prerequisite to structure prediction in electrospray ionization mass spectra. Rapid Commun Mass Spectrom. 2017 Aug 15;31(15):1261-1266. doi: 10.1002/rcm.7905. PubMed PMID: 28499062.
#' @references Broeckling CD, Afsar FA, Neumann S, Ben-Hur A, Prenni JE. RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data. Anal Chem. 2014 Jul 15;86(14):6812-7. doi: 10.1021/ac501530d. Epub 2014 Jun 26. PubMed PMID: 24927477.
#' @references Broeckling CD, Ganna A, Layer M, Brown K, Sutton B, Ingelsson E, Peers G, Prenni JE. Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction. Anal Chem. 2016 Sep 20;88(18):9226-34. doi: 10.1021/acs.analchem.6b02479. Epub 2016 Sep 8. PubMed PMID: 7560453.
#' @keywords 'ramclustR' 'RAMClustR', 'ramclustR', 'metabolomics', 'mass spectrometry', 'clustering', 'feature', 'xcms'
#' @author Corey Broeckling
#' @export
do.findmain <- function (ramclustObj = RC, cmpd = NULL, mode = "positive", mzabs.error = 0.01,
ppm.error = 10, ads = NULL, nls = NULL, adwts = NULL, nlwts = NULL,
plot.findmain = TRUE, writeMat = TRUE, writeMS = TRUE)
{
if (is.null(ads)) {
if (grepl("p", mode)) {
ads <- c("[M+H]+", "[M+Na]+", "[M+K]+", "[M+NH4]+", "[2M+H]+",
"[2M+Na]+", "[2M+K]+", "[2M+NH4]+", "[3M+H]+", "[3M+Na]+",
"[3M+K]+", "[3M+NH4]+")
}
if(grepl("n", mode)) {
ads <- c("[M-H]-", "[M+Na-2H]-", "[M+K-2H]-", "[M+CH2O2- H]-",
"[2M-H]-", "[2M+Na-2H]-", "[2M+K-2H]-", "[2M+CH2O2- H]-",
"[3M-H]-", "[3M+Na-2H]-", "[3M+K-2H]-", "[3M+CH2O2- H]-")
}
if(is.null(ads)) {
stop("please define adducts using 'ads' or set mode to either'positive' or 'negative'")
}
}
if (is.null(nls)) {
if (grepl("p", mode)) {
nls <- c("[M+H-NH3]+", "[M+H-H2O]+", "[M+H-COCH2]+",
"[M+H-CO2]+", "[M+H-NH3-CO2]+", "[M+H-NH3-HCOOH]+",
"[M+H-NH3-H2O]+", "[M+H-NH3-COCH2]+", "[M+H-S]+",
"[M+H-S-NH3-HCOOH]+", "[M+H-H4O2]+", "[M+H-CH2]+",
"[M+H-O]+", "[M+H-C2H2]+", "[M+H-C2H4]+", "[M+H-CO]+",
"[M+H-C3H6]+", "[M+H-C2H4O]+", "[M+H-C4H6]+", "[M+H-C3H4O]+",
"[M+H-C4H8]+", "[M+H-C5H8]+", "[M+H-C4H6O]+", "[M+H-C5H10]+",
"[M+H-C6H12]+", "[M+H-C4H8O2]+", "[M+H-H2O-HCOOH]+",
"[M+H-CH4]+", "[M+H-CH2O]+", "[M+H-C2H6]+", "[M+H-CH3OH]+",
"[M+H-C3H4]+", "[M+H-C3H6O]+", "[M+H-CO2-C3H6]+",
"[M+H-SO3]+", "[M+H-SO3-H2O]+", "[M+H-SO3-H2O-NH3]+",
"[M+H-NH3-C3H4]+", "[M+H-H2O-CO2]+", "[M+H-H2O-H2O-C2H4O]+",
"[M+H-NH3-CO-CO]+", "[M+H-NH3-CO-COCH2]+", "[M+H-C8H6O]+",
"[M+H-C8H6O-NH3]+", "[M+H-C8H6O-H2O]+", "[M+H-C2H2O2]+",
"[M+H-C2H4O2]+", "[M+H-C5H8O]+", "[M+H-NH3-CO2-CH2O]+",
"[M+H-NH3-CO2-NH3-H2O]+", "[M+H-NH3-CO2-C3H4O]+",
"[M+H-NH3-CO2-C5H8]+", "[M+H-HCOOH-HCOOH]+", "[M+H-C2H4-CO2]+",
"[M+H-C2H4-HCOOH]+", "[M+H-NH3-H2O-H2O]+", "[M+H-H2O-C2H2O2]+",
"[M+H-COCH2-C4H8]+", "[M+H-NH3-NH3-C3H4]+", "[M+H-C2H4O2-CH3OH]+",
"[M+H-C3H6O-CH3OH]+", "[M+H-NH3-CO-COCH2-C4H6O]+",
"[M+H-C4H6-H2O]+", "[M+H-C4H6-C2H4]+", "[M+H-C4H6-NH3-H2O]+",
"[M+H-C4H6-COCH2]+", "[M+H-C4H6-C4H6O]+", "[M+H-C3H4O-C4H6]+",
"[M+H-C3H4O-C4H8O2]+", "[M+H-C4H8-C4H6]+", "[M+H-NH3-HCOOH-CH3OH]+",
"[M+H-NH3-C2H6]+", "[M+H-NH3-C8H6O-CH2]+", "[M+H-NH3-C3H4-COCH2]+",
"[M+H-C3H9N]+", "[M+H-C3H9N-C2H4O2]+", "[M+H-C6H10O7]+",
"[M+H-C6H10O7+H2O]+", "[M+H-C6H10O7-(H2O)2]+", "[M+H-C6H12O6]+",
"[M+H-C6H12O6+H2O]+", "[M+H-C6H12O6-H2O]+", "[M+H-C5H10O5]+",
"[M+H- C5H10O5+H2O]+", "[M+H- C5H10O5-H2O]+", "[M+H-C2H8NO4P]+",
"[M+H-(H2O)3-CO]+", "[M+H-C6H13NO2]+", "[M+H-C5H11NO2]+",
"[M+H-CH3S]+", "[M+H-C8H8O2]+", "[M+H-C12H22O11]+",
"[M+H-C12H24O12]+", "[M+H-C12H20O10]+")
}
if (grepl("n", mode)) {
nls <- c("[M-H-NH3]-", "[M-H-H2O]-", "[M-H-COCH2]-",
"[M-H-CO2]-", "[M-H-NH3-CO2]-", "[M-H-NH3-HCOOH]-",
"[M-H-NH3-H2O]-", "[M-H-NH3-COCH2]-", "[M-H-S]-",
