plotSpectra: plotSpectra

In flagme: Analysis of Metabolomics GC/MS Data

Description

Plot the mass spectra from the profile matrix

Usage

plotSpectra(object, sample, spectraID, normalize = TRUE, ...)

Arguments

object	an object of class "peaksDataset" where to keep the mass spectra; both abundance (y) than m/z (x)
sample	character, the sample from were to plot the mass spectra
spectraID	numerical, a vector containing the index of the spectra to be plotted.
normalize	logical, if TRUE normalize the intensity of the mass peak to 100, the most abundant is 100 are scaled consequetially
...	other parameter passed to the plot() function

Details

Plot the deconvoluted mass spectra from the profile matrix

Author(s)

[e-mail]

Examples

gcmsPath <- paste(find.package("gcspikelite"), "data", sep="/")
cdfFiles <- dir(gcmsPath,"CDF", full=TRUE)
# read data, peak detection results
pd <- peaksDataset(cdfFiles[1:3], mz=seq(50,550), rtrange=c(7.5,10.5))
pd <- addXCMSPeaks(files=cdfFiles[1:3], object=pd, peakPicking=c('mF'),
                   snthresh=3, fwhm=10,  step=0.1, steps=2, mzdiff=0.5,
                   sleep=0)
## align two chromatogram
pA <- peaksAlignment(pd@peaksdata[[1]], pd@peaksdata[[2]],
                     pd@peaksrt[[1]], pd@peaksrt[[2]], D=50,
                     metric=3, compress=FALSE, type=2, penality=0.2)
pA@v$match
## plot the mass spectra
par(mfrow=c(2,1))
plotSpectra(object=pd, sample=cdfFiles[1], spectraID=10)
plotSpectra(object=pd, sample=cdfFiles[2], spectraID=12)

flagme documentation built on Nov. 8, 2020, 5:24 p.m.