clean version for Bioc 2.13

DESCRIPTION

 Package: RMassBank
 Type: Package
 Title: Workflow to process tandem MS files and build MassBank records
-Version: 1.3.1
+Version: 1.3.2
 Authors@R: c(
     person(given = "RMassBank at Eawag", email = "massbank@eawag.ch",
     role=c("cre")),
@@ -13,6 +13,9 @@ Authors@R: c(
     "aut", email = "erik.mueller@student.uni-halle.de"), person(given =
     "Tobias", family = "Schulze", role = "ctb", email =
     "tobias.schulze@ufz.de") )
+Author: Michael Stravs, Emma Schymanski, Steffen Neumann, Erik Mueller, with
+    contributions from Tobias Schulze
+Maintainer: RMassBank at Eawag <massbank@eawag.ch>
 Description: Workflow to process tandem MS files and build MassBank records.
     Functions include automated extraction of tandem MS spectra, formula
     assignment to tandem MS fragments, recalibration of tandem MS spectra with
@@ -22,11 +25,11 @@ License: Artistic-2.0
 SystemRequirements: OpenBabel
 biocViews: Bioinformatics, MassSpectrometry, Metabolomics, Software
 Depends:
-    rcdk,yaml,mzR,methods
+    mzR,rcdk,yaml,methods
 Imports:
     XML,RCurl,rjson
 Suggests:
-    gplots,RMassBankData (>= 0.99.3),
+    gplots,RMassBankData,
     xcms (>= 1.37.1),
     CAMERA,
     ontoCAT,

NAMESPACE

+export(CTS.externalIdSubset)
+export(CTS.externalIdTypes)
+export(RmbDefaultSettings)
+export(RmbSettingsTemplate)
 export(add.formula)
 export(addMB)
 export(addPeaks)
@@ -12,8 +16,6 @@ export(cleanElnoise)
 export(combineMultiplicities)
 export(compileRecord)
 export(createMolfile)
-export(CTS.externalIdSubset)
-export(CTS.externalIdTypes)
 export(dbe)
 export(deprofile)
 export(deprofile.fwhm)
@@ -31,7 +33,6 @@ export(findMass)
 export(findMsMsHR)
 export(findMsMsHR.direct)
 export(findMsMsHR.mass)
-export(findMsMsHRperxcms.direct)
 export(findMz)
 export(findMz.formula)
 export(findName)
@@ -83,19 +84,19 @@ export(recalibrateSingleSpec)
 export(recalibrateSpectra)
 export(resetInfolists)
 export(resetList)
-export(RmbDefaultSettings)
-export(RmbSettingsTemplate)
 export(smiles2mass)
 export(to.limits.rcdk)
 export(toMassbank)
-export(toRMB)
 export(validate)
 exportClasses(mbWorkspace)
 exportClasses(msmsWorkspace)
 exportMethods(show)
-import(mzR)
 import(RCurl)
-import(rjson)
 import(XML)
+import(methods)
+import(mzR)
+import(rcdk)
+import(rjson)
+import(yaml)
 importClassesFrom(mzR)
 importMethodsFrom(mzR)

R/RmbWorkspace.R

-
+#' @import methods
+NULL
 
 #' Workspace for \code{msmsWorkflow} data
 #' 

R/formulaCalculator.R

-
+#' @import rcdk
+NULL
 
 
 

