DimPlot / FeatureDimPlot

DimPlot visualizes dimension reduction data (PCA, t-SNE, UMAP, etc.) as a 2D or 3D scatter plot. DimPlot() colours points by a discrete grouping variable (e.g., clusters), while FeatureDimPlot() colours points by a continuous numeric feature (e.g., gene expression, lineage scores).

Both functions share the same internal engine (DimPlotAtomic) and support an extensive set of annotation layers: group boundary marks, network/graph edges, 2D density contours, lineage/trajectory curves, RNA-velocity arrows (raw, grid, or stream), statistical summary mini-plots at group centroids, point highlighting, background context points from other facets, and flexible label positioning.

When dims has 3 elements, both functions automatically return an interactive plotly 3D scatter plot (via DimPlotAtomic3D). Certain 2D-only features are silently ignored in 3D mode (see @param dims for the full list).

Rendering scales with dataset size: standard geom_point() for small data, automatic rasterisation via scattermore::geom_scattermore() when nrow(data) > 1e5, or hex-bin aggregation (geom_hex() / stat_summary_hex()).

FeatureDimPlot to visualize feature expression on dimension reduction plots. Colours points by a continuous numeric variable (e.g., gene expression, module score, lineage pseudotime) using a gradient colour scale, with optional quantile trimming and background cutoff.

When multiple features are provided and facet_by is not set, the data is automatically pivoted to long format and faceted by feature name. split_by = TRUE dispatches each feature to a separate plot for independent layout control. split_by as a column name splits by that column's levels, producing one plot per level with per-split palette support.

For detailed split_by workflows, see the main DimPlot / FeatureDimPlot documentation (@section split_by Workflow (FeatureDimPlot)).

Usage

DimPlot(
  data,
  dims = 1:2,
  group_by,
  group_by_sep = "_",
  split_by = NULL,
  split_by_sep = "_",
  pt_size = NULL,
  pt_alpha = 1,
  bg_color = "grey80",
  label_insitu = FALSE,
  show_stat = !identical(theme, "theme_blank"),
  label = FALSE,
  label_size = 4,
  label_fg = "white",
  label_bg = "black",
  label_bg_r = 0.1,
  label_repel = FALSE,
  label_repulsion = 20,
  label_pt_size = 1,
  label_pt_color = "black",
  label_segment_color = "black",
  order = c("as-is", "reverse", "high-top", "low-top", "random"),
  highlight = NULL,
  highlight_alpha = 1,
  highlight_size = 1,
  highlight_color = "black",
  highlight_stroke = 0.8,
  add_mark = FALSE,
  mark_type = c("hull", "ellipse", "rect", "circle"),
  mark_expand = unit(3, "mm"),
  mark_alpha = 0.1,
  mark_linetype = 1,
  stat_by = NULL,
  stat_plot_type = c("pie", "ring", "bar", "line"),
  stat_plot_size = 0.1,
  stat_args = list(palette = "Set1"),
  graph = NULL,
  edge_size = c(0.05, 0.5),
  edge_alpha = 0.1,
  edge_color = "grey40",
  add_density = FALSE,
  density_color = "grey80",
  density_filled = FALSE,
  density_filled_palette = "Greys",
  density_filled_palcolor = NULL,
  lineages = NULL,
  lineages_trim = c(0.01, 0.99),
  lineages_span = 0.75,
  lineages_palette = "Dark2",
  lineages_palcolor = NULL,
  lineages_arrow = arrow(length = unit(0.1, "inches")),
  lineages_linewidth = 1,
  lineages_line_bg = "white",
  lineages_line_bg_stroke = 0.5,
  lineages_whiskers = FALSE,
  lineages_whiskers_linewidth = 0.5,
  lineages_whiskers_alpha = 0.5,
  velocity = NULL,
  velocity_plot_type = c("raw", "grid", "stream"),
  velocity_n_neighbors = NULL,
  velocity_density = 1,
  velocity_smooth = 0.5,
  velocity_scale = 1,
  velocity_min_mass = 1,
  velocity_cutoff_perc = 5,
  velocity_group_palette = "Set2",
  velocity_group_palcolor = NULL,
  arrow_angle = 20,
  arrow_color = "black",
  arrow_alpha = 1,
  streamline_l = 5,
  streamline_minl = 1,
  streamline_res = 1,
  streamline_n = 15,
  streamline_width = c(0, 0.8),
  streamline_alpha = 1,
  streamline_color = NULL,
  streamline_palette = "RdYlBu",
  streamline_palcolor = NULL,
  streamline_bg_color = "white",
  streamline_bg_stroke = 0.5,
  keep_na = FALSE,
  keep_empty = FALSE,
  facet_by = NULL,
  facet_scales = "fixed",
  facet_nrow = NULL,
  facet_ncol = NULL,
  facet_byrow = TRUE,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  theme = "theme_this",
  theme_args = list(),
  aspect.ratio = 1,
  legend.position = "right",
  legend.direction = "vertical",
  raster = NULL,
  raster_dpi = c(512, 512),
  hex = FALSE,
  hex_linewidth = 0.5,
  hex_count = TRUE,
  hex_bins = 50,
  hex_binwidth = NULL,
  palette = "Paired",
  palcolor = NULL,
  palreverse = FALSE,
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  axes = NULL,
  axis_titles = axes,
  guides = NULL,
  design = NULL,
  ...
)

