detectPeaks-methods function

Detects peaks in a MassSpectrum object.

This method looks for peaks in mass spectrometry data (represented by a MassSpectrum object).

A peak is a local maximum above a user defined noise threshold. methods

## S4 method for signature 'MassSpectrum'
detectPeaks(object,
  halfWindowSize=20, method=c("MAD", "SuperSmoother"), SNR=2,
  ...)
## S4 method for signature 'list'
detectPeaks(object, ...)

Arguments

• object: MassSpectrum object or a list of MassSpectrum objects.

• halfWindowSize: numeric, half window size.

  The resulting window reaches from mass[currentIndex-halfWindowSize]

  to mass[currentIndex+halfWindowSize]. A local maximum have to be the highest one in the given window to be recognized as peak.

• method: a noise estimation function; see estimateNoise,MassSpectrum-method.

• SNR: single numeric value. SNR is an abbreviation for signal-to-noise-ratio. A local maximum has to be higher than SNR*noise to be recognize as peak.

• ...: arguments to be passed to estimateNoise,MassSpectrum-method. If object is a list mc.cores is also supported.

Returns

Returns a MassPeaks object.

Author(s)

Sebastian Gibb mail@sebastiangibb.de

See Also

MassPeaks, MassSpectrum, estimateNoise,MassSpectrum-method

demo("peaks")

Website: https://strimmerlab.github.io/software/maldiquant/

Examples

## load package
library("MALDIquant")

## load example data
data("fiedler2009subset", package="MALDIquant")

## choose only the first mass spectrum
s <- fiedler2009subset[[1]]

## transform intensities
s <- transformIntensity(s, method="sqrt")

## smoothing spectrum
s <- smoothIntensity(s, method="MovingAverage")

## remove baseline
s <- removeBaseline(s)

## plot spectrum
plot(s)

## call peak detection
p <- detectPeaks(s)

## draw peaks on the plot
points(p)

## label 10 highest peaks
top10 <- intensity(p) %in% sort(intensity(p), decreasing=TRUE)[1:10]
labelPeaks(p, index=top10)