R/leMsMs.r

@@ -40,7 +40,7 @@ archiveResults <- function(w, fileName, settings = getOption("RMassBank"))
 #' workflow.
 #' 
 #' @usage msmsWorkflow(w, mode="pH", steps=c(1:8), confirmMode = FALSE, newRecalibration = TRUE, 
-#' 		useRtLimit = TRUE, archivename=NA, readMethod = "mzR", findPeaksArgs = NA, plots = FALSE,
+#' 		useRtLimit = TRUE, archivename=NA, readMethod = "mzR",
 #' 		precursorscan.cf = FALSE,
 #' 		settings = getOption("RMassBank"), analyzeMethod = "formula",
 #' 		progressbar = "progressBarHook")
@@ -56,15 +56,11 @@ archiveResults <- function(w, fileName, settings = getOption("RMassBank"))
 #' 			to reuse the currently stored curve (\code{FALSE}, useful e.g. for adduct-processing runs.) 
 #' @param useRtLimit Whether to enforce the given retention time window.
 #' @param archivename The prefix under which to store the analyzed result files.
-#' @param readMethod Several methods are available to get peak lists from the files.
-#'        Currently supported are "mzR", "xcms", "MassBank" and "peaklist".
-#'        The first two read MS/MS raw data, and differ in the strategy 
-#'        used to extract peaks. MassBank will read existing records, 
-#'        so that e.g. a recalibration can be performed, and "peaklist" 
-#'        just requires a CSV with two columns and the column header "mz", "int".
-#' @param findPeaksArgs A list of arguments that will be handed to the xcms-method findPeaks via do.call
-#' @param plots A parameter that determines whether the spectra should be plotted or not (This parameter is only used for the xcms-method)
-#' @param precursorscan.cf Whether to fill precursor scans. To be used with files which for
+#' @param readMethod Several methods are available to get peak lists from the input files.
+#'        Currently supported are "mzR" and "peaklist".
+#'        "mzR" reads MS/MS raw data. An alternative raw data reader "xcms" is not yet released.
+#' 				"peaklist" reads a CSV with two columns and the column header "mz", "int".
+#' @param precursorscan.cf Whether to fill precursor scan entries (cf = carry forward). To be used with files which for
 #' 		some reasons do not contain precursor scan IDs in the mzML, e.g. AB Sciex converted
 #' 		files.
 #' @param settings Options to be used for processing. Defaults to the options loaded via
@@ -77,7 +73,7 @@ archiveResults <- function(w, fileName, settings = getOption("RMassBank"))
 #' @author Michael Stravs, Eawag <michael.stravs@@eawag.ch>
 #' @export
 msmsWorkflow <- function(w, mode="pH", steps=c(1:8), confirmMode = FALSE, newRecalibration = TRUE, 
-		useRtLimit = TRUE, archivename=NA, readMethod = "mzR", findPeaksArgs = NA, plots = FALSE,
+		useRtLimit = TRUE, archivename=NA, readMethod = "mzR",
 		precursorscan.cf = FALSE,
 		settings = getOption("RMassBank"), analyzeMethod = "formula",
 		progressbar = "progressBarHook")
@@ -124,28 +120,28 @@ msmsWorkflow <- function(w, mode="pH", steps=c(1:8), confirmMode = FALSE, newRec
 		do.call(progressbar, list(object=pb, close=TRUE))
 	}
 	
-	if(readMethod == "xcms"){
-		splitfn <- strsplit(w@files,'_')
-		cpdIDs <- sapply(splitfn, function(splitted){as.numeric(return(splitted[length(splitted)-1]))})
-		files <- list()
-		wfiles <- vector()
-			for(i in 1:length(unique(cpdIDs))) {
-			indices <- sapply(splitfn,function(a){return(unique(cpdIDs)[i] %in% a)})
-			files[[i]] <- w@files[indices]
-		}
-		
-		w@files <- sapply(files,function(files){return(files[1])})
-		
-		for(i in 1:length(unique(cpdIDs))){
-			specs <- list()
-			for(j in 1:length(files[[i]])){
-				specs[[j]] <- findMsMsHRperxcms.direct(files[[i]][j], unique(cpdIDs)[i], mode=mode, findPeaksArgs=findPeaksArgs, plots)	
-			}
-			w@specs[[i]] <- toRMB(unlist(specs, recursive = FALSE), unique(cpdIDs)[i], mode=mode)
-		}
-		names(w@specs) <- basename(as.character(w@files))
-	}
-	
+#	if(readMethod == "xcms"){
+#		splitfn <- strsplit(w@files,'_')
+#		cpdIDs <- sapply(splitfn, function(splitted){as.numeric(return(splitted[length(splitted)-1]))})
+#		files <- list()
+#		wfiles <- vector()
+#			for(i in 1:length(unique(cpdIDs))) {
+#			indices <- sapply(splitfn,function(a){return(unique(cpdIDs)[i] %in% a)})
+#			files[[i]] <- w@files[indices]
+#		}
+#		
+#		w@files <- sapply(files,function(files){return(files[1])})
+#		
+#		for(i in 1:length(unique(cpdIDs))){
+#			specs <- list()
+#			for(j in 1:length(files[[i]])){
+#				specs[[j]] <- findMsMsHRperxcms.direct(files[[i]][j], unique(cpdIDs)[i], mode=mode, findPeaksArgs=findPeaksArgs, plots)	
+#			}
+#			w@specs[[i]] <- toRMB(unlist(specs, recursive = FALSE), unique(cpdIDs)[i], mode=mode)
+#		}
+#		names(w@specs) <- basename(as.character(w@files))
+#	}
+#	
 	##if(readMethod == "MassBank"){
 	##	for(i in 1:length(w@files)){
 	##		w <- addMB(w, w@files[i], mode)

