Description Usage Arguments Value Examples
Performs retention time correction to re-adjust the expected
retention time position of compounds.
Requires an annotated peakPantheRAnnotation object (isAnnotated=TRUE
).
The original rt
value is used as expected and the observed deviation
measured in the rt_dev_sec
field is taken as the deviation to be
corrected.
1 2 3 4 5 6 7 8 9 10 | ## S4 method for signature 'peakPantheRAnnotation'
retentionTimeCorrection(
annotationObject,
rtCorrectionReferences = NULL,
method = "polynomial",
params = list(polynomialOrder = 2),
robust = FALSE,
rtWindowWidth = 15,
diagnostic = TRUE
)
|
annotationObject |
(peakPantheRAnnotation) object with previous fit results to adjust retention time values in uROI and FIR annotationObject, rtCorrectionReferences=NULL, |
rtCorrectionReferences |
(list) of compounds IDs ( |
method |
(str) name of RT correction method to use (currently
|
params |
(list) list of parameters to pass to each correction method.
Currently allowed inputs are |
robust |
(bool) whether to use the RANSAC algorithm to flag and ignore outliers during retention time correction |
rtWindowWidth |
(numeric) full width in seconds of the retention time window defined around the corrected retention time value for each compound |
diagnostic |
(bool) If TRUE returns diagnostic plots (specific to each correction method) |
(list) containing entries 'annotation', with the new and retention
time corrected peakPantheRAnnotation, and 'plot' (if diagnostic=TRUE
).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | if(requireNamespace('faahKO')){
## Initialise a peakPantheRAnnotation object with 3 samples and 2 targeted
## compounds
# 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(), 2, 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[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
496.2, 496.204962)
targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric,
FUN.VALUE=numeric(2))
smallAnnotation <- peakPantheRAnnotation(spectraPaths=spectraPaths,
targetFeatTable=targetFeatTable)
# annotate files serially
annotation_result <- peakPantheR_parallelAnnotation(smallAnnotation,
ncores=0, verbose=TRUE)
data_annotation <- annotation_result$annotation
# Example with constant correction
rtCorrectionOutput <- retentionTimeCorrection(
annotationObject = data_annotation,
rtCorrectionReferences=c('ID-1'),
method='constant', params=list(),
robust=FALSE,
rtWindowWidth=15,
diagnostic=TRUE)
rtCorrectedAnnotation <- rtCorrectionOutput$annotation
# rtCorrectedAnnotation
# An object of class peakPantheRAnnotation
# 2 compounds in 2 samples.
# updated ROI exists, with a modified rt (uROI)
# uses updated ROI (uROI)
# uses fallback integration regions (FIR)
# is annotated
rtCorrectionPlot <- rtCorrectionOutput$plot
# rtCorrectedPlot
# A ggplot2 object
# Scatterplot where x=`r` in the and y=`rt_dev_sec` from data_annotation
# Points colored depending on whether the reference was used to fit
# the correction model
}
|
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