"[M-H-S-NH3-HCOOH]-", "[M-H-H4O2]-", "[M-H-CH2]-",
"[M-H-O]-", "[M-H-C2H2]-", "[M-H-C2H4]-", "[M-H-CO]-",
"[M-H-C3H6]-", "[M-H-C2H4O]-", "[M-H-C4H6]-", "[M-H-C3H4O]-",
"[M-H-C4H8]-", "[M-H-C5H8]-", "[M-H-C4H6O]-", "[M-H-C5H10]-",
"[M-H-C6H12]-", "[M-H-C4H8O2]-", "[M-H-H2O-HCOOH]-",
"[M-H-CH4]-", "[M-H-CH2O]-", "[M-H-C2H6]-", "[M-H-CH3OH]-",
"[M-H-C3H4]-", "[M-H-C3H6O]-", "[M-H-CO2-C3H6]-",
"[M-H-SO3]-", "[M-H-SO3-H2O]-", "[M-H-SO3-H2O-NH3]-",
"[M-H-NH3-C3H4]-", "[M-H-H2O-CO2]-", "[M-H-H2O-H2O-C2H4O]-",
"[M-H-NH3-CO-CO]-", "[M-H-NH3-CO-COCH2]-", "[M-H-C8H6O]-",
"[M-H-C8H6O-NH3]-", "[M-H-C8H6O-H2O]-", "[M-H-C2H2O2]-",
"[M-H-C2H4O2]-", "[M-H-C5H8O]-", "[M-H-NH3-CO2-CH2O]-",
"[M-H-NH3-CO2-NH3-H2O]-", "[M-H-NH3-CO2-C3H4O]-",
"[M-H-NH3-CO2-C5H8]-", "[M-H-HCOOH-HCOOH]-", "[M-H-C2H4-CO2]-",
"[M-H-C2H4-HCOOH]-", "[M-H-NH3-H2O-H2O]-", "[M-H-H2O-C2H2O2]-",
"[M-H-COCH2-C4H8]-", "[M-H-NH3-NH3-C3H4]-", "[M-H-C2H4O2-CH3OH]-",
"[M-H-C3H6O-CH3OH]-", "[M-H-NH3-CO-COCH2-C4H6O]-",
"[M-H-C4H6-H2O]-", "[M-H-C4H6-C2H4]-", "[M-H-C4H6-NH3-H2O]-",
"[M-H-C4H6-COCH2]-", "[M-H-C4H6-C4H6O]-", "[M-H-C3H4O-C4H6]-",
"[M-H-C3H4O-C4H8O2]-", "[M-H-C4H8-C4H6]-", "[M-H-NH3-HCOOH-CH3OH]-",
"[M-H-NH3-C2H6]-", "[M-H-NH3-C8H6O-CH2]-", "[M-H-NH3-C3H4-COCH2]-",
"[M-H-C3H9N]-", "[M-H-C3H9N-C2H4O2]-", "[M-H-C6H10O7]-",
"[M-H-C6H10O7+H2O]-", "[M-H-C6H10O7-(H2O)2]-", "[M-H-C6H12O6]-",
"[M-H-C6H12O6+H2O]-", "[M-H-C6H12O6-H2O]-", "[M-H-C5H10O5]-",
"[M-H- C5H10O5+H2O]-", "[M-H- C5H10O5-H2O]-", "[M-H-C2H8NO4P]-",
"[M-H-(H2O)3-CO]-", "[M-H-C6H13NO2]-", "[M-H-C5H11NO2]-",
"[M-H-CH3S]-", "[M-H-C8H8O2]-", "[M-H-C12H22O11]-",
"[M-H-C12H24O12]-", "[M-H-C12H20O10]-")
}
if(is.null(nls)) {
stop("please define neutral losses using 'nls' or set mode to either'positive' or 'negative'")
}
}
if (length(adwts) > 0) {
if (length(adwts) != length(ads)) {
if (length(adwts) > 1) {
warning("adduct weight length not equal to adduct length: assigning weight ",
adwts[1], " to all adduct weights")
}
adwts <- rep(adwts[1], length(ads))
}
} else {
adwts = rep(1, length(ads))
}
if (length(nlwts) > 0) {
if (length(nlwts) != length(nls)) {
if (length(nlwts) > 1) {
warning("adduct weight length not equal to adduct length: assigning weight ",
nlwts[1], " to all adduct weights")
}
nlwts <- rep(nlwts[1], length(nls))
}
} else {
nlwts = rep(0.1, length(nls))
}
adnlwts <- c(adwts, nlwts)
names(adnlwts) <- c(ads, nls)
M.findmain <- rep(NA, max(ramclustObj$featclus))
M.ppm.findmain <- rep(NA, max(ramclustObj$featclus))
M.ann.findmain <- as.list(rep(NA, max(ramclustObj$featclus)))
M.ramclustr <- rep(NA, max(ramclustObj$featclus))
M.ppm.ramclustr <- rep(NA, max(ramclustObj$featclus))
M.rank.ramclustr <- rep(NA, max(ramclustObj$featclus))
M.ann.ramclustr <- as.list(rep(NA, max(ramclustObj$featclus)))
if (is.null(cmpd)) {
cmpd <- (1:max(ramclustObj$featclus))
}
for (cl in cmpd) {
s <- data.frame(mz = ramclustObj$fmz[which(ramclustObj$featclus ==
cl)], int = ramclustObj$msint[which(ramclustObj$featclus ==
cl)])
out <- findMAIN(s, adductmz = NULL, ionmode = mode, adducthyp = ads,
ms2spec = NULL, rules = c(ads, nls), mzabs = mzabs.error,
ppm = ppm.error, mainpkthr = 0.1, collapseResults = FALSE)
summarytable <- summary(out)
M.findmain[cl] <- summarytable[1, "neutral_mass"]
M.ppm.findmain[cl] <- summarytable[1, "medppm"]
M.ann.findmain[[cl]] <- out[[1]]
for (y in 1:length(out)) {
keep <- which(!is.na(out[[y]][, "adduct"]))
out[[y]][keep[which(is.na(out[[y]][keep, "ppm"]))],
"ppm"] <- ppm.error/2
}
summaryscores <- sapply(1:length(out), FUN = function(x) {
keep <- which(!is.na(out[[x]][, "adduct"]))
wt <- adnlwts[out[[x]][keep, "adduct"]]
int <- (out[[x]][keep, "int"])^0.1