FeatureDimPlot(
  data,
  dims = 1:2,
  features,
  split_by = NULL,
  split_by_sep = "_",
  lower_quantile = 0,
  upper_quantile = 0.99,
  lower_cutoff = NULL,
  upper_cutoff = NULL,
  pt_size = NULL,
  pt_alpha = 1,
  bg_color = "grey80",
  bg_cutoff = NULL,
  label_insitu = FALSE,
  show_stat = !identical(theme, "theme_blank"),
  color_name = "",
  label = FALSE,
  label_size = 4,
  label_fg = "white",
  label_bg = "black",
  label_bg_r = 0.1,
  label_repel = FALSE,
  label_repulsion = 20,
  label_pt_size = 1,
  label_pt_color = "black",
  label_segment_color = "black",
  order = c("as-is", "reverse", "high-top", "low-top", "random"),
  highlight = NULL,
  highlight_alpha = 1,
  highlight_size = 1,
  highlight_color = "black",
  highlight_stroke = 0.8,
  add_mark = FALSE,
  mark_type = c("hull", "ellipse", "rect", "circle"),
  mark_expand = unit(3, "mm"),
  mark_alpha = 0.1,
  mark_linetype = 1,
  keep_na = FALSE,
  keep_empty = FALSE,
  stat_by = NULL,
  stat_plot_type = c("pie", "ring", "bar", "line"),
  stat_plot_size = 0.1,
  stat_args = list(palette = "Set1"),
  graph = NULL,
  edge_size = c(0.05, 0.5),
  edge_alpha = 0.1,
  edge_color = "grey40",
  add_density = FALSE,
  density_color = "grey80",
  density_filled = FALSE,
  density_filled_palette = "Greys",
  density_filled_palcolor = NULL,
  lineages = NULL,
  lineages_trim = c(0.01, 0.99),
  lineages_span = 0.75,
  lineages_palette = "Dark2",
  lineages_palcolor = NULL,
  lineages_arrow = arrow(length = unit(0.1, "inches")),
  lineages_linewidth = 1,
  lineages_line_bg = "white",
  lineages_line_bg_stroke = 0.5,
  lineages_whiskers = FALSE,
  lineages_whiskers_linewidth = 0.5,
  lineages_whiskers_alpha = 0.5,
  velocity = NULL,
  velocity_plot_type = c("raw", "grid", "stream"),
  velocity_n_neighbors = NULL,
  velocity_density = 1,
  velocity_smooth = 0.5,
  velocity_scale = 1,
  velocity_min_mass = 1,
  velocity_cutoff_perc = 5,
  velocity_group_palette = "Set2",
  velocity_group_palcolor = NULL,
  arrow_angle = 20,
  arrow_color = "black",
  arrow_alpha = 1,
  streamline_l = 5,
  streamline_minl = 1,
  streamline_res = 1,
  streamline_n = 15,
  streamline_width = c(0, 0.8),
  streamline_alpha = 1,
  streamline_color = NULL,
  streamline_palette = "RdYlBu",
  streamline_palcolor = NULL,
  streamline_bg_color = "white",
  streamline_bg_stroke = 0.5,
  facet_by = NULL,
  facet_scales = "fixed",
  facet_nrow = NULL,
  facet_ncol = NULL,
  facet_byrow = TRUE,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  theme = "theme_this",
  theme_args = list(),
  aspect.ratio = 1,
  legend.position = "right",
  legend.direction = "vertical",
  raster = NULL,
  raster_dpi = c(512, 512),
  hex = FALSE,
  hex_linewidth = 0.5,
  hex_count = FALSE,
  hex_bins = 50,
  hex_binwidth = NULL,
  palette = "Spectral",
  palcolor = NULL,
  palreverse = FALSE,
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  axes = NULL,
  axis_titles = axes,
  guides = NULL,
  design = NULL,
  ...
)

