Cell density plot

Feature density by group.

Usage

CellDensityPlot(
  srt,
  features,
  group.by = NULL,
  split.by = NULL,
  assay = NULL,
  layer = "data",
  flip = FALSE,
  reverse = FALSE,
  x_order = c("value", "rank"),
  decreasing = NULL,
  palette = "Chinese",
  palcolor = NULL,
  cells = NULL,
  keep_empty = FALSE,
  y.nbreaks = 4,
  y.min = NULL,
  y.max = NULL,
  same.y.lims = FALSE,
  aspect.ratio = NULL,
  title = NULL,
  subtitle = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  theme_use = "theme_scop",
  theme_args = list(),
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  force = FALSE,
  verbose = TRUE
)

Arguments

srt: A Seurat object.
features: Features to plot.
group.by: Metadata column(s) used to color cells.
split.by: Metadata column to facet by.
assay: Assay to use. NULL uses the default assay.
layer: Assay layer to use.
flip, reverse: Flip the x-axis or reverse the y-axis.
x_order: "value" or "rank".
decreasing: Order groups decreasingly.
palette, palcolor: Palette name (thisplot::show_palettes) or custom colors.
cells: Cell names to include. NULL uses all cells.
keep_empty: Keep empty groups.
y.nbreaks, y.min, y.max: Y-axis breaks and limits. NULL limits are automatic.
same.y.lims: Share y-axis limits across panels.
aspect.ratio: Panel aspect ratio.
title: Plot title. NULL hides the title for merged/single panels. When multiple lineages are plotted and title is NULL, each panel is titled with its lineage column.
subtitle: Plot subtitle.
legend.position: Legend placement ("none", "left", "right", "bottom", "top"), direction, and title. legend.title = NULL uses the group name.
legend.direction: Legend direction: "horizontal" or "vertical".
theme_use, theme_args: Theme name or function, plus extra theme arguments.
combine, nrow, ncol, byrow: Combine plots with patchwork. combine = FALSE returns a list of ggplots.
force: Draw even when there are more than 50 features.
verbose: Whether to print messages.

Examples

data(pancreas_sub)
pancreas_sub <- RunStandardWorkflow(pancreas_sub)
#> ℹ [2026-08-30 04:04:48] Start standard processing workflow...
#> ℹ [2026-08-30 04:04:48] Checking a list of <Seurat>...
#> ! [2026-08-30 04:04:48] Data 1/1 of the `srt_list` is "unknown"
#> Warning: Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-08-30 04:04:48] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-08-30 04:04:48] Perform `FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-08-30 04:04:49] Use the separate HVF from `srt_list`
#> ℹ [2026-08-30 04:04:49] Number of available HVF: 2000
#> ℹ [2026-08-30 04:04:49] Finished check
#> ℹ [2026-08-30 04:04:49] Perform `ScaleData()`
#> ℹ [2026-08-30 04:04:49] Perform pca linear dimension reduction
#> ℹ [2026-08-30 04:04:49] Use stored estimated dimensions 1:23 for Standardpca
#> ℹ [2026-08-30 04:04:50] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-08-30 04:04:50] Reorder clusters...
#> ℹ [2026-08-30 04:04:50] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-08-30 04:04:50] Perform umap nonlinear dimension reduction
#> ✔ [2026-08-30 04:04:55] Standard processing workflow completed
CellDensityPlot(
  pancreas_sub,
  features = "Sox9",
  group.by = "SubCellType"
)
#> Picking joint bandwidth of 0.209


pancreas_sub <- RunSlingshot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "UMAP"
)
#> Warning: Removed 7 rows containing missing values or values outside the scale range
#> (`geom_path()`).
#> Warning: Removed 7 rows containing missing values or values outside the scale range
#> (`geom_path()`).


CellDensityPlot(
  pancreas_sub,
  features = "Lineage1",
  group.by = "SubCellType",
  aspect.ratio = 1
)
#> Picking joint bandwidth of 0.459


CellDensityPlot(
  pancreas_sub,
  features = "Lineage1",
  group.by = "SubCellType",
  flip = TRUE
)
#> Picking joint bandwidth of 0.459

Usage

Arguments

See also

Examples