mzerr <- out[[x]][keep, "ppm"]
mzerr <- round(exp(-mzerr^2/(2 * (ppm.error^2))),
digits = 4)
massorder <- sqrt(order(out[[x]][keep, "mz"]))
massorder <- (massorder)/max((massorder))
return(sum((massorder * int * mzerr * wt), na.rm = TRUE) +
(0.1 * length(keep)))
})
best <- which.max(summaryscores)
M.ramclustr[cl] <- summarytable[best, "neutral_mass"]
M.ppm.ramclustr[cl] <- summarytable[best, "medppm"]
M.rank.ramclustr[cl] <- best
M.ann.ramclustr[[cl]] <- out[[best]]
if (10 * round(cl/10, digits = 0) == cl) {
cat(cl, "of", max(ramclustObj$featclus), "\n")
}
}
ramclustObj$M.ramclustr <- M.ramclustr
ramclustObj$M.ppm.ramclustr <- M.ppm.ramclustr
ramclustObj$M.rank.ramclustr <- M.rank.ramclustr
ramclustObj$M.ann.ramclustr <- M.ann.ramclustr
ramclustObj$M.findmain <- M.findmain
ramclustObj$M.ppm.findmain <- M.ppm.findmain
ramclustObj$M.ann.findmain <- M.ann.findmain
ramclustObj$use.findmain <- rep(TRUE, length(M.ppm.findmain))
resolve <- which(abs(ramclustObj$M.ramclustr - ramclustObj$M.findmain) >
(2 * mzabs.error))
for (i in resolve) {
if (ramclustObj$M.ramclustr[i] > ramclustObj$M.findmain[i]) {
ramclustObj$use.findmain[i] <- FALSE
}
}
ramclustObj$M <- ramclustObj$M.findmain
ramclustObj$M[!ramclustObj$use.findmain] <- ramclustObj$M.ramclustr[!ramclustObj$use.findmain]
ramclustObj$M.ann <- ramclustObj$M.ann.findmain
resolved <- which(!ramclustObj$use.findmain)
for (i in resolved) {
ramclustObj$M.ann[[i]] <- ramclustObj$M.ann.ramclustr[[i]]
}
if (plot.findmain) {
cat("plotting findmain annotation results", "\n")
pdf("spectra/findmainPlots.pdf", width = 10, height = 4.6)
par(mfrow = c(1, 2))
for (cl in cmpd) {
PlotSpec(x = ramclustObj$M.ann.ramclustr[[cl]], txt = ramclustObj$M.ann.ramclustr[[cl]][,
c("mz", "adduct")])
title(main = list(paste(cl, ":", "M.ramclustr =",
round(ramclustObj$M.ramclustr[cl], digits = 4),
"( +/-", round(ramclustObj$M.ppm.ramclustr[cl],
digits = 1), "ppm )"), font = if (ramclustObj$use.findmain[cl]) {
1
} else {
2
}, col = if (ramclustObj$use.findmain[cl]) {
1
} else {
2
}))
PlotSpec(x = ramclustObj$M.ann.findmain[[cl]], txt = ramclustObj$M.ann.findmain[[cl]][,
c("mz", "adduct")])
title(main = list(paste(cl, ":", "M.findmain =",
round(ramclustObj$M.findmain[cl], digits = 4),
"( +/-", round(ramclustObj$M.ppm.findmain[cl],
digits = 1), "ppm )"), font = if (ramclustObj$use.findmain[cl]) {
2
} else {
1
}, col = if (ramclustObj$use.findmain[cl]) {
2
} else {
1
}))
}
dev.off()
}
if (writeMat) {
if (!dir.exists("spectra")) {
dir.create("spectra")
}
# list.dirs()
dir.create("spectra/mat")
for (cl in cmpd) {
ms <- ramclustObj$M.ann[[cl]]
prcr <- which(ms[, "adduct"] %in% ads)
prcr <- prcr[which.max(ms[prcr, "int"])]
prcmz <- ms[prcr, "mz"]
prctype <- ms[prcr, "adduct"]
out <- paste("NAME: ", ramclustObj$cmpd[cl], "\n",
"RETENTIONTIME: ", round(ramclustObj$clrt[cl],
digits = 2), "\n", "PRECURSORMZ: ", prcmz,
"\n", "PRECURSORTYPE: ", prctype, "\n", "IONTYPE: ",
mode, "\n", "SPECTRUMTYPE: Centroid", "\n", if ((!is.null(ramclustObj$msmsint))) {
paste("COLLISIONENERGY: ", as.character(ramclustObj$ExpDes[[2]][which(row.names(ramclustObj$ExpDes[[2]]) ==
"CE2"), 1]), "\n", sep = "")
}, "MSTYPE: ", "MS1", "\n", "Num Peaks: ", nrow(ms),
"\n", sep = "")
for (i in 1:nrow(ms)) {
out <- paste(out, ms[i, 1], " ", ms[i, 2], "\n",
sep = "")
}
if (!is.null(ramclustObj$msmsint)) {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msmsint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out <- paste(out, "MSTYPE:", "MS2", "\n", "Num Peaks: ",
nrow(msms), "\n", sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
