Description Usage Arguments Details Value Slots Note Author(s) See Also Examples
FillChromPeaksParam object encapsules all settings for
the signal integration for missing peaks.
expandMz<-: getter and setter
expandMz slot of the object.
expandRt<-: getter and setter
expandRt slot of the object.
ppm<-: getter and setter
ppm slot of the object.
Integrate signal in the mz-rt area of a feature (chromatographic
peak group) for samples in which no chromatographic peak for this
feature was identified and add it to the
chromPeaks. Such peaks
will have a value of
1 in the
"is_filled" column of the
chromPeaks matrix of the object.
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FillChromPeaksParam(expandMz = 0, expandRt = 0, ppm = 0, fixedMz = 0, fixedRt = 0) fixedRt(object) fixedMz(object) ## S4 method for signature 'FillChromPeaksParam' show(object) ## S4 method for signature 'FillChromPeaksParam' expandMz(object) ## S4 replacement method for signature 'FillChromPeaksParam' expandMz(object) <- value ## S4 method for signature 'FillChromPeaksParam' expandRt(object) ## S4 replacement method for signature 'FillChromPeaksParam' expandRt(object) <- value ## S4 method for signature 'FillChromPeaksParam' ppm(object) ## S4 replacement method for signature 'FillChromPeaksParam' ppm(object) <- value ## S4 method for signature 'XCMSnExp,FillChromPeaksParam' fillChromPeaks(object, param, BPPARAM = bpparam()) ## S4 method for signature 'XCMSnExp,missing' fillChromPeaks(object, param, BPPARAM = bpparam())
The value for the slot.
Parallel processing settings.
After correspondence (i.e. grouping of chromatographic peaks across
samples) there will always be features (peak groups) that do not include
peaks from every sample. The
fillChromPeaks method defines
intensity values for such features in the missing samples by integrating
the signal in the mz-rt region of the feature. The mz-rt area is defined
by the median mz and rt start and end points of the other detected
chromatographic peaks for a given feature. Various parameters allow to
increase this area, either by a constant value (
fixedRt) or by a feature-relative amount (
Adjusted retention times will be used if available.
Based on the peak finding algorithm that was used to identify the
(chromatographic) peaks different internal functions are employed to
guarantee that the integrated peak signal matches as much as possible
the peak signal integration used during the peak detection. For peaks
identified with the
matchedFilter method, signal
integration is performed on the profile matrix generated with
the same settings used also during peak finding (using the same
bin size for example). For direct injection data and peaks
identified with the
MSW algorithm signal is integrated
only along the mz dimension. For all other methods the complete (raw)
signal within the area defined by
"rtmax" is used.
FillChromPeaksParam function returns a
XCMSnExp object with previously missing
chromatographic peaks for features filled into its
See corresponding parameter above.
.__classVersion__ stores the version of the class.
"rtmax" for the filled peaks represents the actual MS area from
which the signal was integrated.
Note that no peak is filled in if no signal was present in a file/sample
in the respective mz-rt area. These samples will still show a
in the matrix returned by the
featureValues method. This
is in contrast to the
fillPeaks.chrom method that returned
0 for such peak areas.
Growing the mz-rt area using the
might help to reduce the number of missing peak signals after filling.
groupChromPeaks for methods to perform the
dropFilledChromPeaks for the method to remove filled in peaks.
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## Perform the peak detection using centWave on some of the files from the ## faahKO package. Files are read using the readMSData from the MSnbase ## package library(faahKO) library(xcms) fls <- dir(system.file("cdf/KO", package = "faahKO"), recursive = TRUE, full.names = TRUE) raw_data <- readMSData(fls[1:2], mode = "onDisk") ## Create a CentWaveParam object. Note that the noise is set to 10000 to ## speed up the execution of the example - in a real use case the default ## value should be used, or it should be set to a reasonable value. cwp <- CentWaveParam(ppm = 20, noise = 10000, snthresh = 40) res <- findChromPeaks(raw_data, param = cwp) ## Perform the correspondence. We assign all samples to the same group. res <- groupChromPeaks(res, param = PeakDensityParam(sampleGroups = rep(1, length(fileNames(res))))) ## For how many features do we lack an integrated peak signal? sum(is.na(featureValues(res))) ## Filling missing peak data using default settings. res <- fillChromPeaks(res) ## Get the peaks that have been filled in: fp <- chromPeaks(res)[chromPeaks(res)[, "is_filled"] == 1, ] head(fp) ## Did we get a signal for all missing peaks? sum(is.na(featureValues(res))) ## No. ## Get the process history step along with the parameters used to perform ## The peak filling: ph <- processHistory(res, type = "Missing peak filling")[] ph ## The parameter class: ph@param ## Drop the filled in peaks: res <- dropFilledChromPeaks(res) ## Perform the peak filling with modified settings: allow expansion of the ## mz range by a specified ppm and expanding the mz range by mz width/2 prm <- FillChromPeaksParam(ppm = 40, expandMz = 0.5) res <- fillChromPeaks(res, param = prm) ## Did we get a signal for all missing peaks? sum(is.na(featureValues(res))) ## Still the same missing peaks.
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