findPeaks.centWave-methods {xcms}R Documentation

Feature detection for high resolution LC/MS data

Description

Peak density and wavelet based feature detection for high resolution LC/MS data in centroid mode

Arguments

object xcmsSet object
ppm maxmial tolerated m/z deviation in consecutive scans, in ppm (parts per million)
peakwidth Chromatographic peak width, given as range (min,max) in seconds
snthresh signal to noise ratio cutoff, definition see below.
prefilter prefilter=c(k,I). Prefilter step for the first phase. Mass traces are only retained if they contain at least k peaks with intensity >= I.
integrate Integration method. If =1 peak limits are found through descent on the mexican hat filtered data, if =2 the descent is done on the real data. Method 2 is very accurate but prone to noise, while method 1 is more robust to noise but less exact.
mzdiff minimum difference in m/z for peaks with overlapping retention times, can be negative to allow overlap
fitgauss logical, if TRUE a Gaussian is fitted to each peak
scanrange scan range to process
sleep number of seconds to pause between plotting peak finding cycles
verbose.columns logical, if TRUE additional peak meta data columns are returned

Details

This algorithm is most suitable for high resolution LC/{TOF,OrbiTrap,FTICR}-MS data in centroid mode. In the first phase of the method mass traces (characterised as regions with less than ppm m/z deviation in consecutive scans) in the LC/MS map are located. In the second phase these mass traces are further analysed. Continuous wavelet transform (CWT) is used to locate chromatographic peaks on different scales.

Value

A matrix with columns:

mz weighted (by intensity) mean of peak m/z across scans
mzmin m/z peak minimum
mzmax m/z peak maximum
rt retention time of peak midpoint
rtmin leading edge of peak retention time
rtmax trailing edge of peak retention time
into integrated peak intensity
intb baseline corrected integrated peak intensity
maxo maximum peak intensity
sn Signal/Noise ratio, defined as (maxo - baseline)/sd, where
maxo is the maximum peak intensity,
baseline the estimated baseline value and
sd the standard deviation of local chromatographic noise.
egauss RMSE of Gaussian fit
if verbose.columns is TRUE additionally :
mu Gaussian parameter mu
sigma Gaussian parameter sigma
h Gaussian parameter h
f Region number of m/z ROI where the peak was localised
dppm m/z deviation of mass trace across scans in ppm
scale Scale on which the peak was localised
scpos Peak position found by wavelet analysis
scmin Left peak limit found by wavelet analysis (scan number)
scmax Right peak limit found by wavelet analysis (scan number)

Methods

object = "xcmsRaw"
findPeaks.centWave(object, ppm=25, peakwidth=c(20,50), snthresh=10, prefilter=c(3,100), integrate=1, mzdiff=-0.001, fitgauss=FALSE, scanrange= numeric(), sleep=0, verbose.columns=FALSE)

Author(s)

Ralf Tautenhahn, rtautenh@ipb-halle.de

See Also

findPeaks-methods xcmsRaw-class


[Package xcms version 1.14.1 Index]