MSnbase (version 1.20.7)

pickPeaks-methods: Peak Detection for 'MSnExp' or 'Spectrum' instances

Description

This method performs a peak picking on individual spectra (Spectrum instances) or whole experiments (MSnExp instances) to create centroided spectra. For noisy spectra there are currently two different noise estimators, the Median Absolute Deviation (method = "MAD") and Friedman's Super Smoother (method = "SuperSmoother"), as implemented in the MALDIquant::detectPeaks and MALDIquant::estimateNoise functions respectively.

Methods

signature(x = "MSnExp", halfWindowSize = "integer", method = "character", SNR = "numeric", verbose = "logical", ...)

Performs the peak picking for all spectra in an MSnExp instance. method could be "MAD" or "SuperSmoother". halfWindowSize controls the window size of the peak picking algorithm. The resulting window size is 2 * halfWindowSize + 1. The size should be nearly (or slightly larger) the FWHM (full width at half maximum). A local maximum is considered as peak if its intensity is SNR times larger than the estimated noise. The arguments ... are passed to the noise estimator functions. Currenlty only the method = "SuperSmoother" accepts additional arguments, e.g. span. Please see supsmu for details. This method displays a progress bar if verbose = TRUE. Returns an MSnExp instance with centroided spectra.

signature(x = "Spectrum", method = "character", halfWindowSize = "integer", ...)

Performs the peak picking for the spectrum (Spectrum instance). This method is the same as above but returns a centroided Spectrum instead of an MSnExp object. It has no verbose argument. Please read the details for the above MSnExp method.

References

S. Gibb and K. Strimmer. 2012. MALDIquant: a versatile R package for the analysis of mass spectrometry data. Bioinformatics 28: 2270-2271. http://strimmerlab.org/software/maldiquant/

See Also

clean, removePeaks smooth, estimateNoise and trimMz for other spectra processing methods.

Examples

sp1 <- new("Spectrum1",
           intensity = c(1:6, 5:1),
           mz = 1:11)
sp2 <- pickPeaks(sp1)
intensity(sp2)

data(itraqdata)
itraqdata2 <- pickPeaks(itraqdata)
processingData(itraqdata2)