findPeaks-methods: Feature detection for GC/MS and LC/MS Data - methods

In xiaodfeng/DynamicXCMS: LC-MS and GC-MS Data Analysis

Feature detection for GC/MS and LC/MS Data - methods

Description

A number of peak pickers exist in XCMS. findPeaks is the generic method.

Arguments

object	xcmsRaw-class object
method	Method to use for peak detection. See details.
...	Optional arguments to be passed along

Details

Different algorithms can be used by specifying them with the method argument. For example to use the matched filter approach described by Smith et al (2006) one would use: findPeaks(object, method="matchedFilter"). This is also the default.

Further arguments given by ... are passed through to the function implementing the method.

A character vector of nicknames for the algorithms available is returned by getOption("BioC")$xcms$findPeaks.methods. If the nickname of a method is called "centWave", the help page for that specific method can be accessed with ?findPeaks.centWave.

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
maxo	maximum intensity of original (raw) peak

and additional columns depending on the choosen method.

Methods

object = "xcmsRaw"

findPeaks(object, ...)

See Also

findPeaks.matchedFilter findPeaks.centWave findPeaks.addPredictedIsotopeFeatures findPeaks.centWaveWithPredictedIsotopeROIs xcmsRaw-class

xiaodfeng/DynamicXCMS documentation built on Aug. 6, 2023, 3:02 p.m.