cosmiq (version 1.6.0)

peakdetection: An algorithm for the detection of peak locations and boundaries in mass spectra or ion chromatograms

Description

peakdetection uses Continuous wavelet transformation (CWT) to determine optimal peak location. A modified algorithm of Du et al. (2006) is used to localize peak positions.

Usage

peakdetection(scales, y, x, SNR.Th, SNR.area, mintr)

Arguments

scales

vector with the scales to perform CWT

y

vector of ion intensities

x

vector of mz bins

SNR.Th

Signal-to-noise threshold

SNR.area

Window size for noise estimation

mintr

Minimal peak width intensity treshold (in percentage), for which two overlapping peaks are considered as separated. default is set to 0.5.

Details

A peak detection algorithm based on continuous wavelet transformation (CWT) is used for this step (modified from Du et al., 2006). Peak detection based on CWT has the advantage that a sliding scale of wavelets instead of a single filter function with fixed wavelength is used. This allows for a flexible and automatic approximation of the peak width. As a result it is possible to locate both narrow and broad peaks within a given dynamic range.

References

Du, P., Kibbe, W. A., & Lin, S. M. (2006). Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching. Bioinformatics, 22(17), 2059-2065. doi:10.1093/bioinformatics/btl355

Examples

    
cdfpath <- file.path(find.package("faahKO"), "cdf")

my.input.files <- dir(c(paste(cdfpath, "WT", sep='/'),
    paste(cdfpath, "KO", sep='/')), full.names=TRUE)


# create xcmsSet object
xs <- new("xcmsSet")
xs@filepaths <- my.input.files

op<-par(mfrow=c(3,1))

x<-combine_spectra(xs=xs, mzbin=0.25,
    linear=TRUE, continuum=FALSE)

plot(x$mz, x$intensity, 
    type='h', 
    main='original',
    xlab='m/Z', ylab='ion intensity')

xy <- peakdetection(x=x$mz, y=x$intensity,
    scales=1:10, SNR.Th=1.0, SNR.area=20, mintr=0.5)

id.peakcenter<-xy[,4]

plot(x$mz[id.peakcenter], x$intensity[id.peakcenter], type='h', 
    main='filtered')


plot(x$mz, x$intensity, type='l',
    xlim=c(400,450),
    main='zoom',
    log='y',
    xlab='m/Z', ylab='ion intensity (log scale)')

points(x$mz[id.peakcenter], x$intensity[id.peakcenter],col='red', type='h')