plot.peaksDataset {flagme}R Documentation

Plotting functions for GCMS data objects

Description

Store the raw data and optionally, information regarding signal peaks for a number of GCMS runs

Usage

.plotpD(object,runs=1:length(object@rawdata),mzind=1:nrow(object@rawdata[[1]]),
               mind=NULL,plotSampleLabels=TRUE,calcGlobalMax=FALSE,peakCex = 0.8,plotPeaks=TRUE,
                           plotPeakBoundaries=FALSE,plotPeakLabels=FALSE,plotMergedPeakLabels=TRUE,mlwd=3,
                           usePeaks=TRUE,plotAcrossRuns=FALSE,overlap=F,rtrange=NULL,cols=NULL,thin=1,
                           max.near=median(object@rawrt[[1]]),how.near=50,scale.up=1,...)
                           
.plotpA(object,xlab="Peaks - run 1",ylab="Peaks - run 2",plotMatches=TRUE,matchPch=19,matchLwd=3,
               matchCex=.5,matchCol="black",col=colorpanel(50,"black","blue","white"),
                           breaks=seq(0,1,length=51),...)
                           
.plotcA(object,alignment=1,...)

Arguments

object a peaksDataset, peaksAlignment or clusterAlignment object.
runs for peaksDataset only: set of run indices to plot
mzind for peaksDataset only: set of mass-to-charge indices to sum over (default, all)
mind for peaksDataset only: matrix of aligned indices
plotSampleLabels for peaksDataset only: logical, whether to display sample labels
calcGlobalMax for peaksDataset only: logical, whether to calculate an overall maximum for scaling
peakCex character expansion factor for peak labels
plotPeaks for peaksDataset only: logical, whether to plot hashes for each peak
plotPeakBoundaries for peaksDataset only: logical, whether to display peak boundaries
plotPeakLabels for peaksDataset only: logical, whether to display peak labels
plotMergedPeakLabels for peaksDataset only: logical, whether to display 'merged' peak labels
mlwd for peaksDataset only: line width of lines indicating the alignment
usePeaks for peaksDataset only: logical, whether to plot alignment of peaks (otherwise, scans)
plotAcrossRuns for peaksDataset only: logical, whether to plot across peaks when unmatched peak is given
overlap for peaksDataset only: logical, whether to plot TIC/XICs overlapping
rtrange for peaksDataset only: vector of length 2 giving start and end of the X-axis
cols for peaksDataset only: vector of colours (same length as the length of runs)
thin for peaksDataset only: when usePeaks=FALSE, plot the alignment lines every thin values
max.near for peaksDataset only: where to look for maximum
how.near for peaksDataset only: how far away from max.near to look
scale.up for peaksDataset only: a constant factor to scale the TICs
plotMatches for peaksDataset only: logical, whether to plot matches
xlab for peaksAlignment and clusterAlignment only: x-axis label
ylab for peaksAlignment and clusterAlignment only: y-axis label
matchPch for peaksAlignment and clusterAlignment only: match plotting character
matchLwd for peaksAlignment and clusterAlignment only: match line width
matchCex for peaksAlignment and clusterAlignment only: match character expansion factor
matchCol for peaksAlignment and clusterAlignment only: match colour
col for peaksAlignment and clusterAlignment only: vector of colours for colourscale
breaks for peaksAlignment and clusterAlignment only: vector of breaks for colourscale
alignment for peaksAlignment and clusterAlignment only: the set of alignments to plot
... further arguments passed to the plot or 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.

Author(s)

Mark Robinson

References

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

See Also

plotImage, peaksDataset

Examples

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[1:3],mz=seq(50,550),rtrange=c(7.5,8.5))

# image plot
plot(pd,rtrange=c(7.5,8.5),plotPeaks=TRUE,plotPeakLabels=TRUE)

[Package flagme version 1.0.0 Index]