peakDetectionCWT: The main function of peak detection by CWT based pattern...

In MassSpecWavelet: Mass spectrum processing by wavelet-based algorithms

Description

This function is a wrapper of cwt, getLocalMaximumCWT, getRidge, identifyMajorPeaks

Usage

peakDetectionCWT(ms, scales = c(1, seq(2, 30, 2), seq(32, 64, 4)), SNR.Th = 3, nearbyPeak = TRUE, peakScaleRange = 5, amp.Th = 0.01, minNoiseLevel = amp.Th/SNR.Th, ridgeLength = 24, peakThr=NULL, tuneIn = FALSE, ...)

Arguments

ms	the mass spectrometry spectrum
scales	scales of CWT
SNR.Th	SNR (Signal to Noise Ratio) threshold
nearbyPeak	Determine whether to include the nearby small peaks of major peaks. TRUE by default
peakScaleRange	the scale range of the peak. larger than 5 by default.
amp.Th	the minimum required relative amplitude of the peak (ratio to the maximum of CWT coefficients)
minNoiseLevel	the minimum noise level used in computing the SNR
ridgeLength	the minimum highest scale of the peak in 2-D CWT coefficient matrix
peakThr	Minimal absolute intensity (above the baseline) of peaks to be picked. If this value is provided, then the smoothing function sav.gol will be called to estimate the local intensity.(added based on the suggestion and code of Steffen Neumann)
tuneIn	determine whether to tune in the parameter estimation of the detected peaks
...	other parameters used by identifyMajorPeaks and smoothing function sav.gol

Value

majorPeakInfo	return of identifyMajorPeaks
ridgeList	return of getRidge
localMax	return of getLocalMaximumCWT
wCoefs	2-D CWT coefficient matrix, see cwt for details.

Author(s)

Pan Du, Simon Lin

References

Du, P., Kibbe, W.A. and Lin, S.M. (2006) Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching, Bioinformatics, 22, 2059-2065.

See Also

cwt, getLocalMaximumCWT, getRidge, identifyMajorPeaks

Examples

	data(exampleMS)
	SNR.Th <- 3
	peakInfo <- peakDetectionCWT(exampleMS, SNR.Th=SNR.Th)
	majorPeakInfo = peakInfo$majorPeakInfo
	peakIndex <- majorPeakInfo$peakIndex
	plotPeak(exampleMS, peakIndex, main=paste('Identified peaks with SNR >', SNR.Th)) 
	
	## In some cases, users may want to add peak filtering based on the absolute peak amplitude
	peakInfo <- peakDetectionCWT(exampleMS, SNR.Th=SNR.Th, peakThr=500)
	majorPeakInfo = peakInfo$majorPeakInfo
	peakIndex <- majorPeakInfo$peakIndex
	plotPeak(exampleMS, peakIndex, main=paste('Identified peaks with SNR >', SNR.Th)) 	

Example output

Loading required package: waveslim

waveslim: Wavelet Method for 1/2/3D Signals (version = 1.7.5)

MassSpecWavelet documentation built on Nov. 8, 2020, 5:36 p.m.