peakPantheR_ROIStatistics {peakPantheR} | R Documentation |
Using reference samples (referenceSpectraFiles
), save
(to saveFolder
) each ROI EIC (ROI
) and reports the mean apex RT
for all IS (IS_ROI
) across samples
peakPantheR_ROIStatistics( referenceSpectraFiles, saveFolder, ROI = NULL, IS_ROI = NULL, sampleColour = NULL, ncores = 0, saveISPlots = TRUE, verbose = TRUE )
referenceSpectraFiles |
(str) A character vector of paths to the reference spectra files |
saveFolder |
(str) Path to the folder where EICs and IS mean RT
( |
ROI |
(data.frame) NULL or a data.frame of Regions Of Interest (ROI)
with compounds as row and ROI parameters as columns: |
IS_ROI |
(data.frame) NULL or a data.frame of IS ROI with IS as row and
ROI parameters as columns: |
sampleColour |
(str) NULL or vector colour for each sample |
ncores |
(int) Number of cores to use to integrate IS in parallel |
saveISPlots |
(bool) If TRUE save a diagnostic plot for each IS to
|
verbose |
(bool) If TRUE message progress |
None
if(requireNamespace('faahKO')){ ## Initialise a peakPantheRAnnotation object with 2 samples and 1 targeted ## compound # Paths to spectra files library(faahKO) spectraPaths <- c(system.file('cdf/KO/ko15.CDF', package = 'faahKO'), system.file('cdf/KO/ko16.CDF', package = 'faahKO')) # targetFeatTable targetFeatTable <- data.frame(matrix(vector(), 1, 8, dimnames=list(c(), c('cpdID','cpdName','rtMin','rt','rtMax','mzMin','mz', 'mzMax'))), stringsAsFactors=FALSE) targetFeatTable[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778, 522.2, 522.205222) targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric, FUN.VALUE=numeric(1)) # input refSpecFiles <- spectraPaths input_ROI <- targetFeatTable input_IS_ROI <- targetFeatTable sampleColour <- c('blue', 'red') # temporary saveFolder saveFolder1 <- tempdir() # Calculate ROI statiscs peakPantheR_ROIStatistics(refSpecFiles, saveFolder1, ROI=input_ROI, IS_ROI=input_IS_ROI, sampleColour=sampleColour, ncores=0, saveISPlots=TRUE, verbose=TRUE) }