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3D-Dimensional reduction plot for cell classification visualization.

Source: R/CellDimPlot.R
CellDimPlot3D.Rd

Plotting cell points on a reduced 3D space and coloring according to the groups of the cells.

Usage

CellDimPlot3D(
  srt,
  group.by,
  plot_type = c("scatter", "density_surface"),
  reduction = NULL,
  dims = c(1, 2, 3),
  axis_labs = NULL,
  palette = "Chinese",
  palcolor = NULL,
  bg_color = "grey80",
  pt.size = 1.5,
  cells.highlight = NULL,
  cols.highlight = "black",
  shape.highlight = "circle-open",
  sizes.highlight = 2,
  lineages = NULL,
  lineages_palette = "Dark2",
  density_n = 200,
  density_bandwidth = 1,
  density_threshold = 0.018,
  density_power = 0.52,
  density_colors = c("#ffffff", "#edf9fa", "#c7e6ed", "#7faac2", "#294a74", "#11162f",
    "#7f1025", "#ef3b2c"),
  density_color_stops = c(0, 0.02, 0.12, 0.35, 0.62, 0.82, 0.93, 1),
  density_surface_opacity = 0.78,
  density_label = FALSE,
  density_label_color = TRUE,
  density_label_top_n = Inf,
  density_label_min_distance = 0.08,
  density_show_axes = TRUE,
  density_show_colorbar = TRUE,
  density_show_title = TRUE,
  span = 0.75,
  width = NULL,
  height = NULL,
  save = NULL,
  force = FALSE,
  verbose = TRUE
)

Arguments

srt

A Seurat object.

group.by

Name of one or more meta.data columns to group (color) cells by.

plot_type

Plot type. "scatter" keeps the original 3D cell scatter, while "density_surface" draws an interactive 3D kernel-density surface from the first two requested dimensions.

reduction

Which dimensionality reduction to use. If not specified, will use the reduction returned by DefaultReduction.

dims

Dimensions to plot. For plot_type = "scatter", this must be a three-length numeric vector specifying x-, y- and z-dimensions. For plot_type = "density_surface", the first two dimensions are used as x and y, and density is drawn on the z-axis.

axis_labs

A character vector of length 3 indicating the labels for the axes.

palette

Color palette name. Available palettes can be found in thisplot::show_palettes. Default is "Chinese".

palcolor

Custom colors used to create a color palette. Default is NULL.

bg_color

Color value for background(NA) points.

pt.size

The size of the points in the plot.

cells.highlight

A logical or character vector specifying the cells to highlight in the plot. If TRUE, all cells are highlighted. If FALSE, no cells are highlighted. Default is NULL.

cols.highlight

Color used to highlight the cells.

shape.highlight

Shape of the cell to highlight. See scattergl-marker-symbol

sizes.highlight

Size of highlighted cell points.

lineages

Lineages/pseudotime to add to the plot. If specified, curves will be fitted using stats::loess method.

lineages_palette

Color palette used for lineages.

density_n

Grid size used by MASS::kde2d() for plot_type = "density_surface".

density_bandwidth

Bandwidth passed to MASS::kde2d(). A single value scales the default x and y bandwidth; a two-length vector supplies absolute x and y bandwidths.

density_threshold

Relative density values below this cutoff are removed from the surface.

density_power

Power transform applied to relative density before plotting. Values below 1 broaden peaks.

density_colors

Colors used for the density surface. The last colors are reserved for the highest density peaks.

density_color_stops

Numeric stops between 0 and 1 for density_colors. By default, red is reserved for the highest density peaks.

density_surface_opacity

Opacity for density surfaces.

density_label

Whether to add group labels to the density surface.

density_label_color

Whether group labels use the same palette as CellDimPlot().

density_label_top_n

Maximum number of group labels to draw.

density_label_min_distance

Minimum distance between labels in the x-y embedding space, expressed as a fraction of the larger embedding range.

density_show_axes, density_show_colorbar, density_show_title

Whether to show axes, colorbar, and title for plot_type = "density_surface".

span

The span of the loess smoother for lineages line.

width

Width in pixels, defaults to automatic sizing.

height

Height in pixels, defaults to automatic sizing.

save

The name of the file to save the plot to. Must end in ".html".

force

Whether to force drawing regardless of maximum levels in any cell group is greater than 100. Default is FALSE.

verbose

Whether to print the message. Default is TRUE.

See also

CellDimPlot, FeatureDimPlot3D

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(
  pancreas_sub,
  nonlinear_reduction_dims = 3
)
#> ℹ [2026-07-02 08:28:35] Start standard processing workflow...
#> ℹ [2026-07-02 08:28:35] Checking a list of <Seurat>...
#> ! [2026-07-02 08:28:35] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-07-02 08:28:35] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-07-02 08:28:36] Perform `FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-07-02 08:28:36] Use the separate HVF from `srt_list`
#> ℹ [2026-07-02 08:28:36] Number of available HVF: 2000
#> ℹ [2026-07-02 08:28:36] Finished check
#> ℹ [2026-07-02 08:28:36] Perform `ScaleData()`
#> ℹ [2026-07-02 08:28:36] Perform pca linear dimension reduction
#> ℹ [2026-07-02 08:28:37] Use stored estimated dimensions 1:23 for Standardpca
#> ℹ [2026-07-02 08:28:37] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-07-02 08:28:37] Reorder clusters...
#> ℹ [2026-07-02 08:28:37] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-07-02 08:28:37] Perform umap nonlinear dimension reduction
#> ℹ [2026-07-02 08:28:37] Perform umap nonlinear dimension reduction using Standardpca (1:23)
#> ✔ [2026-07-02 08:28:40] Standard processing workflow completed
CellDimPlot3D(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "StandardpcaUMAP3D"
)



CellDimPlot3D(
 pancreas_sub,
 group.by = "SubCellType",
 plot_type = "density_surface",
 reduction = "umap",
 dims = c(1, 2),
 density_label = TRUE
)



pancreas_sub <- RunSlingshot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "StandardpcaUMAP3D",
  show_plot = FALSE
)
CellDimPlot3D(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "StandardpcaUMAP3D",
  lineages = "Lineage1"
)