Arguments

data

A data frame.

dims

A character vector of the column names to plot on the x, y (and optionally z) axes or a numeric vector of the column indices. When 3 dimensions are provided, a 3D interactive plot is created using plotly. Supported in 3D: group_by, features, labels, highlight, lineages, graph/network, show_stat, order. Not supported in 3D: add_mark, stat_by, add_density, velocity, hex, facet_by, raster.

group_by

Columns to group the data for plotting For those plotting functions that do not support multiple groups, They will be concatenated into one column, using group_by_sep as the separator

group_by_sep

The separator for multiple group_by columns. See group_by

split_by

A character vector of column names to split the data by and plot separately. If TRUE, the data is split by features — each feature is plotted in its own panel. Use this instead of facet_by when you need independent layout control (nrow, ncol) or per-feature palettes via split_by = TRUE combined with palette / palcolor.

split_by_sep

The separator for multiple split_by columns. See split_by

pt_size

A numeric value for point size, or a character string naming a numeric column in data to map point sizes to. If NULL (default), auto-calculated as min(3000 / nrow(data), 0.6). Column-name mapping only applies to 2D plots and is ignored with a message when raster = TRUE.

pt_alpha

A numeric value in [0, 1] for the point transparency. Default is 1.

bg_color

A character string specifying the colour used for NA-valued points and background context points drawn from other facets. Default is "grey80".

label_insitu

A logical value. If TRUE, the raw group names are placed at the group median coordinates instead of numeric indices. Forces label = TRUE. Default is FALSE.

show_stat

A logical value. If TRUE (default), the number of points per group is shown in the legend labels and subtitle. Ignored when theme = "theme_blank".

label

A logical value. If TRUE, group labels (numeric indices by default, or group names when label_insitu = TRUE) are placed at the median coordinates of each group. Forced to TRUE when label_repel or label_insitu is set.

label_size

A numeric value for the label text size. Passed to ggrepel::geom_text_repel(). Default is 4.

label_fg

A character string for the label text (foreground) colour. Default is "white".

label_bg

A character string for the label background / outline colour. Default is "black".

label_bg_r

A numeric value for the background fill ratio of the label bounding box. Passed to ggrepel::geom_text_repel(bg.r = ...). Default is 0.1.

label_repel

A logical value. If TRUE, labels are repelled from each other with force label_repulsion. A visible point anchor is drawn. Forces label = TRUE.

label_repulsion

A numeric value for the repulsion force when label_repel = TRUE. Passed to ggrepel::geom_text_repel(force = ...). Default is 20.

label_pt_size

A numeric value for the size of the anchor point drawn when label_repel = TRUE. Default is 1.

label_pt_color

A character string for the colour of the label anchor point. Default is "black".

label_segment_color

A character string for the colour of the line segment connecting the label to the anchor. Used in non-repel mode (label_repel = FALSE) where min.segment.length = 0. Default is "black".

order

A character string controlling the draw order of points:

"as-is" (default) — the row order in the data is preserved.
"reverse" — rows are reversed.
"high-top" — points with high values (last factor levels for group_by) are drawn last (on top).
"low-top" — points with low values (first factor levels) are drawn last.
"random" — rows are randomly shuffled.

For high-top and low-top, NA values are always plotted at the bottom. When applied to group_by, only the draw order changes — legend colours and order are unaffected. Within the same level, point order is preserved. For precise control, set factor levels before plotting. See https://github.com/pwwang/scplotter/issues/29#issuecomment-3009694130 for examples.

highlight

A specification for highlighted points:

NULL (default): no highlighting.
TRUE: highlight all points (adds a dark outline around every point).
A character string: a dplyr filter expression (e.g., "clusters == 'Ductal'").
A character vector: row names to highlight.
A numeric vector: row indices to highlight.

highlight_alpha

A numeric value in [0, 1] for the transparency of highlighted points. Default is 1.

highlight_size

A numeric value for the size of the inner (coloured) highlight point. Default is 1.

highlight_color

A character string for the colour of the outer highlight ring. Default is "black".

highlight_stroke

A numeric value for the thickness of the outer highlight ring (the difference between the outer ring size and highlight_size). Default is 0.8.

add_mark

A logical value. If TRUE, group boundaries are drawn around points using ggforce marks. Requires group_by. Only supported in 2D.

