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## Init a new peakPantheRAnnotation object after loading ROI, uROI and FIR parameters from CSV
#' Load fit parameters from CSV
#'
#' Initialise a new \code{peakPantheRAnnotation} object after loading ROI, uROI and FIR parameters from CSV. \code{spectraPaths}, \code{spectraMetadata} or \code{cpdMetadata} are not initialised and will need to be filled before annotation. \code{useUROI} and \code{useFIR} are set to \code{FALSE} and will need to be set accordingly. \code{uROIExist} is established depending on the uROI columns present in the CSV and will be set to \code{TRUE} only if no \code{NA} are present
#'
#' @param CSVParamPath (str) Path to a CSV file of fit parameters as saved by \code{outputAnnotationDiagnostic}
#' @param verbose (bool) If TRUE message progress
#'
#' @return (peakPantheRAnnotation) Object initialised with ROI, uROI and FIR read from the CSV file
#'
#' @export
peakPantheR_loadAnnotationParamsCSV <- function(CSVParamPath, verbose=TRUE) {
# Check file exist
if (!file.exists(CSVParamPath)) {
stop('specified "CSVParamPath" does not exist')
}
# Read file
tmp_csv <- read.csv(CSVParamPath, header=TRUE, sep=",", quote="\"", stringsAsFactors=FALSE)
# Check columns
expected_col <- c("cpdID", "cpdName", "ROI_rt", "ROI_mz", "ROI_rtMin", "ROI_rtMax", "ROI_mzMin", "ROI_mzMax", "uROI_rtMin", "uROI_rtMax", "uROI_mzMin", "uROI_mzMax", "uROI_rt", "uROI_mz", "FIR_rtMin", "FIR_rtMax", "FIR_mzMin", "FIR_mzMax")
if (!(all(expected_col %in% colnames(tmp_csv)))) {
stop('Columns in "CSVParamPath" must be: "cpdID", "cpdName", "ROI_rt", "ROI_mz", "ROI_rtMin", "ROI_rtMax", "ROI_mzMin", "ROI_mzMax", "uROI_rtMin", "uROI_rtMax", "uROI_mzMin", "uROI_mzMax", "uROI_rt", "uROI_mz", "FIR_rtMin", "FIR_rtMax", "FIR_mzMin", "FIR_mzMax"')
}
# Prepare ROI, uROI and FIR
tmp_targetFeatTable <- tmp_csv[,c("cpdID", "cpdName", "ROI_rtMin", "ROI_rt", "ROI_rtMax", "ROI_mzMin", "ROI_mz", "ROI_mzMax")]
colnames(tmp_targetFeatTable) <- c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax")
tmp_targetFeatTable[,c(3:8)] <- sapply(tmp_targetFeatTable[,c(3:8)], as.numeric)
tmp_uROI <- tmp_csv[,c("uROI_rtMin", "uROI_rt", "uROI_rtMax", "uROI_mzMin", "uROI_mz", "uROI_mzMax")]
colnames(tmp_uROI) <- c("rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax")
tmp_uROI[,c(1:6)] <- sapply(tmp_uROI[,c(1:6)], as.numeric)
tmp_FIR <- tmp_csv[,c("FIR_rtMin", "FIR_rtMax", "FIR_mzMin", "FIR_mzMax")]
colnames(tmp_FIR) <- c("rtMin", "rtMax", "mzMin", "mzMax")
tmp_FIR[,c(1:4)] <- sapply(tmp_FIR[,c(1:4)], as.numeric)
# establish if uROIExist
tmp_uROIExist <- !any(is.na(tmp_uROI[,c("rtMin", "rtMax", "mzMin", "mzMax")]))
if (tmp_uROIExist) {
if (verbose) { message('uROIExist set to TRUE') }
} else {
if (verbose) { message('NA in uROI, uROIExist is set to FALSE') }
}
# Initialise new object
tmp_annotation <- peakPantheRAnnotation(targetFeatTable=tmp_targetFeatTable, uROI=tmp_uROI, FIR=tmp_FIR, uROIExist=tmp_uROIExist)
if (verbose) { message('New peakPantheRAnnotation object initialised for ', nbCompounds(tmp_annotation), ' compounds') }
return(tmp_annotation)
}
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