Skip to contents

Cell density plot

Source: R/CellDensityPlot.R
CellDensityPlot.Rd

Plots the density of specified features in a single or multiple groups, grouped by specified variables.

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 = "Paired",
  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
)

Arguments

srt

A Seurat object.

features

A character vector of features to use.

group.by

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

split.by

Name of a column in meta.data column to split plot by. Default is NULL.

assay

Which assay to use. If NULL, the default assay of the Seurat object will be used.

layer

Which layer to use. Default is data.

flip

Whether to flip the x-axis. Default is FALSE.

reverse

Whether to reverse the y-axis. Default is FALSE.

x_order

A character specifying how to order the x-axis. Can be "value" or "rank". Default is "value".

decreasing

Whether to order the groups in decreasing order. Default is NULL.

palette

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

palcolor

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

cells

A character vector of cell names to use. Default is NULL, which means all cells are included.

keep_empty

Whether to keep empty groups. Default is FALSE.

y.nbreaks

A number of breaks on the y-axis. Default is 4.

y.min

A numeric specifying the minimum value on the y-axis. Default is NULL, which means the minimum value will be automatically determined.

y.max

A numeric specifying the maximum value on the y-axis. Default is NULL, which means the maximum value will be automatically determined.

same.y.lims

Whether to use the same y-axis limits for all plots. Default is FALSE.

aspect.ratio

Aspect ratio of the panel. Default is NULL.

title

The text for the title. Default is NULL.

subtitle

The text for the subtitle for the plot which will be displayed below the title. Default is NULL.

legend.position

The position of legends, one of "none", "left", "right", "bottom", "top". Default is "right".

legend.direction

The direction of the legend in the plot. Can be one of "vertical" or "horizontal".

theme_use

Theme used. Can be a character string or a theme function. Default is "theme_scop".

theme_args

Other arguments passed to the theme_use. Default is list().

combine

Combine plots into a single patchwork object. If FALSE, return a list of ggplot objects.

nrow

Number of rows in the combined plot. Default is NULL, which means determined automatically based on the number of plots.

ncol

Number of columns in the combined plot. Default is NULL, which means determined automatically based on the number of plots.

byrow

Whether to arrange the plots by row in the combined plot. Default is TRUE.

force

Whether to continue plotting if there are more than 50 features. Default is FALSE.

See also

CellStatPlot

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2026-01-27 07:16:42] Start standard scop workflow...
#> ℹ [2026-01-27 07:16:43] Checking a list of <Seurat>...
#> ! [2026-01-27 07:16:43] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-01-27 07:16:43] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/1 of the `srt_list`...
#> ℹ [2026-01-27 07:16:45] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#> ℹ [2026-01-27 07:16:45] Use the separate HVF from srt_list
#> ℹ [2026-01-27 07:16:45] Number of available HVF: 2000
#> ℹ [2026-01-27 07:16:45] Finished check
#> ℹ [2026-01-27 07:16:46] Perform `Seurat::ScaleData()`
#> ℹ [2026-01-27 07:16:46] Perform pca linear dimension reduction
#> ℹ [2026-01-27 07:16:47] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-01-27 07:16:47] Reorder clusters...
#> ℹ [2026-01-27 07:16:47] Perform umap nonlinear dimension reduction
#> ℹ [2026-01-27 07:16:47] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ℹ [2026-01-27 07:16:49] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ✔ [2026-01-27 07:16:52] Run scop standard 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: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_path()`).
#> Warning: Removed 3 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 0.548


CellDensityPlot(
  pancreas_sub,
  features = "Lineage1",
  group.by = "SubCellType",
  flip = TRUE
)
#> Picking joint bandwidth of 0.548