mark_type

A character string specifying the mark shape. Options: "hull" (convex hull, default), "ellipse", "rect", or "circle".

mark_expand

A unit value for the outward expansion of the mark boundary. Passed to ggforce::geom_mark_*(expand = ...). Default is unit(3, "mm").

mark_alpha

A numeric value in [0, 1] for the transparency of the mark fill. Default is 0.1.

mark_linetype

A numeric value for the line type of the mark boundary. Default is 1 (solid).

stat_by

A character string naming a column used to compute per-group statistical summary mini-plots embedded at group centroid positions. Only supported with group_by (not features). Only supported in 2D without facet_by.

stat_plot_type

A character string specifying the mini-plot type. Options: "pie" (default), "ring", "bar", or "line".

stat_plot_size

A numeric value for the size of the stat mini-plot, expressed as a fraction of the axis range. Default is 0.1.

stat_args

A list of additional arguments passed to the stat plot function (e.g., list(palette = "Set1")). Default is list(palette = "Set1").

graph

A specification for network / graph edges to overlay. Sources:

A character string starting with "@" (e.g., "@graph"): extracts the attribute named "graph" from attributes(data).
A Graph object (e.g., Seurat): coerced to dense matrix via as.matrix().
A matrix, data.frame, or dgCMatrix: used directly as the adjacency matrix.
Numeric indices or character column names: extracts columns from data. Edges are drawn for non-zero, lower-triangle entries. Requires data to have row names matching the matrix dimnames.

edge_size

A numeric vector of length 2 specifying the range [min, max] for scale_linewidth_continuous(range = ...) applied to edge widths. Default is c(0.05, 0.5).

edge_alpha

A numeric value in [0, 1] for the transparency of graph edges. Default is 0.1.

edge_color

A character string for the colour of graph edges. Default is "grey40".

add_density

A logical value. If TRUE, a 2D density layer is overlaid. Only supported in 2D.

density_color

A character string for the colour of the density contour lines. Used when density_filled = FALSE. Default is "grey80".

density_filled

A logical value. If TRUE, the density is rendered as a filled raster (stat_density_2d(geom = "raster")) instead of contour lines. A separate fill scale is used.

density_filled_palette

A character string naming the palette for the filled density layer. Default is "Greys".

density_filled_palcolor

A character vector of specific colours for the filled density palette. Default is NULL (auto-resolved from density_filled_palette).

lineages

A character vector of column names representing pseudotime / trajectory lineages. Each column is fitted with a LOESS smooth (span = lineages_span, degree = 2) across the 2D embedding, after trimming the top and bottom lineages_trim quantiles. Only supported in 2D without facet_by.

lineages_trim

A numeric vector of length 2 specifying the lower and upper quantile thresholds [0, 1] for trimming lineage values before LOESS fitting. Default is c(0.01, 0.99).

lineages_span

A numeric value passed as span to stats::loess() controlling the smoothness of the lineage curve. Smaller values follow the data more closely. Default is 0.75.

lineages_palette

A character string naming the palette for lineage colours. Default is "Dark2".

lineages_palcolor

A character vector of specific colours for lineage curves. Default is NULL (auto-resolved from lineages_palette).

lineages_arrow

A ggplot2 arrow specification applied to the end of lineage paths. Default is arrow(length = unit(0.1, "inches")).

lineages_linewidth

A numeric value for the width of the lineage curve lines. Default is 1.

lineages_line_bg

A character string for the colour of the background (wider) stroke drawn behind each lineage curve for improved visibility. Default is "white".

lineages_line_bg_stroke

A numeric value for the additional width of the background stroke relative to lineages_linewidth. The background line has total width lineages_linewidth + lineages_line_bg_stroke. Default is 0.5.

lineages_whiskers

A logical value. If TRUE, short line segments connect the smoothed lineage curve to the original data coordinates of the fitted points. Default is FALSE.

lineages_whiskers_linewidth

A numeric value for the width of the whisker lines. Default is 0.5.

lineages_whiskers_alpha

A numeric value in [0, 1] for the transparency of the whisker lines. Default is 0.5.

velocity

A specification for RNA-velocity arrows. Can be:

NULL (default): no velocity overlay.
A character / integer vector: column names or indices in data for the velocity embedding.
A data frame or matrix: the velocity embedding itself (must align with data rows). Only supported in 2D without facet_by.

velocity_plot_type

A character string specifying the velocity rendering style. Options: "raw" (arrows from embedding), "grid" (grid-based arrows), or "stream" (streamlines). Default is "raw".