R/leMsmsRaw.R

@@ -32,7 +32,7 @@ NULL
 #'			mzCoarse = getOption("RMassBank")$findMsMsRawSettings$mzCoarse,
 #'			fillPrecursorScan = getOption("RMassBank")$findMsMsRawSettings$fillPrecursorScan,
 #'			rtMargin = getOption("RMassBank")$rtMargin,
-#'			deprofile = getOption("RMassBank")$deprofile)
+#'			deprofile = getOption("RMassBank")$deprofile, headerCache = NA)
 #' 
 #' @aliases findMsMsHR.mass findMsMsHR.direct findMsMsHR
 #' @param fileName The file to open and search the MS2 spectrum in.
@@ -260,110 +260,6 @@ findMsMsHR.direct <- function(msRaw, cpdID, mode = "pH", confirmMode = 0, useRtL
   return(sp)
 }
 
-#' Read in mz-files using XCMS
-#' 
-#' Picks peaks from mz-files and returns the pseudospectra that CAMERA creates with the help of XCMS
-#'
-#' @usage findMsMsHRperxcms.direct(fileName, cpdID, mode="pH", findPeaksArgs = NULL, plots = FALSE) 
-#' @param fileName The path to the mz-file that should be read
-#' @param cpdID The compoundID of the compound that has been used for the file
-#' @param mode The ionization mode that has been used for the spectrum represented by the peaklist
-#' @param findPeaksArgs A list of arguments that will be handed to the xcms-method findPeaks via do.call
-#' @param plots A parameter that determines whether the spectra should be plotted or not
-#' @return The \code{msmsWorkspace} with the additional peaklist added to the right spectrum
-#' @seealso \code{\link{msmsWorkflow}}
-#' @author Erik Mueller
-#' @examples \dontrun{
-#' 		fileList <- list.files(system.file("XCMSinput", package = "RMassBank"), "Glucolesquerellin", full.names=TRUE)[3]
-#'		loadList(system.file("XCMSinput/compoundList.csv",package="RMassBank"))
-#'      psp <- findMsMsHRperxcms.direct(fileList,2184)
-#' }
-#' @export
-findMsMsHRperxcms.direct <- function(fileName, cpdID, mode="pH", findPeaksArgs = NULL, plots = FALSE) {
-	
-	require(CAMERA)
-	require(xcms)
-	parentMass <- findMz(cpdID)$mzCenter
-	RT <- findRt(cpdID)$RT * 60
-	mzabs <- 0.1
-	
-	getRT <- function(xa) {
-		rt <- sapply(xa@pspectra, function(x) {median(peaks(xa@xcmsSet)[x, "rt"])})
-	}
-	##
-	## MS
-	##
-	
-	
-	
-	##
-	## MSMS
-	##
-	xrmsms <- xcmsRaw(fileName, includeMSn=TRUE)
-	print("File read")
-	## Where is the wanted isolation ?
-	precursorrange <- range(which(xrmsms@msnPrecursorMz == parentMass)) ## TODO: add ppm one day
-
-	## Fake MS1 from MSn scans
-	## xrmsmsAsMs <- msn2xcmsRaw(xrmsms)
-	
-	xrs <- split(msn2xcmsRaw(xrmsms), f=xrmsms@msnCollisionEnergy)
-	## Fake s simplistic xcmsSet
-	setReplicate <- xcmsSet(files=fileName, method="MS1")
-	xsmsms <- as.list(replicate(length(xrs),setReplicate))
-	candidates <- list()
-	anmsms <- list()
-	psp <- list()
-	spectra <- list()
-	whichmissing <- vector()
-	
-	for(i in 1:length(xrs)){
-		peaks(xsmsms[[i]]) <- do.call(findPeaks,c(findPeaksArgs, object = xrs[[i]]))
-
-                if (nrow(peaks(xsmsms[[i]])) == 0) {
-                  spectra[[i]] <- matrix(0,2,7)
-                  next 
-                }
-                
-		## Get pspec 
-		pl <- peaks(xsmsms[[i]])[,c("mz", "rt"), drop=FALSE]
-
-		## Best: find precursor peak
-		candidates[[i]] <- which( pl[,"mz", drop=FALSE] < parentMass + mzabs & pl[,"mz", drop=FALSE] > parentMass - mzabs
-						& pl[,"rt", drop=FALSE] < RT * 1.1 & pl[,"rt", drop=FALSE] > RT * 0.9 )
-                
-		print(paste("Candidates:",candidates[[i]]))
-		anmsms[[i]] <- xsAnnotate(xsmsms[[i]])
-		anmsms[[i]] <- groupFWHM(anmsms[[i]])
-
-        if(length(candidates[[i]]) > 0)
-		closestCandidate <- which.min (abs( RT - pl[candidates[[i]], "rt", drop=FALSE]  ) )
-        else(closestCandidate <- 1)
-		## Now find the pspec for compound
-		
-		psp[[i]] <- which(sapply(anmsms[[i]]@pspectra, function(x) {candidates[[i]][closestCandidate] %in% x}))       
-		print(paste("Pseudospectra:",psp[[i]]))
-
-		## 2nd best: Spectrum closest to MS1
-		##psp <- which.min( abs(getRT(anmsms) - actualRT))
-
-		## 3rd Best: find pspec closest to RT from spreadsheet
-		##psp <- which.min( abs(abs(getRT(anmsms) - RT) )
-		if((plots == TRUE) && (length(psp[[i]]) > 0)){
-			plotPsSpectrum(anmsms[[i]], psp[[i]], log=TRUE,  mzrange=c(0, findMz(cpdID)[[3]]), maxlabel=10)
-		}
-		if(length(psp[[i]]) != 0){
-		spectra[[i]] <- getpspectra(anmsms[[i]], psp[[i]])
-		} else {whichmissing <- c(whichmissing,i)}
-	}
-	if(length(spectra) != 0){
-		for(i in whichmissing){
-			spectra[[i]] <- matrix(0,2,7)
-		}
-	}
-	return(spectra)
-}
-
 # Finds the EIC for a mass trace with a window of x ppm.
 # (For ppm = 10, this is +5 / -5 ppm from the non-recalibrated mz.)
 #' Extract EICs 
@@ -408,120 +304,6 @@ findEIC <- function(msRaw, mz, limit = NULL, rtLimit = NA)
 	return(data.frame(rt = rt, intensity=pks_t, scan=scan))
 }
 