} else {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out <- paste(out, "MSTYPE:", "MS2", "\n", "Num Peaks: ",
nrow(msms), "\n", sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
}
write(out, file = paste0("spectra/mat/", ramclustObj$cmpd[cl],
".mat"))
}
}
if (writeMS) {
if (!dir.exists("spectra")) {
dir.create("spectra")
}
# list.dirs()
dir.create("spectra/ms")
for (cl in cmpd) {
ms <- ramclustObj$M.ann[[cl]]
m1ads<-ads[grep("[M", ads, fixed = TRUE)]
if(length(m1ads) == 0) {
next
} else {
prcr <- which(ms[, "adduct"] %in% m1ads)
}
prcr <- prcr[which.max(ms[prcr, "int"])]
prcmz <- ms[prcr, "mz"]
prctype <- ms[prcr, "adduct"]
out <- paste(">compound ", ramclustObj$cmpd[cl], "\n",
">parentmass ", prcmz,
"\n", ">ionization ", prctype, "\n", '\n', sep = "")
ms<-ms[which((abs(ms[,"mz"] - prcmz) < 5.5) | (abs(prcmz - ms[,"mz"]) < 0.2)), ]
out<-paste(out, ">ms1peaks",
'\n', sep = "")
for (i in 1:nrow(ms)) {
out <- paste(out, ms[i, 1], " ", ms[i, 2], "\n",
sep = "")
}
# ms<-ms[which((abs(ms[,"mz"] - prcmz) < 5.5) | (abs(prcmz - ms[,"mz"]) < 0.2)), ]
# out<-paste(out, '\n', ">collision ",
# ramclustObj$ExpDes$instrument[which(dimnames(ramclustObj$ExpDes$instrument)[[1]]=="CE2"),1],
# '\n', sep = "")
# for (i in 1:nrow(ms)) {
# out <- paste(out, ms[i, 1], " ", ms[i, 2], "\n",
# sep = "")
# }
if (!is.null(ramclustObj$msmsint)) {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msmsint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out<-paste(out, '\n', ">collision ",
ramclustObj$ExpDes$instrument[which(dimnames(ramclustObj$ExpDes$instrument)[[1]]=="CE2"),1],
'\n', sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
} else {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out<-paste(out, '\n', ">collision ",
ramclustObj$ExpDes$instrument[which(dimnames(ramclustObj$ExpDes$instrument)[[1]]=="CE1"),1],
'\n', sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
}
write(out, file = paste0("spectra/ms/", ramclustObj$cmpd[cl],
".ms"))
}
}
cat("finished", "\n")
return(ramclustObj)
}
sneumann/RAMClustR documentation built on May 30, 2019, 5:05 a.m.
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#' do.findmain
#'
#' Cluster annotation function: inference of 'M' - molecular weight of the compound giving rise to each spectrum - using the InterpretMSSpectrum::findMain function
#'
#' @param ramclustObj ramclustR object to annotate.
#' @param cmpd integer: vector defining compound numbers to annotated. if NULL (default), all compounds
#' @param mode character: "positive" or "negative"
#' @param mzabs.error numeric: absolute mass deviation allowd
#' @param ppm.error numeric: ppm mass error added to mzabs.error
#' @param ads character: vector of allowed adducts, i.e. c("[M+H]+"). if NULL, default values of H+, Na+, K+, and NH4+, as monomer, dimer, and trimer, are assigned.
#' @param nls character: vector of allowed neutral losses, i.e. c("[M+H-H2O]+"). if NULL, an extensive list derived from CAMERA's will be used.
#' @param adwts numeric: vector of weights for adducts. length should match that of 'ads', else first value will be repeated. if NULL (default), value of 1 is assigned to all. Only used for ramclustR scoring of M.
#' @param nlwts numeric: vector of weights for neutral losses. length should match that of 'nls', else first value will be repeated. if NULL (default), value of 0.1 is assigned to all. Only used for ramclustR scoring of M.
#' @param plot.findmain logical: should pdf polts be generated for evaluation?
#' @param writeMat logical: should indidual .mat files (for MSFinder) be generated in a 'mat' subdirectory in the 'spectra' folder? default = TRUE.
