ggplot2 Version of plotChromPeakDensity()

Visualizes the density of chromatographic peaks along the retention time axis to help evaluate peak density correspondence analysis settings. This is a ggplot2 implementation of xcms's xcms::plotChromPeakDensity() function.

Usage

gplotChromPeakDensity(
  object,
  param,
  col = "#00000060",
  peakType = c("polygon", "point", "rectangle", "none"),
  peakCol = "#00000060",
  peakBg = "#00000020",
  peakPch = 1,
  simulate = TRUE,
  ...
)

# S4 method for class 'XChromatograms'
gplotChromPeakDensity(
  object,
  param,
  col = "#00000060",
  peakType = c("polygon", "point", "rectangle", "none"),
  peakCol = "#00000060",
  peakBg = "#00000020",
  peakPch = 1,
  simulate = TRUE,
  ...
)

Arguments

object

An XChromatograms object with detected chromatographic peaks.

param

A PeakDensityParam object defining the peak density correspondence parameters. If missing, the function will try to extract it from the object's process history (if correspondence has been performed).

col

Color for the chromatogram lines in the upper panel (default: "#00000060").

peakType

character(1) defining the type of peak annotation in upper panel: "polygon", "point", "rectangle", or "none" (default: "polygon").

peakCol

Color for peak markers (default: "#00000060").

peakBg

Background color for peak markers (default: "#00000020").

peakPch

Point character for peak markers when peakType = "point" (default: 1).

simulate

logical(1), whether to simulate correspondence analysis (TRUE) or display existing results (FALSE). Default: TRUE.

...

Additional arguments passed to plot() methods.

Value

A ggplot object with two panels:

• Upper panel: Chromatogram(s) with identified peaks

• Lower panel: Peak density along retention time axis showing individual peaks as points (y-axis = sample) with density estimate overlaid as a line. Grey rectangles indicate peaks grouped into features.

Details

The function creates a two-panel visualization:

• Upper panel shows the chromatographic data with detected peaks

• Lower panel shows each peak at its retention time (x-axis) and sample (y-axis)

• A kernel density estimate is shown as a line

• Grey rectangles indicate peaks that would be (simulate = TRUE) or have been (simulate = FALSE) grouped into features based on the peak density method

This visualization is particularly useful for optimizing PeakDensityParam settings, especially the bw (bandwidth) parameter which controls the smoothing of the density estimate.

Note: Currently only supports plotting a single row (m/z slice) across multiple samples. If object has multiple rows, please subset to one row first.

See also

xcms::plotChromPeakDensity() for the original xcms implementation

Author

Jan Stanstrup

Examples

library(xcmsVis)
library(xcms)
library(faahKO)
library(MsExperiment)
library(BiocParallel)

# Load example data
cdf_files <- dir(system.file("cdf", package = "faahKO"),
                 recursive = TRUE, full.names = TRUE)[1:3]

# Create XcmsExperiment and perform peak detection
xdata <- readMsExperiment(spectraFiles = cdf_files, BPPARAM = SerialParam())
cwp <- CentWaveParam(peakwidth = c(20, 80), ppm = 25)
xdata <- findChromPeaks(xdata, param = cwp, BPPARAM = SerialParam())

# Extract chromatogram for a specific m/z range
chr <- chromatogram(xdata, mz = c(305.05, 305.15))
#> Extracting chromatographic data
#> Processing chromatographic peaks

# Visualize peak density with default settings
prm <- PeakDensityParam(sampleGroups = rep(1, 3), bw = 30)
gplotChromPeakDensity(chr, param = prm)
#> Warning: Ignoring unknown aesthetics: text
#> Warning: Removed 240 rows containing missing values or values outside the scale range
#> (`geom_line()`).


# Try different bandwidth to see effect on peak grouping
prm2 <- PeakDensityParam(sampleGroups = rep(1, 3), bw = 60)
gplotChromPeakDensity(chr, param = prm2)
#> Warning: Ignoring unknown aesthetics: text
#> Warning: Removed 240 rows containing missing values or values outside the scale range
#> (`geom_line()`).