plotImage: Plot of images of GCMS data

Description

Image plots (i.e. 2D heatmaps) of raw GCMS profile data

Usage

plotImage(object,run=1,rtrange=c(11,13),main=NULL,mzrange=c(50,200),SCALE=log2,...)

Arguments

object

a peaksDataset object

run

index of the run to plot an image for

rtrange

vector of length 2 giving start and end of the X-axis (retention time)

main

main title (auto-constructed if not specified)

mzrange

vector of length 2 giving start and end of the Y-axis (mass-to-charge ratio)

SCALE

function called to scale the data (default: log2)

...

further arguments passed to the image command

Details

For peakDataset objects, each TIC is scale to the maximum value (as specified by the how.near and max.near values). The many parameters gives considerable flexibility of how the TICs can be visualized.

For peakAlignment objects, the similarity matrix is plotted and optionally, the set of matching peaks. clusterAlignment objects are just a collection of all pairwise peakAlignment objects.

References

Mark D Robinson (2008). Methods for the analysis of gas chromatography - mass spectrometry data PhD dissertation University of Melbourne.

Examples

Run this code

require(gcspikelite)

# paths and files
gcmsPath<-paste(find.package("gcspikelite"),"data",sep="/")
cdfFiles<-dir(gcmsPath,"CDF",full=TRUE)
eluFiles<-dir(gcmsPath,"ELU",full=TRUE)

# read data
pd<-peaksDataset(cdfFiles[1],mz=seq(50,550),rtrange=c(7.5,8.5))

# image plot
plotImage(pd,run=1,rtrange=c(7.5,8.5),main="")