#' @details a partially annotated ramclustR object. base structure is that of a standard R heirarchical clustering output, with additional slots described in ramclustR documentation (?ramclustR). New slots added after using the interpretMSSpectrum functionality include those described below. .mat files written in new directory 'spectra/mat' in working directory
#' @return $M: The inferred molecular weight of the compound giving rise to the each spectrum
#' @return $M.ppm: The ppm error of all the MS signals annotated, high error values should be considered 'red flags'
#' @return $M.ann: The annotated spectrum supporting the intepretation of M
#' @return $use.findmain: Logical vector indicating whether findmain scoring (TRUE) or ramclustR scoring (FALSE) was used to support inference of M. By default, findmain scoring is used. When ramclustR scoring differs from findmain scoring, the scoring metric which predicts higher M is selected.
#' @return $M.ramclustr: M selected using ramclustR scoring
#' @return $M.ppm.ramclustr: ppm error of M selected using ramclustR scoring
#' @return $M.ann.ramclustr: annotated spectrum supporing M using ramclustR scoring
#' @return $M.findmain: M selected using findmain scoring
#' @return $M.ppm.findmain: ppm error of M selected using findmain scoring
#' @return $M.ann.findmain: annotated spectrum supporing M using findmain scoring
#' @references Jaeger C, Méret M, Schmitt CA, Lisec J. Compound annotation in liquid chromatography/high-resolution mass spectrometry based metabolomics: robust adduct ion determination as a prerequisite to structure prediction in electrospray ionization mass spectra. Rapid Commun Mass Spectrom. 2017 Aug 15;31(15):1261-1266. doi: 10.1002/rcm.7905. PubMed PMID: 28499062.
#' @references Broeckling CD, Afsar FA, Neumann S, Ben-Hur A, Prenni JE. RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data. Anal Chem. 2014 Jul 15;86(14):6812-7. doi: 10.1021/ac501530d. Epub 2014 Jun 26. PubMed PMID: 24927477.
#' @references Broeckling CD, Ganna A, Layer M, Brown K, Sutton B, Ingelsson E, Peers G, Prenni JE. Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction. Anal Chem. 2016 Sep 20;88(18):9226-34. doi: 10.1021/acs.analchem.6b02479. Epub 2016 Sep 8. PubMed PMID: 7560453.
#' @keywords 'ramclustR' 'RAMClustR', 'ramclustR', 'metabolomics', 'mass spectrometry', 'clustering', 'feature', 'xcms'
#' @author Corey Broeckling
#' @export
do.findmain <- function (ramclustObj = RC, cmpd = NULL, mode = "positive", mzabs.error = 0.01,
ppm.error = 10, ads = NULL, nls = NULL, adwts = NULL, nlwts = NULL,
plot.findmain = TRUE, writeMat = TRUE, writeMS = TRUE)
{
if (is.null(ads)) {
if (grepl("p", mode)) {
ads <- c("[M+H]+", "[M+Na]+", "[M+K]+", "[M+NH4]+", "[2M+H]+",
"[2M+Na]+", "[2M+K]+", "[2M+NH4]+", "[3M+H]+", "[3M+Na]+",
"[3M+K]+", "[3M+NH4]+")
}
if(grepl("n", mode)) {
ads <- c("[M-H]-", "[M+Na-2H]-", "[M+K-2H]-", "[M+CH2O2- H]-",
"[2M-H]-", "[2M+Na-2H]-", "[2M+K-2H]-", "[2M+CH2O2- H]-",
"[3M-H]-", "[3M+Na-2H]-", "[3M+K-2H]-", "[3M+CH2O2- H]-")
}
if(is.null(ads)) {
stop("please define adducts using 'ads' or set mode to either'positive' or 'negative'")
}
}
if (is.null(nls)) {
if (grepl("p", mode)) {
nls <- c("[M+H-NH3]+", "[M+H-H2O]+", "[M+H-COCH2]+",
"[M+H-CO2]+", "[M+H-NH3-CO2]+", "[M+H-NH3-HCOOH]+",
"[M+H-NH3-H2O]+", "[M+H-NH3-COCH2]+", "[M+H-S]+",
"[M+H-S-NH3-HCOOH]+", "[M+H-H4O2]+", "[M+H-CH2]+",
"[M+H-O]+", "[M+H-C2H2]+", "[M+H-C2H4]+", "[M+H-CO]+",
"[M+H-C3H6]+", "[M+H-C2H4O]+", "[M+H-C4H6]+", "[M+H-C3H4O]+",
"[M+H-C4H8]+", "[M+H-C5H8]+", "[M+H-C4H6O]+", "[M+H-C5H10]+",
"[M+H-C6H12]+", "[M+H-C4H8O2]+", "[M+H-H2O-HCOOH]+",
"[M+H-CH4]+", "[M+H-CH2O]+", "[M+H-C2H6]+", "[M+H-CH3OH]+",
