View source: R/do_findChromPeaksfunctions.R
do_findChromPeaks_centWaveWithPredIsoROIs  R Documentation 
The do_findChromPeaks_centWaveWithPredIsoROIs
performs a
twostep centWave based peak detection: chromatographic peaks are
identified using centWave followed by a prediction of the location of
the identified peaks' isotopes in the mzretention time space. These
locations are fed as regions of interest (ROIs) to a subsequent
centWave run. All non overlapping peaks from these two peak detection
runs are reported as the final list of identified peaks.
The do_findChromPeaks_centWaveAddPredIsoROIs
performs
centWave based peak detection based in regions of interest (ROIs)
representing predicted isotopes for the peaks submitted with argument
peaks.
. The function returns a matrix with the identified peaks
consisting of all input peaks and peaks representing predicted isotopes
of these (if found by the centWave algorithm).
do_findChromPeaks_centWaveWithPredIsoROIs(
mz,
int,
scantime,
valsPerSpect,
ppm = 25,
peakwidth = c(20, 50),
snthresh = 10,
prefilter = c(3, 100),
mzCenterFun = "wMean",
integrate = 1,
mzdiff = 0.001,
fitgauss = FALSE,
noise = 0,
verboseColumns = FALSE,
roiList = list(),
firstBaselineCheck = TRUE,
roiScales = NULL,
snthreshIsoROIs = 6.25,
maxCharge = 3,
maxIso = 5,
mzIntervalExtension = TRUE,
polarity = "unknown",
extendLengthMSW = FALSE,
verboseBetaColumns = FALSE
)
do_findChromPeaks_addPredIsoROIs(
mz,
int,
scantime,
valsPerSpect,
ppm = 25,
peakwidth = c(20, 50),
snthresh = 6.25,
prefilter = c(3, 100),
mzCenterFun = "wMean",
integrate = 1,
mzdiff = 0.001,
fitgauss = FALSE,
noise = 0,
verboseColumns = FALSE,
peaks. = NULL,
maxCharge = 3,
maxIso = 5,
mzIntervalExtension = TRUE,
polarity = "unknown"
)
mz 
Numeric vector with the individual m/z values from all scans/ spectra of one file/sample. 
int 
Numeric vector with the individual intensity values from all scans/spectra of one file/sample. 
scantime 
Numeric vector of length equal to the number of spectra/scans of the data representing the retention time of each scan. 
valsPerSpect 
Numeric vector with the number of values for each spectrum. 
ppm 

peakwidth 

snthresh 
For 
prefilter 

mzCenterFun 
Name of the function to calculate the m/z center of the
chromatographic peak. Allowed are: 
integrate 
Integration method. For 
mzdiff 

fitgauss 

noise 

verboseColumns 

roiList 
An optional list of regionsofinterest (ROI) representing
detected mass traces. If ROIs are submitted the first analysis step is
omitted and chromatographic peak detection is performed on the submitted
ROIs. Each ROI is expected to have the following elements specified:

firstBaselineCheck 

roiScales 
Optional numeric vector with length equal to 
snthreshIsoROIs 

maxCharge 

maxIso 

mzIntervalExtension 

polarity 

extendLengthMSW 
Option to force centWave to use all scales when
running centWave rather than truncating with the EIC length. Uses the "open"
method to extend the EIC to a integer base2 length prior to being passed to

verboseBetaColumns 
Option to calculate two additional metrics of peak
quality via comparison to an idealized bell curve. Adds 
peaks. 
A matrix or 
For more details on the centWave algorithm see
centWave
.
A matrix, each row representing an identified chromatographic peak. All nonoverlapping peaks identified in both centWave runs are reported. The matrix columns are:
Intensity weighted mean of m/z values of the peaks across scans.
Minimum m/z of the peaks.
Maximum m/z of the peaks.
Retention time of the peak's midpoint.
Minimum retention time of the peak.
Maximum retention time of the peak.
Integrated (original) intensity of the peak.
Perpeak baseline corrected integrated peak intensity.
Maximum intensity of the peak.
Signal to noise ratio, defined as (maxo  baseline)/sd
,
sd
being the standard deviation of local chromatographic noise.
RMSE of Gaussian fit.
Additional columns for verboseColumns = TRUE
:
Gaussian parameter mu.
Gaussian parameter sigma.
Gaussian parameter h.
Region number of the m/z ROI where the peak was localized.
m/z deviation of mass trace across scans in ppm.
Scale on which the peak was localized.
Peak position found by wavelet analysis (scan number).
Left peak limit found by wavelet analysis (scan number).
Right peak limit found by wavelet analysis (scan numer).
Additional columns for verboseBetaColumns = TRUE
:
Correlation between an "ideal" bell curve and the raw data
Signaltonoise residuals calculated from the beta_cor fit
Hendrik Treutler, Johannes Rainer
Other core peak detection functions:
do_findChromPeaks_centWave()
,
do_findChromPeaks_massifquant()
,
do_findChromPeaks_matchedFilter()
,
do_findPeaks_MSW()
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