dimplot: DimPlot / FeatureDimPlot
In plotthis: High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages

DimPlot

R Documentation

DimPlot / FeatureDimPlot

Description

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 of the point size. If NULL (default), the point size is auto-calculated as `min(3000 / nrow(data), 0.6)` so large datasets automatically get smaller points.
`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


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)
DimPlot(dim_example, group_by = "clusters", add_density = TRUE, density_filled = TRUE,
    density_filled_palette = "Blues", highlight = TRUE)

# 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)
DimPlot(dim_example, group_by = "clusters", hex = TRUE, hex_bins = 20)
DimPlot(dim_example, group_by = "clusters", hex = TRUE, hex_count = FALSE)

# 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)
DimPlot(dim_example, group_by = "clusters", velocity = 3:4,
    velocity_plot_type = "grid", arrow_alpha = 0.6)
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)


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)
FeatureDimPlot(dim_example, features = c("stochasticbasis_1", "stochasticbasis_2"),
 hex = TRUE, hex_bins = 15, split_by = "group", palette = list(A = "Reds", B = "Blues"))

# 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")

plotthis documentation built on July 9, 2026, 5:07 p.m.