"[M+H-C3H4]+", "[M+H-C3H6O]+", "[M+H-CO2-C3H6]+",
"[M+H-SO3]+", "[M+H-SO3-H2O]+", "[M+H-SO3-H2O-NH3]+",
"[M+H-NH3-C3H4]+", "[M+H-H2O-CO2]+", "[M+H-H2O-H2O-C2H4O]+",
"[M+H-NH3-CO-CO]+", "[M+H-NH3-CO-COCH2]+", "[M+H-C8H6O]+",
"[M+H-C8H6O-NH3]+", "[M+H-C8H6O-H2O]+", "[M+H-C2H2O2]+",
"[M+H-C2H4O2]+", "[M+H-C5H8O]+", "[M+H-NH3-CO2-CH2O]+",
"[M+H-NH3-CO2-NH3-H2O]+", "[M+H-NH3-CO2-C3H4O]+",
"[M+H-NH3-CO2-C5H8]+", "[M+H-HCOOH-HCOOH]+", "[M+H-C2H4-CO2]+",
"[M+H-C2H4-HCOOH]+", "[M+H-NH3-H2O-H2O]+", "[M+H-H2O-C2H2O2]+",
"[M+H-COCH2-C4H8]+", "[M+H-NH3-NH3-C3H4]+", "[M+H-C2H4O2-CH3OH]+",
"[M+H-C3H6O-CH3OH]+", "[M+H-NH3-CO-COCH2-C4H6O]+",
"[M+H-C4H6-H2O]+", "[M+H-C4H6-C2H4]+", "[M+H-C4H6-NH3-H2O]+",
"[M+H-C4H6-COCH2]+", "[M+H-C4H6-C4H6O]+", "[M+H-C3H4O-C4H6]+",
"[M+H-C3H4O-C4H8O2]+", "[M+H-C4H8-C4H6]+", "[M+H-NH3-HCOOH-CH3OH]+",
"[M+H-NH3-C2H6]+", "[M+H-NH3-C8H6O-CH2]+", "[M+H-NH3-C3H4-COCH2]+",
"[M+H-C3H9N]+", "[M+H-C3H9N-C2H4O2]+", "[M+H-C6H10O7]+",
"[M+H-C6H10O7+H2O]+", "[M+H-C6H10O7-(H2O)2]+", "[M+H-C6H12O6]+",
"[M+H-C6H12O6+H2O]+", "[M+H-C6H12O6-H2O]+", "[M+H-C5H10O5]+",
"[M+H- C5H10O5+H2O]+", "[M+H- C5H10O5-H2O]+", "[M+H-C2H8NO4P]+",
"[M+H-(H2O)3-CO]+", "[M+H-C6H13NO2]+", "[M+H-C5H11NO2]+",
"[M+H-CH3S]+", "[M+H-C8H8O2]+", "[M+H-C12H22O11]+",
"[M+H-C12H24O12]+", "[M+H-C12H20O10]+")
}
if (grepl("n", mode)) {
nls <- c("[M-H-NH3]-", "[M-H-H2O]-", "[M-H-COCH2]-",
"[M-H-CO2]-", "[M-H-NH3-CO2]-", "[M-H-NH3-HCOOH]-",
"[M-H-NH3-H2O]-", "[M-H-NH3-COCH2]-", "[M-H-S]-",
"[M-H-S-NH3-HCOOH]-", "[M-H-H4O2]-", "[M-H-CH2]-",
"[M-H-O]-", "[M-H-C2H2]-", "[M-H-C2H4]-", "[M-H-CO]-",
"[M-H-C3H6]-", "[M-H-C2H4O]-", "[M-H-C4H6]-", "[M-H-C3H4O]-",
"[M-H-C4H8]-", "[M-H-C5H8]-", "[M-H-C4H6O]-", "[M-H-C5H10]-",
"[M-H-C6H12]-", "[M-H-C4H8O2]-", "[M-H-H2O-HCOOH]-",
"[M-H-CH4]-", "[M-H-CH2O]-", "[M-H-C2H6]-", "[M-H-CH3OH]-",
"[M-H-C3H4]-", "[M-H-C3H6O]-", "[M-H-CO2-C3H6]-",
"[M-H-SO3]-", "[M-H-SO3-H2O]-", "[M-H-SO3-H2O-NH3]-",
"[M-H-NH3-C3H4]-", "[M-H-H2O-CO2]-", "[M-H-H2O-H2O-C2H4O]-",
"[M-H-NH3-CO-CO]-", "[M-H-NH3-CO-COCH2]-", "[M-H-C8H6O]-",
"[M-H-C8H6O-NH3]-", "[M-H-C8H6O-H2O]-", "[M-H-C2H2O2]-",
"[M-H-C2H4O2]-", "[M-H-C5H8O]-", "[M-H-NH3-CO2-CH2O]-",
"[M-H-NH3-CO2-NH3-H2O]-", "[M-H-NH3-CO2-C3H4O]-",
"[M-H-NH3-CO2-C5H8]-", "[M-H-HCOOH-HCOOH]-", "[M-H-C2H4-CO2]-",
"[M-H-C2H4-HCOOH]-", "[M-H-NH3-H2O-H2O]-", "[M-H-H2O-C2H2O2]-",
"[M-H-COCH2-C4H8]-", "[M-H-NH3-NH3-C3H4]-", "[M-H-C2H4O2-CH3OH]-",
"[M-H-C3H6O-CH3OH]-", "[M-H-NH3-CO-COCH2-C4H6O]-",
"[M-H-C4H6-H2O]-", "[M-H-C4H6-C2H4]-", "[M-H-C4H6-NH3-H2O]-",
"[M-H-C4H6-COCH2]-", "[M-H-C4H6-C4H6O]-", "[M-H-C3H4O-C4H6]-",
"[M-H-C3H4O-C4H8O2]-", "[M-H-C4H8-C4H6]-", "[M-H-NH3-HCOOH-CH3OH]-",
"[M-H-NH3-C2H6]-", "[M-H-NH3-C8H6O-CH2]-", "[M-H-NH3-C3H4-COCH2]-",
"[M-H-C3H9N]-", "[M-H-C3H9N-C2H4O2]-", "[M-H-C6H10O7]-",
"[M-H-C6H10O7+H2O]-", "[M-H-C6H10O7-(H2O)2]-", "[M-H-C6H12O6]-",
"[M-H-C6H12O6+H2O]-", "[M-H-C6H12O6-H2O]-", "[M-H-C5H10O5]-",
"[M-H- C5H10O5+H2O]-", "[M-H- C5H10O5-H2O]-", "[M-H-C2H8NO4P]-",
"[M-H-(H2O)3-CO]-", "[M-H-C6H13NO2]-", "[M-H-C5H11NO2]-",
"[M-H-CH3S]-", "[M-H-C8H8O2]-", "[M-H-C12H22O11]-",
"[M-H-C12H24O12]-", "[M-H-C12H20O10]-")
}
if(is.null(nls)) {
stop("please define neutral losses using 'nls' or set mode to either'positive' or 'negative'")
}
}
if (length(adwts) > 0) {
if (length(adwts) != length(ads)) {
if (length(adwts) > 1) {
warning("adduct weight length not equal to adduct length: assigning weight ",
adwts[1], " to all adduct weights")
}
adwts <- rep(adwts[1], length(ads))
}
} else {
adwts = rep(1, length(ads))
}
if (length(nlwts) > 0) {
if (length(nlwts) != length(nls)) {
if (length(nlwts) > 1) {
warning("adduct weight length not equal to adduct length: assigning weight ",
