groupChromPeaks-nearest: Peak grouping based on proximity in the mz-rt space

Description Usage Arguments Value Slots Note References See Also Examples

Description

This method is inspired by the grouping algorithm of mzMine (Katajamaa 2006) and performs correspondence based on proximity of peaks in the space spanned by retention time and mz values. The method creates first a master peak list consisting of all chromatographic peaks from the sample in which most peaks were identified, and starting from that, calculates distances to peaks from the sample with the next most number of peaks. If peaks are closer than the defined threshold they are grouped together.

The NearestPeaksParam class allows to specify all settings for the peak grouping based on the nearest algorithm. Instances should be created with the NearestPeaksParam constructor.

sampleGroups,sampleGroups<-: getter and setter for the sampleGroups slot of the object.

mzVsRtBalance,mzVsRtBalance<-: getter and setter for the mzVsRtBalance slot of the object.

absMz,absMz<-: getter and setter for the absMz slot of the object.

absRt,absRt<-: getter and setter for the absRt slot of the object.

kNN,kNN<-: getter and setter for the kNN slot of the object.

groupChromPeaks,XCMSnExp,NearestPeaksParam: performs peak grouping based on the proximity between chromatographic peaks from different samples in the mz-rt range.

The correspondence analysis can be performed on chromatographic peaks of any MS level (if present and if chromatographic peak detection has been performed for that MS level) defining features combining these peaks. The MS level can be selected with the parameter msLevel. By default, calling groupChromPeaks will remove any previous correspondence results. This can be disabled with add = TRUE, which will add newly defined features to already present feature definitions.

Usage

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NearestPeaksParam(
  sampleGroups = numeric(),
  mzVsRtBalance = 10,
  absMz = 0.2,
  absRt = 15,
  kNN = 10
)

## S4 method for signature 'NearestPeaksParam'
show(object)

## S4 method for signature 'NearestPeaksParam'
sampleGroups(object)

## S4 replacement method for signature 'NearestPeaksParam'
sampleGroups(object) <- value

## S4 method for signature 'NearestPeaksParam'
mzVsRtBalance(object)

## S4 replacement method for signature 'NearestPeaksParam'
mzVsRtBalance(object) <- value

## S4 method for signature 'NearestPeaksParam'
absMz(object)

## S4 replacement method for signature 'NearestPeaksParam'
absMz(object) <- value

## S4 method for signature 'NearestPeaksParam'
absRt(object)

## S4 replacement method for signature 'NearestPeaksParam'
absRt(object) <- value

## S4 method for signature 'NearestPeaksParam'
kNN(object)

## S4 replacement method for signature 'NearestPeaksParam'
kNN(object) <- value

## S4 method for signature 'XCMSnExp,NearestPeaksParam'
groupChromPeaks(object, param, msLevel = 1L, add = FALSE)

Arguments

sampleGroups

A vector of the same length than samples defining the sample group assignments (i.e. which samples belong to which sample group). This parameter is mandatory for the PeakDensityParam and has to be provided also if there is no sample grouping in the experiment (in which case all samples should be assigned to the same group).

mzVsRtBalance

numeric(1) representing the factor by which mz values are multiplied before calculating the (euclician) distance between two peaks.

absMz

numeric(1) maximum tolerated distance for mz values.

absRt

numeric(1) maximum tolerated distance for rt values.

kNN

numeric(1) representing the number of nearest neighbors to check.

object

For groupChromPeaks: an XCMSnExp object containing the results from a previous chromatographic peak detection analysis (see findChromPeaks()).

For all other methods: a `NearestPeaksParam` object.
value

The value for the slot.

param

A PeakDensityParam object containing all settings for the peak grouping algorithm.

msLevel

integer(1) defining the MS level. Currently only MS level 1 is supported.

add

logical(1) (default add = FALSE) allowing to perform an additional round of correspondence (e.g. on a different MS level) and add features to the already present feature definitions.

Value

The NearestPeaksParam function returns a NearestPeaksParam class instance with all of the settings specified for peak alignment based on peak proximity.

For groupChromPeaks: a XCMSnExp object with the results of the peak grouping/correspondence step (i.e. the mz-rt features). These can be accessed with the featureDefinitions() method.

Slots

.__classVersion__,sampleGroups,mzVsRtBalance,absMz,absRt,kNN

See corresponding parameter above. .__classVersion__ stores the version from the class. Slots values should exclusively be accessed via the corresponding getter and setter methods listed above.

Note

These methods and classes are part of the updated and modernized xcms user interface. All of the settings to the algorithm can be passed with a NearestPeaksParam object.

References

Katajamaa M, Miettinen J, Oresic M: MZmine: Toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics 2006, 22:634-636.

See Also

The do_groupChromPeaks_nearest() core API function.

featureDefinitions() and featureValues() for methods to access peak grouping results (i.e. the features).

XCMSnExp for the object containing the results of the peak grouping.

Other peak grouping methods: groupChromPeaks-density, groupChromPeaks-mzClust, groupChromPeaks()

Examples

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## Create a NearestPeaksParam object
p <- NearestPeaksParam(kNN = 3)
p

## Load a test data set with detected peaks
data(faahko_sub)
## Update the path to the files for the local system
dirname(faahko_sub) <- system.file("cdf/KO", package = "faahKO")
res <- faahko_sub

## Disable parallel processing for this example
register(SerialParam())

head(chromPeaks(res))
## The number of peaks identified per sample:
table(chromPeaks(res)[, "sample"])

## Performing the peak grouping
p <- NearestPeaksParam()
res <- groupChromPeaks(res, param = p)

## The results from the peak grouping:
featureDefinitions(res)

## Using the featureValues method to extract a matrix with the intensities of
## the features per sample.
head(featureValues(res, value = "into"))

## The process history:
processHistory(res)

xcms documentation built on Nov. 8, 2020, 5:13 p.m.