-#' Conversion of XCMS-pseudospectra into RMassBank-spectra
-#' 
-#' Converts a pseudospectrum extracted from XCMS using CAMERA into the msmsWorkspace(at)specs-format that RMassBank uses
-#'
-#' @usage toRMB(msmsXCMSspecs, cpdID, mode, MS1spec)
-#' @param msmsXCMSspecs The compoundID of the compound that has been used for the peaklist
-#' @param cpdID The compound ID of the substance of the given spectrum
-#' @param mode The ionization mode that has been used for the spectrum
-#' @param MS1spec The MS1-spectrum from XCMS, which can be optionally supplied
-#' @return One list element of the (at)specs-entry from an msmsWorkspace
-#' @seealso \code{\link{msmsWorkspace-class}}
-#' @author Erik Mueller
-#' @examples \dontrun{
-#' 		XCMSpspectra <- findmsmsHRperxcms.direct("Glucolesquerellin_2184_1.mzdata", 2184)
-#'      wspecs <- toRMB(XCMSpspectra)
-#' }
-#' @export
-toRMB <- function(msmsXCMSspecs = NA, cpdID = NA, mode="pH", MS1spec = NA){
-	
-	ret <- list()
-	ret$mz <- findMz(cpdID,mode=mode)
-	ret$id <- cpdID
-	ret$formula <- findFormula(cpdID)
-	print(paste("Length of msmsXCMSspecs:",length(msmsXCMSspecs)))
-	if(length(msmsXCMSspecs) == 0){
-		ret$foundOK <- FALSE
-		print("blabla")
-		return(ret)
-	}
-	if(is.na(msmsXCMSspecs)){
-			stop("You need a readable spectrum!")
-	}
-	if(is.na(cpdID)){
-			stop("Please supply the compoundID!")
-	}
-	numScan <- length(msmsXCMSspecs)
-
-	
-	ret$foundOK <- TRUE
-	ret$parentscan <- 1
-	ret$parentHeader <- matrix(0, ncol = 20, nrow = 1)
-	rownames(ret$parentHeader) <- 1
-	colnames(ret$parentHeader) <- c("seqNum", "acquisitionNum", "msLevel", "peaksCount", "totIonCurrent", "retentionTime", "basepeakMZ", 
-									"basePeakIntensity", "collisionEnergy", "ionisationEnergy", "lowMZ", "highMZ", "precursorScanNum",
-									"precursorMZ", "precursorCharge", "precursorIntensity", "mergedScan", "mergedResultScanNum", 
-									"mergedResultStartScanNum", "mergedResultEndScanNum")
-	ret$parentHeader[1,1:3] <- 1
-	##Write nothing in the parents if there is no MS1-spec
-	if(is.na(MS1spec)){
-		ret$parentHeader[1,4:20] <- 0
-                ret$parentHeader[1,6] <- NA
-	} else { ##Else use the MS1spec spec to write everything into the parents
-		ret$parentHeader[1,4] <- length(MS1spec[,1])
-		ret$parentHeader[1,5] <- 0
-		ret$parentHeader[1,6] <- findRt(cpdID)
-		ret$parentHeader[1,7] <- MS1spec[which.max(MS1spec[,7]),1]
-		ret$parentHeader[1,8] <- max(MS1spec[,7])
-		ret$parentHeader[1,9] <- 0
-		ret$parentHeader[1,10] <- 0
-		ret$parentHeader[1,11] <- min(MS1spec[,1])
-		ret$parentHeader[1,12] <- max(MS1spec[,1])
-		ret$parentHeader[1,13:20] <- 0 ##Has no precursor and merge is not yet implemented
-	}
-	ret$parentHeader <- as.data.frame(ret$parentHeader)
-	
-	##Write the peaks into the childscans
-	ret$childScans <- 2:(numScan+1)
-
-	childHeader <- t(sapply(msmsXCMSspecs, function(spec){
-		header <- vector()
-		header[3] <- 2
-		header[4] <- length(spec[,1])
-		header[5] <- 0 ##Does this matter?
-		header[6] <- median(spec[,4])
-		header[7] <- spec[which.max(spec[,7]),1]
-		header[8] <- max(spec[,7])
-		header[9] <- 0 ##Does this matter?
-		header[10] <- 0 ##Does this matter?
-		header[11] <- min(spec[,1])
-		header[12] <- max(spec[,1]) 
-		header[13] <- 1
-		header[14] <- findMz(cpdID)[[3]]
-		header[15] <- 1 ##Will be changed for different charges
-		header[16] <- 0 ##There sadly isnt any precursor intensity to find in the msms-scans. Workaround? msmsXCMS@files[1]
-		header[17:20] <- 0 ##Will be changed if merge is wanted
-		return(header)
-		}))
-		childHeader[,1:2] <- 2:(length(msmsXCMSspecs)+1)
-	
-	
-	ret$childHeader <- as.data.frame(childHeader)
-	rownames(ret$childHeader) <- 2:(numScan+1)
-	colnames(ret$childHeader) <- c("seqNum", "acquisitionNum", "msLevel", "peaksCount", "totIonCurrent", "retentionTime", "basepeakMZ", 
-									"basePeakIntensity", "collisionEnergy", "ionisationEnergy", "lowMZ", "highMZ", "precursorScanNum",
-									"precursorMZ", "precursorCharge", "precursorIntensity", "mergedScan", "mergedResultScanNum", 
-									"mergedResultStartScanNum", "mergedResultEndScanNum")
-        if (is.na(ret$parentHeader[1,"retentionTime"])) {
-          ## Overwrite MS1 RT with average from MS2 
-          ret$parentHeader[1,"retentionTime"] <- median(ret$childHeader[which(ret$childHeader[,"retentionTime"] != 0), "retentionTime"])
-        }
-	
-	ret$parentPeak <- matrix(nrow = 1, ncol = 2)
-	colnames(ret$parentPeak) <- c("mz","int")
-	ret$parentPeak[1,] <- c(findMz(cpdID,mode=mode)$mzCenter,100)
-	ret$peaks <- list()
-	ret$peaks <- lapply (msmsXCMSspecs, function(specs){
-									peaks <- matrix(nrow = length(specs[,1]), ncol = 2)
-									colnames(peaks) <- c("mz","int")
-									peaks[,1] <- specs[,1]
-									peaks[,2] <- specs[,7]
-									return(peaks)
-								})
-	return(ret)
-}
 
