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 a feature EIC via get_xcms_feature_chromatogram and plot it.

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. Y-axis tick labels use scientific notation (e.g. $9 \times 10^{7}$).

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), extracted with get_xcms_chromatogram (aggregationFun = "sum"). Lower panel: m/z vs retention time with points coloured by intensity.