velocity_n_neighbors

A numeric value for the number of neighbours used in the velocity grid computation. Default is NULL (auto).

velocity_density

A numeric value for the velocity kernel density bandwidth. Default is 1.

velocity_smooth

A numeric value for the velocity smoothing parameter. Default is 0.5.

velocity_scale

A numeric value for scaling the velocity arrows. Default is 1.

velocity_min_mass

A numeric value for the minimum cell mass threshold in velocity grid computation. Default is 1.

velocity_cutoff_perc

A numeric value for the velocity cutoff percentage. Default is 5.

velocity_group_palette

A character string naming the palette for velocity group colours (used in "raw" plot type). Default is "Set2".

velocity_group_palcolor

A character vector of specific colours for velocity groups. Default is NULL (auto-resolved from velocity_group_palette).

arrow_angle

A numeric value specifying the angle of the arrowheads in degrees. Applied to arrow when plot_type is "raw" or "grid". Default is 20.

arrow_color

A character string specifying the color of the velocity arrows. For plot_type = "stream", this sets only the arrowhead color. Default is "black".

arrow_alpha

A numeric value between 0 and 1 specifying the transparency of the velocity arrows. Only used when plot_type = "raw" or "grid"; for plot_type = "stream", use streamline_alpha instead. Default is 1.

streamline_l

A numeric value specifying the integration length of the streamlines. Passed to geom_streamline as the L parameter. Default is 5.

streamline_minl

A numeric value specifying the minimum streamline length. Shorter streamlines are not drawn. Passed to geom_streamline as the min.L parameter. Default is 1.

streamline_res

A numeric value specifying the resolution of the streamline integration. Passed to geom_streamline as the res parameter. Default is 1.

streamline_n

A numeric value specifying the number of streamlines to draw. Passed to geom_streamline as the n parameter. Default is 15.

streamline_width

A numeric vector of length 2 specifying the range of line widths for streamlines. Passed to scale_size(range = ...). Only used when streamline_color is NULL. Default is c(0, 0.8).

streamline_alpha

A numeric value between 0 and 1 specifying the transparency of the velocity streamlines. Default is 1.

streamline_color

An optional character string specifying a fixed color for streamlines. When NULL (the default), streamlines are colored by velocity magnitude using streamline_palette.

streamline_palette

A character string specifying the color palette for streamline velocity magnitude. Passed to palette_this. Only used when streamline_color is NULL. Default is "RdYlBu".

streamline_palcolor

An optional character vector of specific colors for the streamline velocity gradient. If NULL, colors are generated from streamline_palette. Default is NULL.

streamline_bg_color

A character string specifying the background (outline) color applied to streamlines to create a stroke effect. Default is "white".

streamline_bg_stroke

A numeric value specifying the additional line width of the background stroke relative to the foreground streamline. Default is 0.5.

keep_na

A logical value or a character to replace the NA values in the data. It can also take a named list to specify different behavior for different columns. If TRUE or NA, NA values will be replaced with NA. If FALSE, NA values will be removed from the data before plotting. If a character string is provided, NA values will be replaced with the provided string. If a named vector/list is provided, the names should be the column names to apply the behavior to, and the values should be one of TRUE, FALSE, or a character string. Without a named vector/list, the behavior applies to categorical/character columns used on the plot, for example, the x, group_by, fill_by, etc.

keep_empty

One of FALSE, TRUE and "level". It can also take a named list to specify different behavior for different columns. Without a named list, the behavior applies to the categorical/character columns used on the plot, for example, the x, group_by, fill_by, etc.

FALSE (default): Drop empty factor levels from the data before plotting.
TRUE: Keep empty factor levels and show them as a separate category in the plot.
"level": Keep empty factor levels, but do not show them in the plot. But they will be assigned colors from the palette to maintain consistency across multiple plots. Alias: levels

facet_by

A character string specifying the column name of the data frame to facet the plot. Otherwise, the data will be split by split_by and generate multiple plots and combine them into one using patchwork::wrap_plots

facet_scales

Whether to scale the axes of facets. Default is "fixed" Other options are "free", "free_x", "free_y". See ggplot2::facet_wrap

facet_nrow

A numeric value specifying the number of rows in the facet. When facet_by is a single column and facet_wrap is used.

facet_ncol

A numeric value specifying the number of columns in the facet. When facet_by is a single column and facet_wrap is used.

facet_byrow

A logical value indicating whether to fill the plots by row. Default is TRUE.