 #' Addition of manual peaklists
 #' 

R/settings_example.R

-
+#' @import yaml
+NULL
 
 .checkMbSettings <- function()
 {

man/RmbDefaultSettings.Rd

 \name{RmbDefaultSettings}
-\alias{loadRmbSettings}
-\alias{loadRmbSettingsFromEnv}
 \alias{RmbDefaultSettings}
 \alias{RmbSettingsTemplate}
+\alias{loadRmbSettings}
+\alias{loadRmbSettingsFromEnv}
 \title{RMassBank settings}
 \usage{
   loadRmbSettings(file_or_list)

man/combineMultiplicities.Rd

@@ -39,7 +39,7 @@
  w1 <- msmsWorkflow(w, steps=c(1:7), mode="pH")
  w2 <- msmsWorkflow(w, steps=c(1:7), mode="pH", confirmMode = 1)
  wTotal <- combineMultiplicities(c(w1, w2))
- wTotal <- msmsWorkflow(wTotal, steps=8, mode="pH", archiveName = "output")
+ wTotal <- msmsWorkflow(wTotal, steps=8, mode="pH", archivename = "output")
  # continue here with mbWorkflow
 }
 }

man/findMsMsHR.Rd

@@ -27,7 +27,7 @@
     fillPrecursorScan =
     getOption("RMassBank")$findMsMsRawSettings$fillPrecursorScan,
     rtMargin = getOption("RMassBank")$rtMargin, deprofile =
-    getOption("RMassBank")$deprofile)
+    getOption("RMassBank")$deprofile, headerCache = NA)
 }
 \arguments{
   \item{fileName}{The file to open and search the MS2

man/findMsMsHRperxcms.direct.Rd

-\name{findMsMsHRperxcms.direct}
-\alias{findMsMsHRperxcms.direct}
-\title{Read in mz-files using XCMS}
-\usage{
-  findMsMsHRperxcms.direct(fileName, cpdID, mode="pH",
-    findPeaksArgs = NULL, plots = FALSE)
-}
-\arguments{
-  \item{fileName}{The path to the mz-file that should be
-  read}
-
-  \item{cpdID}{The compoundID of the compound that has been
-  used for the file}
-
-  \item{mode}{The ionization mode that has been used for
-  the spectrum represented by the peaklist}
-
-  \item{findPeaksArgs}{A list of arguments that will be
-  handed to the xcms-method findPeaks via do.call}
-
-  \item{plots}{A parameter that determines whether the
-  spectra should be plotted or not}
-}
-\value{
-  The \code{msmsWorkspace} with the additional peaklist
-  added to the right spectrum
-}
-\description{
-  Picks peaks from mz-files and returns the pseudospectra
-  that CAMERA creates with the help of XCMS
-}
-\examples{
-\dontrun{
-		fileList <- list.files(system.file("XCMSinput", package = "RMassBank"), "Glucolesquerellin", full.names=TRUE)[3]
-		loadList(system.file("XCMSinput/compoundList.csv",package="RMassBank"))
-     psp <- findMsMsHRperxcms.direct(fileList,2184)
-}
-}
-\author{
-  Erik Mueller
-}
-\seealso{
-  \code{\link{msmsWorkflow}}
-}
-

man/findProgress.Rd

@@ -16,6 +16,11 @@
   the \code{workspace} object and finds out which steps
   have already been processed on it.
 }
+\examples{
+\dontrun{
+findProgress(w)
+}
+}
 \author{
   Stravs MA, Eawag <michael.stravs@eawag.ch>
 }

man/msmsWorkflow.Rd

@@ -4,10 +4,9 @@
 \usage{
   msmsWorkflow(w, mode="pH", steps=c(1:8), confirmMode =
     FALSE, newRecalibration = TRUE, useRtLimit = TRUE,
-    archivename=NA, readMethod = "mzR", findPeaksArgs = NA,
-    plots = FALSE, precursorscan.cf = FALSE, settings =
-    getOption("RMassBank"), analyzeMethod = "formula",
-    progressbar = "progressBarHook")
+    archivename=NA, readMethod = "mzR", precursorscan.cf =
+    FALSE, settings = getOption("RMassBank"), analyzeMethod
+    = "formula", progressbar = "progressBarHook")
 }
 \arguments{
   \item{w}{A \code{msmsWorkspace} to work with.}
@@ -35,25 +34,16 @@
   analyzed result files.}
 
   \item{readMethod}{Several methods are available to get
-  peak lists from the files.  Currently supported are
-  "mzR", "xcms", "MassBank" and "peaklist".  The first two
-  read MS/MS raw data, and differ in the strategy used to
-  extract peaks. MassBank will read existing records, so
-  that e.g. a recalibration can be performed, and
-  "peaklist" just requires a CSV with two columns and the
-  column header "mz", "int".}
+  peak lists from the input files.  Currently supported are
+  "mzR" and "peaklist".  "mzR" reads MS/MS raw data. An
+  alternative raw data reader "xcms" is not yet released.
+  "peaklist" reads a CSV with two columns and the column
+  header "mz", "int".}
 
-  \item{findPeaksArgs}{A list of arguments that will be
-  handed to the xcms-method findPeaks via do.call}
-
-  \item{plots}{A parameter that determines whether the
-  spectra should be plotted or not (This parameter is only
-  used for the xcms-method)}
-
-  \item{precursorscan.cf}{Whether to fill precursor scans.
-  To be used with files which for some reasons do not
-  contain precursor scan IDs in the mzML, e.g. AB Sciex
-  converted files.}
+  \item{precursorscan.cf}{Whether to fill precursor scan
+  entries (cf = carry forward). To be used with files which
+  for some reasons do not contain precursor scan IDs in the
+  mzML, e.g. AB Sciex converted files.}
 
