MSclassifR (version 0.5.0)

PlotSpectra: Plot spectral data with optional peak markers

Description

Create a ggplot of a mass spectrum with optional points for detected peaks and optional vertical lines (and points) highlighting user-specified m/z values.

Usage

PlotSpectra(
  SpectralData,
  absx = "ALL",
  Peaks = NULL,
  Peaks2 = NULL,
  col_spec = 1,
  col_peak = 2,
  shape_peak = 3,
  col_peak2 = 2,
  shape_peak2 = 2,
  tol = 0
)

Value

A ggplot object representing the spectrum and optional annotations.

Arguments

SpectralData

An object containing spectrum data with numeric slots @mass (m/z) and @intensity (signal). Typically a MALDIquant MassSpectrum-like S4 object.

absx

Either the string "ALL" to plot the full m/z range, or a numeric length-2 vector c(min, max) specifying the m/z window to display.

Peaks

Optional MassPeaks object (e.g., from MALDIquant) providing detected peak positions (@mass) and intensities (@intensity) to plot as points.

Peaks2

Optional numeric or character vector of m/z values to highlight. If character/factor, values are coerced to numeric (non-numeric chars removed). Vertical dashed lines are drawn at these m/z. If Peaks is also supplied, points are plotted for peaks whose m/z match Peaks2 (within tol).

col_spec

Colour for the spectrum line. Default: 1 (black).

col_peak

Colour for points corresponding to all peaks in Peaks. Default: 2 (red).

shape_peak

Point shape for Peaks points. Default: 3.

col_peak2

Colour for points corresponding to the subset of Peaks that match Peaks2. Default: 2 (red).

shape_peak2

Point shape for the Peaks2-matched points. Default: 2.

tol

Numeric tolerance (in m/z units) used to match Peaks@mass to Peaks2. Set to 0 for exact matching (may miss due to floating-point precision). Default: 0.

Examples

# \donttest{
if (requireNamespace("MALDIquant", quietly = TRUE)) {
# Load mass spectra
 data("CitrobacterRKIspectra", package = "MSclassifR")
# Plot raw mass spectrum
 PlotSpectra(SpectralData = CitrobacterRKIspectra[[1]])
# standard pre-processing of mass spectra
 spectra <- SignalProcessing(CitrobacterRKIspectra)
# Plot pre-processed mass spectrum
 PlotSpectra(SpectralData=spectra[[1]])
# detection of peaks in pre-processed mass spectra
 peaks <- PeakDetection(x = spectra, averageMassSpec=FALSE)
# Plot peaks on pre-processed mass spectrum
 PlotSpectra(SpectralData=spectra[[1]],Peaks=peaks[[1]],col_spec="blue",col_peak="black")
}
# }