title

A character string specifying the title of the plot. A function can be used to generate the title based on the default title. This is useful when split_by is used and the title needs to be dynamic.

subtitle

A character string specifying the subtitle of the plot.

xlab

A character string specifying the x-axis label.

ylab

A character string specifying the y-axis label.

theme

A character string or a theme class (i.e. ggplot2::theme_classic) specifying the theme to use. Default is "theme_this".

theme_args

A list of arguments to pass to the theme function.

aspect.ratio

A numeric value specifying the aspect ratio of the plot.

legend.position

A character string specifying the position of the legend. if waiver(), for single groups, the legend will be "none", otherwise "right".

legend.direction

A character string specifying the direction of the legend.

raster

A logical value. If TRUE, points are rendered via scattermore::geom_scattermore() for efficient rasterised plotting. Default is NULL, which auto-enables when nrow(data) > 1e5.

raster_dpi

A numeric vector of length 2 [x_dpi, y_dpi] specifying the raster resolution in pixels. Passed to scattermore::geom_scattermore(pixels = ...). Default is c(512, 512). If a single value is provided it is recycled to both dimensions.

hex

A logical value. If TRUE, points are rendered as hexagonal bins via geom_hex() / stat_summary_hex(). Not supported with highlight. Default is FALSE. Only supported in 2D.

hex_linewidth

A numeric value for the width of the hexagon boundary lines. Default is 0.5.

hex_count

A logical value. If TRUE and group_by is set, hex fill alpha is mapped to after_stat(count) so denser bins are more opaque. For features mode hex_count is ignored. Default is !is.null(group_by).

hex_bins

A numeric value for the number of hex bins along each axis. Passed to geom_hex(bins = ...). Default is 50.

hex_binwidth

A numeric value for the width of individual hex bins. Passed to geom_hex(binwidth = ...). Takes precedence over hex_bins when set.

palette

A character string specifying the palette to use. A named list or vector can be used to specify the palettes for different split_by values.

palcolor

A character string specifying the color to use in the palette. A named list can be used to specify the colors for different split_by values. If some values are missing, the values from the palette will be used (palcolor will be NULL for those values).

palreverse

A logical value indicating whether to reverse the palette. Default is FALSE.

seed

The random seed to use. Default is 8525.

combine

Whether to combine the plots into one when facet is FALSE. Default is TRUE.

nrow

A numeric value specifying the number of rows in the facet.

ncol

A numeric value specifying the number of columns in the facet.

byrow

A logical value indicating whether to fill the plots by row.

axes

A string specifying how axes should be treated. Passed to patchwork::wrap_plots(). Only relevant when split_by is used and combine is TRUE. Options are:

'keep' will retain all axes in individual plots.
'collect' will remove duplicated axes when placed in the same run of rows or columns of the layout.
'collect_x' and 'collect_y' will remove duplicated x-axes in the columns or duplicated y-axes in the rows respectively.

axis_titles

A string specifying how axis titltes should be treated. Passed to patchwork::wrap_plots(). Only relevant when split_by is used and combine is TRUE. Options are:

'keep' will retain all axis titles in individual plots.
'collect' will remove duplicated titles in one direction and merge titles in the opposite direction.
'collect_x' and 'collect_y' control this for x-axis titles and y-axis titles respectively.

guides

A string specifying how guides should be treated in the layout. Passed to patchwork::wrap_plots(). Only relevant when split_by is used and combine is TRUE. Options are:

'collect' will collect guides below to the given nesting level, removing duplicates.
'keep' will stop collection at this level and let guides be placed alongside their plot.
'auto' will allow guides to be collected if a upper level tries, but place them alongside the plot if not.

design

Specification of the location of areas in the layout, passed to patchwork::wrap_plots(). Only relevant when split_by is used and combine is TRUE. When specified, nrow, ncol, and byrow are ignored. See patchwork::wrap_plots() for more details.

...

Additional arguments.

features

A character vector of the column names to plot as features (continuous colouring). When multiple features are provided and facet_by is not set, the data is pivoted to long format and faceted by feature name.

lower_quantile, upper_quantile

Lower and upper quantiles for the continuous color/fill scale. The actual cutoffs are determined by these quantiles when lower_cutoff and upper_cutoff are NULL. Defaults: lower_quantile = 0, upper_quantile = 0.99.

lower_cutoff, upper_cutoff

Explicit lower and upper cutoffs for the continuous color/fill scale. When NULL (the default), the cutoffs are determined by lower_quantile and upper_quantile via quantile. Values outside the [lower_cutoff, upper_cutoff] range are clamped (winsorized) to the nearest cutoff value.

bg_cutoff

A numeric threshold. Feature values with absolute value below this cutoff are set to NA (and therefore rendered in bg_color). Default is NULL.

color_name

A character string used as the title for the continuous colour bar in feature mode. Default is "".