   \item{settings}{Options to be used for processing.
   Defaults to the options loaded via

man/toRMB.Rd

-\name{toRMB}
-\alias{toRMB}
-\title{Conversion of XCMS-pseudospectra into RMassBank-spectra}
-\usage{
-  toRMB(msmsXCMSspecs, cpdID, mode, MS1spec)
-}
-\arguments{
-  \item{msmsXCMSspecs}{The compoundID of the compound that
-  has been used for the peaklist}
-
-  \item{cpdID}{The compound ID of the substance of the
-  given spectrum}
-
-  \item{mode}{The ionization mode that has been used for
-  the spectrum}
-
-  \item{MS1spec}{The MS1-spectrum from XCMS, which can be
-  optionally supplied}
-}
-\value{
-  One list element of the (at)specs-entry from an
-  msmsWorkspace
-}
-\description{
-  Converts a pseudospectrum extracted from XCMS using
-  CAMERA into the msmsWorkspace(at)specs-format that
-  RMassBank uses
-}
-\examples{
-\dontrun{
-		XCMSpspectra <- findmsmsHRperxcms.direct("Glucolesquerellin_2184_1.mzdata", 2184)
-     wspecs <- toRMB(XCMSpspectra)
-}
-}
-\author{
-  Erik Mueller
-}
-\seealso{
-  \code{\link{msmsWorkspace-class}}
-}
-

