group.mzClust: Group Peaks via High Resolution Alignment

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

Group Peaks via High Resolution Alignment

Description

Runs high resolution alignment on single spectra samples stored in a given xcmsSet.

Arguments

object	a xcmsSet with peaks
mzppm	the relative error used for clustering/grouping in ppm (parts per million)
mzabs	the absolute error used for clustering/grouping
minsamp	set the minimum number of samples in one bin
minfrac	set the minimum fraction of each class in one bin

Value

Returns a xcmsSet with slots groups and groupindex set.

Methods

object = "xcmsSet"

group(object, method="mzClust", mzppm = 20, mzabs = 0, minsamp = 1, minfrac=0)

References

Saira A. Kazmi, Samiran Ghosh, Dong-Guk Shin, Dennis W. Hill and David F. Grant
Alignment of high resolution mass spectra: development of a heuristic approach for metabolomics.
Metabolomics, Vol. 2, No. 2, 75-83 (2006)

See Also

xcmsSet-class,

Examples

## Not run: 
library(msdata)
mzdatapath <- system.file("fticr", package = "msdata")
mzdatafiles <- list.files(mzdatapath, recursive = TRUE, full.names = TRUE)

xs <- xcmsSet(method="MSW", files=mzdatafiles, scales=c(1,7),
              SNR.method='data.mean' , winSize.noise=500,
              peakThr=80000,  amp.Th=0.005)

xsg <- group(xs, method="mzClust")

## End(Not run)

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