Value

A ggplot object (single plot), a patchwork / wrap_plots object (when split_by is provided and combine = TRUE), or a list of ggplot objects (when split_by is provided and combine = FALSE). When dims has 3 elements, a plotly object is returned instead.

split_by Workflow (DimPlot)

When split_by is specified, DimPlot() executes the following pipeline:

Argument validation — validate_common_args() checks the seed and blocks split_by + velocity combinations.
NA / empty normalisation — check_keep_na() / check_keep_empty() convert keep_na / keep_empty to per-column lists.
Theme resolution — process_theme() resolves the theme string to a theme function.
Split column resolution — check_columns() validates split_by (force_factor, concat_multi).
Pre-filtering — process_keep_na_empty() removes NA / empty levels from the split column, then data is split by split_by levels (order preserved). When graph references an attribute (@graph), the graph matrix is also subset per split.
Per-split parameter resolution — check_palette(), check_palcolor(), check_legend() resolve palette, palcolor, legend.position, and legend.direction for each split.
Per-split dispatch — each split is passed to DimPlotAtomic() with its resolved parameters. Title defaults to the split level name unless title is a function.
Combination — combine_plots() assembles the list of plots via patchwork::wrap_plots(), applying nrow, ncol, byrow, axes, axis_titles, guides, and design.

split_by Workflow (FeatureDimPlot)

FeatureDimPlot() supports two forms of splitting:

A. split_by = TRUE (split by features)

Each feature in features is dispatched individually to DimPlotAtomic(), producing one plot per feature. The plot title defaults to the feature name.
Plots are combined via combine_plots() with split_by = ".features".

B. split_by as a column name (split by data column)

Data is split by the named column's levels (same pipeline as DimPlot steps 1–8 above). Graph attribute splitting is supported.

Examples

# \donttest{
data(dim_example)

# basic dim plot
DimPlot(dim_example, group_by = "clusters")

DimPlot(dim_example, group_by = "clusters", theme = "theme_blank")

DimPlot(dim_example, group_by = "clusters", theme = ggplot2::theme_classic,
    theme_args = list(base_size = 16), palette = "seurat")


# raster and highlighting
DimPlot(dim_example, group_by = "clusters", raster = TRUE, raster_dpi = 50)

DimPlot(dim_example, group_by = "clusters", highlight = 1:20,
    highlight_color = "black", highlight_stroke = 2)

DimPlot(dim_example, group_by = "clusters", highlight = TRUE, facet_by = "group",
    theme = "theme_blank")


# labels
DimPlot(dim_example, group_by = "clusters", label = TRUE,
    label_size = 5, label_bg_r = 0.2)

DimPlot(dim_example, group_by = "clusters", label = TRUE, label_fg = "red",
    label_bg = "yellow", label_size = 5)

DimPlot(dim_example, group_by = "clusters", label = TRUE, label_insitu = TRUE)


# group marks
DimPlot(dim_example, group_by = "clusters", add_mark = TRUE)

DimPlot(dim_example, group_by = "clusters", add_mark = TRUE, mark_linetype = 2)

DimPlot(dim_example, group_by = "clusters", add_mark = TRUE, mark_type = "ellipse")


# density overlays
DimPlot(dim_example, group_by = "clusters", add_density = TRUE)

DimPlot(dim_example, group_by = "clusters", add_density = TRUE, density_filled = TRUE)
#> Warning: Removed 396 rows containing missing values or values outside the scale range
#> (`geom_raster()`).

DimPlot(dim_example, group_by = "clusters", add_density = TRUE, density_filled = TRUE,
    density_filled_palette = "Blues", highlight = TRUE)
#> Warning: Removed 396 rows containing missing values or values outside the scale range
#> (`geom_raster()`).


# statistics at group centroids
DimPlot(dim_example, group_by = "clusters", stat_by = "group")

DimPlot(dim_example, group_by = "clusters", stat_by = "group",
    stat_plot_type = "bar", stat_plot_size = 0.06)


# hex bins
DimPlot(dim_example, group_by = "clusters", hex = TRUE)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_hex()`).