vignettes/RMassBankXCMS.Rnw

-% \VignetteIndexEntry{RMassBank using XCMS walkthrough}
-% \VignettePackage{rcdk}
-% \VignetteKeywords{}
-%% To generate the Latex code
-%library(RMassBank)
-%Rnwfile<- file.path("RMassBankXCMS.Rnw")
-%Sweave(Rnwfile,pdf=TRUE,eps=TRUE,stylepath=TRUE,driver=RweaveLatex())
-
-
-\documentclass[letterpaper, 11pt]{article}
-
-\usepackage{times}
-\usepackage{url}
-\usepackage[pdftex,bookmarks=true]{hyperref}
-
-\newcommand{\Rfunction}[1]{{\texttt{#1}}}
-\newcommand{\Rpackage}[1]{{\textit{#1}}}
-\newcommand{\funcarg}[1]{{\texttt{#1}}}
-
-\newcommand{\Rvar}[1]{{\texttt{#1}}}
-
-\newcommand{\rclass}[1]{{\textit{#1}}}
-
-<<echo=FALSE>>=
-options(width=74)
-#library(xtable)
-@
-\parindent 0in
-\parskip 1em
-
-\begin{document}
-
-\title{RMassBank for XCMS}
-\author{Erik M\"uller}
-\maketitle
-\tableofcontents
-\newpage
-
-\section{Introduction}
-
-As the RMassBank-workflow is described in the other manual, this document mainly explains how to utilize the
-XCMS-, MassBank-, andpeaklist-readMethods for step 1 of the workflow.
-
-\section{Input files}
-
-\subsection{LC/MS data}
-
-\Rpackage{RMassBank} handles high-resolution LC/MS spectra in mzML or mzdata format in
-centroid\footnote{The term "centroid" here refers to any kind of data which are
-not in profile mode, i.e. don't have continuous m/z data. It does not refer to
-the (mathematical) centroid peak, i.e. the area-weighted mass peak.} or in
-profile mode.
-Data in the examples was acquired using an QTOF instrument.
-
-In the standard workflow, the file names are used to identify a
-compound: file names must be in the format \funcarg{xxxxxxxx\_1234\_xxx.mzXML},
-where the xxx parts denote anything and the 1234 part denotes the compound ID in
-the compound list (see below). Advanced and alternative uses can be implemented;
-consult the implementation of \Rvar{msms\_workflow}  and \Rvar{findMsMsHRperX.direct} for
-more information.
-
-\section{Additional Workflow-Methods}
-
-The data used in the following example is available as a package \Rpackage{RMassBankData},
-so both libraries have to be installed to run this vignette.
-
-<<>>=
-library(RMassBank)
-library(RMassBankData)
-@ 
-
-\subsection{Options}
-
-In the first part of the workflow, spectra are extracted from the files and processed. In the following example, we will process the Glulesquerellin spectra from the provided files.
-
-For the workflow to work correctly, we use the default settings, and modify then to match the data acquisition method. The settings have to contain the same parameters as the mzR-method would for the workflow.
-
-<<echo=TRUE,eval=TRUE>>=
-RmbDefaultSettings() 
-rmbo <- getOption("RMassBank")
-rmbo$spectraList <- list(
-  list(mode="CID", ces="10eV", ce="10eV", res=12000),
-  list(mode="CID", ces="20eV", ce="20eV", res=12000)
-)
-
-rmbo$filterSettings$prelimCut <- 0
-
-rmbo$annotations$instrument <- "Bruker micrOTOFq"
-rmbo$annotations$instrument_type <- "LC-ESI-QTOF"
-
-options("RMassBank" = rmbo)
-
-
-@
-
-
-\subsection{XCMS-workflow}
-
-First, a workspace for the \Rvar{msmsWorkflow} must be created:
-<<>>=
-msmsList <- newMsmsWorkspace()
-@
-
-The full paths of the files must be loaded into the container in the array
-\Rvar{files}:
-
-<<>>=
-msmsList@files <- list.files(system.file("spectra.Glucolesquerellin", 
-                                         package = "RMassBankData"), 
