Heatmap of xcms feature intensities — plot_xcms_features

Draws xcms::featureValues() as a ComplexHeatmap: rows are features ordered by rtmed, columns are samples ordered by injection time. Cells are log10 peak intensity (maxo by default); missing peaks stay NA and are shown in na_col. A left color bar encodes retention time; a top bar encodes sample.type (or group) and injection order.

export peaks data by xcms::chromPeaks and plot by ggplot2

Visualizes the distribution of detected features in a 2D space of retention time (x-axis) vs m/z (y-axis). Point size represents peak width, color represents log10 intensity. Includes peak detection parameters in subtitle.

extract Chromatogram from xcms according to feature's mz range and plot

plot scans number of MS1 levels in each peak, note that to many peaks will lead to stuck, apply filterFile to decrease peaks count

Dot-plot MS1 scan frequency along retention time. Scans are counted in successive rt_window-wide RT bins (per file); frequency is scan_count / rt_window.

Visualizes the number of MS2 scans that overlap each chromatographic peak based on retention time and m/z ranges. Produces a scatter plot with jitter, violin distribution, and counts of peaks with 0-5 MS2 scans.

extract EIC according to peaks' mzrange and rtrange, note that if multiple sample in xcms object, only first sample will be extracted

plot feature's intensity, ordered by Biobase::pData(xcms.xcms)$analysis.time.positive or Biobase::pData(xcms.xcms)$analysis.time.negative

Plot MS1 total ion chromatograms (TIC) for an XCMSnExp object, colored by sample group from Biobase::pData(xcms.xcms)$group.

Diagnostic and overview plots for xcms peaks, features, chromatograms, and TIC/XIC.

Usage

plot_xcms_features_heatmap(
  xcms,
  value = "maxo",
  log = TRUE,
  na_col = "#BDBDBD"
)

plot_xcms_peaks_distribution(
  xcms.xcms,
  plot.title = "Peaks distribution",
  type = "o"
)

plot_xcms_features_distribution(
  xcms.xcms,
  plot.title = "Features distribution"
)

plot_xcms_feature_chromatogram(xcms.xcms, feature.id, sampleNames = NULL)

plot_xcms_peaks_ms1_scans(xcms.xcms, plot.title = "Peaks Sans of MS1")

plot_xcms_ms1_scan_freq(xcms, rt_window = 5, plot.title = "MS1 Scan Frequency")

plot_xcms_peaks_ms2_scans(xcms.xcms, plot.title = "Peaks Sans of MS2")

plot_xcms_peaks_Chromatogram(xcms.xcms, peak_id, rt = "expand")

plot_xcms_feature_intensity(xcms.xcms, feature_id_to_show)

plot_xcms_TIC(xcms.xcms, col.group = NULL, title = "TIC")

plot_xcms_xic(
  xcms.filt,
  mzr = NULL,
  rtr = NULL,
  title = NULL,
  subtitle = NULL,
  base_size = 6,
  return.data = FALSE
)

Arguments

xcms: XCMSnExp / XcmsExperiment object
value: Intensity column passed to xcms::featureValues() (default "maxo").
log: Logical; log10-transform intensities (default TRUE). Non-finite values become NA.
na_col: Color for missing peaks (default "#BDBDBD").
xcms.xcms: XCMSnExp object
plot.title: Character title for the plot (default "Peaks Sans of MS2").
type: "o", for geom_point, "l", for geom_segment
feature.id: feature id
sampleNames: sample names to include
rt_window: positive numeric; RT window width (same unit as retention time, typically seconds)
peak_id: peak id
rt: expansion range for rt
feature_id_to_show: feature id to plot
col.group: named character vector of colors for groups. If NULL, Blank/QC use fixed colors and remaining groups use ggsci::pal_aaas() (or an interpolated palette when there are more than 10 groups)
title: Optional plot title.
xcms.filt: XCMSnExp after filterRt() and filterMz().
mzr: Optional m/z range used for extraction (for axis limits).
rtr: Optional RT range used for extraction (for axis limits).
subtitle: Optional subtitle.
base_size: Base font size.
return.data: If TRUE, return a list with plot, p_chr, p_mz, chrom, and points.

Value

(Invisibly) a ComplexHeatmap::Heatmap object.

ggplot object

ggplot object.

ggplot object

ggplot object.

ggplot object

A patchwork object with two panels, or a list when return.data = TRUE.

Details

Injection order uses pData$analysis.time.positive (positive polarity) or analysis.time.negative (negative), falling back to analysis.time, then ExpTime, then the current sample order.

Functions

plot_xcms_features_heatmap(): feature x sample intensity heatmap
plot_xcms_peaks_distribution(): plot peaks distribution
plot_xcms_features_distribution(): plot features distribution
plot_xcms_feature_chromatogram(): plot feature chromatogram
plot_xcms_peaks_ms1_scans(): plot MS1 scan counts for peaks
plot_xcms_ms1_scan_freq(): plot MS1 scan frequency vs RT
plot_xcms_peaks_ms2_scans(): plot MS2 scan counts for peaks
plot_xcms_peaks_Chromatogram(): plot chromatogram for a peak
plot_xcms_feature_intensity(): plot feature intensity
plot_xcms_TIC(): plot TIC
plot_xcms_xic(): ggplot2 XIC plot matching xcms plot(type = \"XIC\")

Upper panel: extracted ion chromatogram (intensity vs retention time). Lower panel: m/z vs retention time with points coloured by intensity.