nlwts[1], " to all adduct weights")
}
nlwts <- rep(nlwts[1], length(nls))
}
} else {
nlwts = rep(0.1, length(nls))
}
adnlwts <- c(adwts, nlwts)
names(adnlwts) <- c(ads, nls)
M.findmain <- rep(NA, max(ramclustObj$featclus))
M.ppm.findmain <- rep(NA, max(ramclustObj$featclus))
M.ann.findmain <- as.list(rep(NA, max(ramclustObj$featclus)))
M.ramclustr <- rep(NA, max(ramclustObj$featclus))
M.ppm.ramclustr <- rep(NA, max(ramclustObj$featclus))
M.rank.ramclustr <- rep(NA, max(ramclustObj$featclus))
M.ann.ramclustr <- as.list(rep(NA, max(ramclustObj$featclus)))
if (is.null(cmpd)) {
cmpd <- (1:max(ramclustObj$featclus))
}
for (cl in cmpd) {
s <- data.frame(mz = ramclustObj$fmz[which(ramclustObj$featclus ==
cl)], int = ramclustObj$msint[which(ramclustObj$featclus ==
cl)])
out <- findMAIN(s, adductmz = NULL, ionmode = mode, adducthyp = ads,
ms2spec = NULL, rules = c(ads, nls), mzabs = mzabs.error,
ppm = ppm.error, mainpkthr = 0.1, collapseResults = FALSE)
summarytable <- summary(out)
M.findmain[cl] <- summarytable[1, "neutral_mass"]
M.ppm.findmain[cl] <- summarytable[1, "medppm"]
M.ann.findmain[[cl]] <- out[[1]]
for (y in 1:length(out)) {
keep <- which(!is.na(out[[y]][, "adduct"]))
out[[y]][keep[which(is.na(out[[y]][keep, "ppm"]))],
"ppm"] <- ppm.error/2
}
summaryscores <- sapply(1:length(out), FUN = function(x) {
keep <- which(!is.na(out[[x]][, "adduct"]))
wt <- adnlwts[out[[x]][keep, "adduct"]]
int <- (out[[x]][keep, "int"])^0.1
mzerr <- out[[x]][keep, "ppm"]
mzerr <- round(exp(-mzerr^2/(2 * (ppm.error^2))),
digits = 4)
massorder <- sqrt(order(out[[x]][keep, "mz"]))
massorder <- (massorder)/max((massorder))
return(sum((massorder * int * mzerr * wt), na.rm = TRUE) +
(0.1 * length(keep)))
})
best <- which.max(summaryscores)
M.ramclustr[cl] <- summarytable[best, "neutral_mass"]
M.ppm.ramclustr[cl] <- summarytable[best, "medppm"]
M.rank.ramclustr[cl] <- best
M.ann.ramclustr[[cl]] <- out[[best]]
if (10 * round(cl/10, digits = 0) == cl) {
cat(cl, "of", max(ramclustObj$featclus), "\n")
}
}
ramclustObj$M.ramclustr <- M.ramclustr
ramclustObj$M.ppm.ramclustr <- M.ppm.ramclustr
ramclustObj$M.rank.ramclustr <- M.rank.ramclustr
ramclustObj$M.ann.ramclustr <- M.ann.ramclustr
ramclustObj$M.findmain <- M.findmain
ramclustObj$M.ppm.findmain <- M.ppm.findmain
ramclustObj$M.ann.findmain <- M.ann.findmain
ramclustObj$use.findmain <- rep(TRUE, length(M.ppm.findmain))
resolve <- which(abs(ramclustObj$M.ramclustr - ramclustObj$M.findmain) >
(2 * mzabs.error))
for (i in resolve) {
if (ramclustObj$M.ramclustr[i] > ramclustObj$M.findmain[i]) {
ramclustObj$use.findmain[i] <- FALSE
}
}
ramclustObj$M <- ramclustObj$M.findmain
ramclustObj$M[!ramclustObj$use.findmain] <- ramclustObj$M.ramclustr[!ramclustObj$use.findmain]
ramclustObj$M.ann <- ramclustObj$M.ann.findmain
resolved <- which(!ramclustObj$use.findmain)
for (i in resolved) {
ramclustObj$M.ann[[i]] <- ramclustObj$M.ann.ramclustr[[i]]
}
if (plot.findmain) {
cat("plotting findmain annotation results", "\n")
pdf("spectra/findmainPlots.pdf", width = 10, height = 4.6)
par(mfrow = c(1, 2))
for (cl in cmpd) {
PlotSpec(x = ramclustObj$M.ann.ramclustr[[cl]], txt = ramclustObj$M.ann.ramclustr[[cl]][,
c("mz", "adduct")])
title(main = list(paste(cl, ":", "M.ramclustr =",
round(ramclustObj$M.ramclustr[cl], digits = 4),
"( +/-", round(ramclustObj$M.ppm.ramclustr[cl],
digits = 1), "ppm )"), font = if (ramclustObj$use.findmain[cl]) {
1
} else {
2
}, col = if (ramclustObj$use.findmain[cl]) {
1
} else {
2
}))
PlotSpec(x = ramclustObj$M.ann.findmain[[cl]], txt = ramclustObj$M.ann.findmain[[cl]][,
c("mz", "adduct")])
title(main = list(paste(cl, ":", "M.findmain =",
round(ramclustObj$M.findmain[cl], digits = 4),