-                             "Glucolesquerellin.*mzData", full.names=TRUE)
-@
-
-Note the position of the compound IDs in the filenames. Historically, the "\Rvar{pos}" at the end was used to denote the polarity; it is obsolete now, but the ID must be terminated with an underscore.
-If you have multiple files for one compound, you have to give them the same ID, but thanks to the polarity at the end being obsolete, you can just enumerate them.
-
-Additionally, the compound list must be loaded using \Rfunction{loadList}:
-
-<<>>=
-loadList(system.file("list/PlantDataset.csv",package="RMassBankData"))
-@
-
-Basically, the changes to the workflow using XCMS can be described as follows:
-
-The MS2-Spectra(and optionally the MS1-spectrum) are extracted and peakpicked using XCMS. You can pass different parameters for the \Rfunction{findPeaks} function of XCMS using the findPeaksArgs-argument to detect actual peaks. Then, CAMERA processes the peak lists and creates pseudospectra (or compound spectra). The obtained pseudospectra are stored in the array \Rvar{specs}.
-Please note that "findPeaksArgs" has to be a list with the list elements named after the arguments that the method you want to use contains, as findPeaks is called by \Rfunction{do.call}.
-For example, if you want to use centWave with a peakwidth from 5 to 10 and 25 ppm, findPeaksArgs would look like this:
-
-<<eval=TRUE>>=
-	Args <- list(method="centWave", 
-                     peakwidth=c(5,12), 
-                     prefilter=c(0,0), 
-                     ppm=25, snthr=2)
-@
-
-If you want to utilize XCMS for Step 1 of the workflow, you have to set the readMethod-parameter to "xcms" and - if you don't want to use standard values for findPeaks - pass on findPeaksArgs to the workflow.
-
-<<eval=TRUE>>=
-	msmsList <- msmsWorkflow(msmsList, steps=1:8, 
-                                 mode="mH", readMethod="xcms", 
-                                 findPeaksArgs = Args)
-@
-
-You can of course run the rest of the workflow as usual, by - like here - setting steps to 1:8
-
-\subsection{peaklist-workflow}
-
-The peaklist-workflow works akin to the normal mzR-workflow with the only difference being, that the supplied data has to be in .csv format and contain 2 columns: "mz" and "int".
-You can look at an example file in the RMassBankData-package in spectra.Glucolesquerellin. Please note that the naming of the csv has to be similar to the mzdata-files, with the only difference being the filename extension.
-The readMethod name for this is "peaklist"
-
-<<eval=FALSE>>=
-	msmsPeaklist <- newMsmsWorkspace()
-	msmsPeaklist@files <- list.files(system.file("spectra.Glucolesquerellin", 
-                                                     package = "RMassBankData"), 
-                                         "Glucolesquerellin.*csv", full.names=TRUE)
-	msmsPeaklist <- msmsWorkflow(msmsPeaklist, steps=1:8, 
-                                     mode="mH", readMethod="peaklist")
-@
-
-\subsection{Export the records}
-
-This section is just to debug the record creation with XCMS, and hence very terse.
-
-
-<<>>=
-mb <- newMbWorkspace(msmsList)
-mb <- resetInfolists(mb)
-mb <- loadInfolist(mb,system.file("infolists/PlantDataset.csv", 
-                                  package = "RMassBankData"))
-## Step 
-mb <- mbWorkflow(mb, steps=3:4)
-@
-
-
-
-
-\section{Session information}
-
-<<>>=
-sessionInfo()
-@
-
-\end{document}
-