plotChrom-peaksDataset-method: Plotting functions for GCMS data objects

In rromoli/flagme: Analysis of Metabolomics GC/MS Data

Plotting functions for GCMS data objects

Description

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

Usage

## S4 method for signature 'peaksDataset'
plotChrom(
  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,
  ...
)

Arguments

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

Details

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.

Value

plot the chromatograms

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

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
plotChrom(pd, rtrange = c(7.5,8.5), plotPeaks = TRUE,
          plotPeakLabels = TRUE)

rromoli/flagme documentation built on Feb. 10, 2023, 12:59 a.m.