"( +/-", round(ramclustObj$M.ppm.findmain[cl],
digits = 1), "ppm )"), font = if (ramclustObj$use.findmain[cl]) {
2
} else {
1
}, col = if (ramclustObj$use.findmain[cl]) {
2
} else {
1
}))
}
dev.off()
}
if (writeMat) {
if (!dir.exists("spectra")) {
dir.create("spectra")
}
# list.dirs()
dir.create("spectra/mat")
for (cl in cmpd) {
ms <- ramclustObj$M.ann[[cl]]
prcr <- which(ms[, "adduct"] %in% ads)
prcr <- prcr[which.max(ms[prcr, "int"])]
prcmz <- ms[prcr, "mz"]
prctype <- ms[prcr, "adduct"]
out <- paste("NAME: ", ramclustObj$cmpd[cl], "\n",
"RETENTIONTIME: ", round(ramclustObj$clrt[cl],
digits = 2), "\n", "PRECURSORMZ: ", prcmz,
"\n", "PRECURSORTYPE: ", prctype, "\n", "IONTYPE: ",
mode, "\n", "SPECTRUMTYPE: Centroid", "\n", if ((!is.null(ramclustObj$msmsint))) {
paste("COLLISIONENERGY: ", as.character(ramclustObj$ExpDes[[2]][which(row.names(ramclustObj$ExpDes[[2]]) ==
"CE2"), 1]), "\n", sep = "")
}, "MSTYPE: ", "MS1", "\n", "Num Peaks: ", nrow(ms),
"\n", sep = "")
for (i in 1:nrow(ms)) {
out <- paste(out, ms[i, 1], " ", ms[i, 2], "\n",
sep = "")
}
if (!is.null(ramclustObj$msmsint)) {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msmsint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out <- paste(out, "MSTYPE:", "MS2", "\n", "Num Peaks: ",
nrow(msms), "\n", sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
} else {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out <- paste(out, "MSTYPE:", "MS2", "\n", "Num Peaks: ",
nrow(msms), "\n", sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
}
write(out, file = paste0("spectra/mat/", ramclustObj$cmpd[cl],
".mat"))
}
}
if (writeMS) {
if (!dir.exists("spectra")) {
dir.create("spectra")
}
# list.dirs()
dir.create("spectra/ms")
for (cl in cmpd) {
ms <- ramclustObj$M.ann[[cl]]
m1ads<-ads[grep("[M", ads, fixed = TRUE)]
if(length(m1ads) == 0) {
next
} else {
prcr <- which(ms[, "adduct"] %in% m1ads)
}
prcr <- prcr[which.max(ms[prcr, "int"])]
prcmz <- ms[prcr, "mz"]
prctype <- ms[prcr, "adduct"]
out <- paste(">compound ", ramclustObj$cmpd[cl], "\n",
">parentmass ", prcmz,
"\n", ">ionization ", prctype, "\n", '\n', sep = "")
ms<-ms[which((abs(ms[,"mz"] - prcmz) < 5.5) | (abs(prcmz - ms[,"mz"]) < 0.2)), ]
out<-paste(out, ">ms1peaks",
'\n', sep = "")
for (i in 1:nrow(ms)) {
out <- paste(out, ms[i, 1], " ", ms[i, 2], "\n",
sep = "")
}
# ms<-ms[which((abs(ms[,"mz"] - prcmz) < 5.5) | (abs(prcmz - ms[,"mz"]) < 0.2)), ]
# out<-paste(out, '\n', ">collision ",
# ramclustObj$ExpDes$instrument[which(dimnames(ramclustObj$ExpDes$instrument)[[1]]=="CE2"),1],
# '\n', sep = "")
# for (i in 1:nrow(ms)) {
# out <- paste(out, ms[i, 1], " ", ms[i, 2], "\n",
# sep = "")
# }
if (!is.null(ramclustObj$msmsint)) {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msmsint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out<-paste(out, '\n', ">collision ",
ramclustObj$ExpDes$instrument[which(dimnames(ramclustObj$ExpDes$instrument)[[1]]=="CE2"),1],
'\n', sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
} else {
do <- which(ramclustObj$featclus == cl)
if(length(do)>0) {
msms <- cbind(mz = ramclustObj$fmz[do], int = ramclustObj$msint[do])
msms <- msms[which(msms[, "mz"] <= (prcmz + 3)), , drop = FALSE]
msms <- msms[order(msms[, "int"], decreasing = TRUE), , drop = FALSE]
if (nrow(msms) > 0) {
out<-paste(out, '\n', ">collision ",
ramclustObj$ExpDes$instrument[which(dimnames(ramclustObj$ExpDes$instrument)[[1]]=="CE1"),1],
'\n', sep = "")
for (i in 1:nrow(msms)) {
out <- paste(out, msms[i, 1], " ", msms[i,
2], "\n", sep = "")
}
}
}
}
write(out, file = paste0("spectra/ms/", ramclustObj$cmpd[cl],
".ms"))
}
}
cat("finished", "\n")
return(ramclustObj)
}
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