peakBin-methods {Cardinal}R Documentation

Peak bin an imaging dataset

Description

Apply peak binning to a mass spectrometry imaging dataset.

Usage

## S4 method for signature 'MSImagingExperiment,numeric'
peakBin(object, ref, type=c("height", "area"),
        tolerance = 200, units = c("ppm", "mz"), ...)

## S4 method for signature 'MSImagingExperiment,missing'
peakBin(object, type=c("height", "area"),
        tolerance = 200, units = c("ppm", "mz"), ...)

Arguments

object

An imaging dataset.

ref

A reference to which the peaks are binned.

type

Should the summarized intensity of the peak by the maximum height of the peak or the area under the curve?

tolerance

The tolerance to be used when matching the m/z features in the dataset to the reference.

units

The units to use for the tolerance.

...

Ignored.

Details

Peak binning is performed by first matching the m/z-values in the dataset to those in the reference, and then finding the boundaries of the peak by detecting the nearest local minima. Then either the maximum height or the area under the curve of the peak are returned.

Internally, pixelApply is used to apply the binning. See its documentation page for more details.

Value

An object of the same class with the binned peaks.

Author(s)

Kylie A. Bemis

See Also

MSImagingExperiment, peakPick, peakAlign, peakFilter, reduceDimension, pixelApply, process

Examples

register(SerialParam())

set.seed(2)
data <- simulateImage(preset=1, npeaks=10, dim=c(3,3))
data <- data[,pData(data)$circle]
ref <- mz(metadata(data)$design$featureData)

# queue peak binning
data <- peakBin(data, ref=ref, type="height")

# apply peak binning
data_peaks <- process(data, plot=interactive())

[Package Cardinal version 2.2.3 Index]