findPeaks.matchedFilter-methods: Feature detection in the chromatographic time domain

In benjiec/xcms: LC/MS and GC/MS Data Analysis

Description

Find peaks in extracted the chromatographic time domain of the profile matrix.

Arguments

object	xcmsRaw object
fwhm	full width at half maximum of matched filtration gaussian model peak. Only used to calculate the actual sigma, see below.
sigma	standard deviation (width) of matched filtration model peak
max	maximum number of peaks per extracted ion chromatogram
snthresh	signal to noise ratio cutoff
step	step size to use for profile generation
steps	number of steps to merge prior to filtration
mzdiff	minimum difference in m/z for peaks with overlapping retention times
index	return indicies instead of values for m/z and retention times
sleep	number of seconds to pause between plotting peak finding cycles
scanrange	scan range to process

Value

A matrix with columns:

mz	weighted (by intensity) mean of peak m/z across scans
mzmin	m/z of minimum step
mzmax	m/z of maximum step
rt	retention time of peak midpoint
rtmin	leading edge of peak retention time
rtmax	trailing edge of peak retention time
into	integrated area of original (raw) peak
intf	integrated area of filtered peak
maxo	maximum intensity of original (raw) peak
maxf	maximum intensity of filtered peak
i	rank of peak identified in merged EIC (<= max)
sn	signal to noise ratio of the peak

Methods

object = "xcmsRaw"

findPeaks.matchedFilter(object, fwhm = 30, sigma = fwhm/2.3548, max = 5, snthresh = 10, step = 0.1, steps = 2, mzdiff = 0.8 - step*steps, index = FALSE, sleep = 0, scanrange= numeric())

Author(s)

Colin A. Smith, [e-mail]

See Also

findPeaks-methods xcmsRaw-class

benjiec/xcms documentation built on May 12, 2019, 11:57 a.m.