DimPlot(dim_example, group_by = "clusters", hex = TRUE, hex_bins = 20)
#> Warning: Removed 5 rows containing missing values or values outside the scale range
#> (`geom_hex()`).

DimPlot(dim_example, group_by = "clusters", hex = TRUE, hex_count = FALSE)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_hex()`).


# graph / network edges
DimPlot(dim_example, group_by = "clusters", graph = "@graph", edge_color = "grey80")


# lineages / trajectories
DimPlot(dim_example, group_by = "clusters", lineages = c("stochasticbasis_1", "stochasticbasis_2"))

DimPlot(dim_example, group_by = "clusters", lineages = c("stochasticbasis_1", "stochasticbasis_2"),
    lineages_whiskers = TRUE, lineages_whiskers_linewidth = 0.1)

DimPlot(dim_example, group_by = "clusters", lineages = c("stochasticbasis_1", "stochasticbasis_2"),
    lineages_span = 0.4)


# split_by
DimPlot(dim_example, group_by = "clusters",  split_by = "group",
    palette = list(A = "Paired", B = "Set1"))


# velocity
DimPlot(dim_example, group_by = "clusters", velocity = c("stochasticbasis_1", "stochasticbasis_2"),
    pt_alpha = 0)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_segment()`).

DimPlot(dim_example, group_by = "clusters", velocity = 3:4,
    velocity_plot_type = "grid", arrow_alpha = 0.6)
#> Warning: Removed 6 rows containing missing values or values outside the scale range
#> (`geom_segment()`).

DimPlot(dim_example, group_by = "clusters", velocity = 3:4,
    velocity_plot_type = "stream")


# 3D plots (returns a plotly object)
DimPlot(dim_example, dims = 1:3, group_by = "clusters")

DimPlot(dim_example, dims = 1:3, group_by = "clusters", label = TRUE,
    label_insitu = TRUE)

DimPlot(dim_example, dims = c("basis_1", "basis_2", "stochasticbasis_1"),
    group_by = "clusters", graph = "@graph", edge_color = "grey80")


# keep_na and keep_empty
dim_example$clusters[dim_example$clusters == "Ductal"] <- NA

DimPlot(dim_example, group_by = "clusters", keep_na = FALSE, keep_empty = TRUE)

DimPlot(dim_example, group_by = "clusters", keep_na = TRUE, keep_empty = TRUE)

DimPlot(dim_example, group_by = "clusters", keep_na = TRUE, keep_empty = FALSE)

# }
# \donttest{
data(dim_example)

# single feature
FeatureDimPlot(dim_example, features = "stochasticbasis_1", pt_size = 2)

FeatureDimPlot(dim_example, features = "stochasticbasis_1", pt_size = 2, bg_cutoff = 0)

FeatureDimPlot(dim_example, features = "stochasticbasis_1", raster = TRUE, raster_dpi = 30)


# multiple features (auto-pivoted to long, faceted by feature)
FeatureDimPlot(dim_example, features = c("stochasticbasis_1", "stochasticbasis_2"),
 pt_size = 2)


# single feature with facet_by (facet_by works when only 1 feature)
FeatureDimPlot(dim_example, features = c("stochasticbasis_1"), pt_size = 2,
 facet_by = "group")


# multiple features with split_by for independent layout
FeatureDimPlot(dim_example, features = c("stochasticbasis_1", "stochasticbasis_2"),
 split_by = "group", nrow = 2)


# highlight and hex
FeatureDimPlot(dim_example, features = c("stochasticbasis_1", "stochasticbasis_2"),
 highlight = TRUE)

FeatureDimPlot(dim_example, features = c("stochasticbasis_1", "stochasticbasis_2"),
 hex = TRUE, hex_bins = 15)
#> Warning: Removed 8 rows containing missing values or values outside the scale range
#> (`geom_hex()`).

FeatureDimPlot(dim_example, features = c("stochasticbasis_1", "stochasticbasis_2"),
 hex = TRUE, hex_bins = 15, split_by = "group", palette = list(A = "Reds", B = "Blues"))
#> Warning: Removed 6 rows containing missing values or values outside the scale range
#> (`geom_hex()`).
#> Warning: Removed 8 rows containing missing values or values outside the scale range
#> (`geom_hex()`).


# 3D plots (returns a plotly object)
FeatureDimPlot(dim_example, dims = 1:3, features = "stochasticbasis_2", pt_size = 2)

FeatureDimPlot(dim_example, dims = c("basis_1", "basis_2", "stochasticbasis_1"),
 features = "stochasticbasis_2")

# }