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Pseudotime Projection Plot

Source: R/PseudotimeProjectionPlot.R
PseudotimeProjectionPlot.Rd

This function creates a projection plot similar to VelocityPlot, but uses pseudotime data instead of RNA velocity analysis results.

Usage

PseudotimeProjectionPlot(
  srt,
  reduction,
  time_key,
  dims = c(1, 2),
  cells = NULL,
  method = c("knn", "gradient"),
  k = 30,
  graph_name = NULL,
  plot_type = c("raw", "grid", "stream"),
  group.by = NULL,
  group_palette = "Chinese",
  group_palcolor = NULL,
  n_neighbors = ceiling(ncol(srt@assays[[1]])/50),
  density = 2,
  smooth = 0.5,
  scale = 1,
  min_mass = 1,
  cutoff_perc = 5,
  arrow_angle = 20,
  arrow_color = "black",
  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,
  aspect.ratio = 1,
  title = "Pseudotime projection",
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  theme_use = "theme_scop",
  theme_args = list(),
  return_layer = FALSE,
  palette = NULL,
  palcolor = NULL,
  show_cells = TRUE,
  pt.size = 2,
  pt.alpha = 0.3,
  label = NULL,
  label.size = 4,
  label.fg = "black",
  label.bg = "white",
  label.bg.r = 0.1,
  seed = 11
)

Arguments

srt

A Seurat object.

reduction

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

time_key

Name of the column in the Seurat object metadata containing pseudotime values.

dims

Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions

cells

A character vector of cell names to use.

method

Method to compute velocity vectors from pseudotime. Can be "gradient" or "knn". Default is "knn".

k

Number of nearest neighbors to use when method = "knn". Default is 30.

graph_name

Name of the KNN graph in the Seurat object to use. If NULL, a new graph will be computed. Default is NULL.

plot_type

Type of plot to create. Can be "raw", "grid", or "stream".

group.by

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

group_palette

Name of the palette to use for coloring the groups. Defaults is "Chinese".

group_palcolor

Colors to use for coloring the groups. Defaults is NULL.

n_neighbors

Number of neighbors to include for the density estimation. Defaults is ceiling(ncol(srt@assays[[1]]) / 50).

density

Scale for the streamline grid (number of points per axis is ceiling(50 * density)). Default is 2 (CellRank/scvelo-style).

smooth

Smoothing parameter for density estimation. Defaults is 0.5.

scale

Scaling factor for the velocity vectors. Defaults is 1.

min_mass

Minimum mass value for the density-based cutoff. Defaults is 1.

cutoff_perc

Percentile value for the density-based cutoff. Defaults is 5.

arrow_angle

Angle of the arrowheads. Defaults is 20.

arrow_color

Color of the arrowheads. Defaults is "black".

streamline_L

Typical length of a streamline in x and y units

streamline_minL

Minimum length of segments to show.

streamline_res

Resolution parameter (higher numbers increases the resolution).

streamline_n

Number of points to draw.

streamline_width

Size of streamline.

streamline_alpha

Transparency of streamline.

streamline_color

Color of streamline.

streamline_palette

Color palette used for streamline.

streamline_palcolor

Custom colors used for streamline.

streamline_bg_color

Background color of streamline.

streamline_bg_stroke

Border width of streamline background.

aspect.ratio

Aspect ratio of the panel. Default is 1.

title

The text for the title. Defaults is "Pseudotime projection".

subtitle

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

xlab

The x-axis label of the plot. Default is NULL.

ylab

The y-axis label of the plot. 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().

return_layer

Whether to return the plot layers as a list. Defaults is FALSE.

palette

Deprecated alias of group_palette.

palcolor

Deprecated alias of group_palcolor.

show_cells

Whether to show cell points on the plot. Defaults is TRUE.

pt.size

Size of cell points. Defaults is 2 (CellRank-style overlapping patches).

pt.alpha

The transparency of the data points. Default is 0.3 (CellRank/scvelo-style).

label

Whether to label the cell groups. Defaults is TRUE when group.by is specified.

label.size

Size of labels.

label.fg

Foreground color of labels. Defaults is "black".

label.bg

Background color of labels. Defaults is "white".

label.bg.r

Background ratio of label.

seed

Random seed for reproducibility. Default is 11.

See also

VelocityPlot, CellDimPlot

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2026-04-26 01:52:09] Start standard processing workflow...
#> ℹ [2026-04-26 01:52:10] Checking a list of <Seurat>...
#> ! [2026-04-26 01:52:10] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-04-26 01:52:10] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-04-26 01:52:12] Perform `Seurat::FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-04-26 01:52:13] Use the separate HVF from `srt_list`
#> ℹ [2026-04-26 01:52:13] Number of available HVF: 2000
#> ℹ [2026-04-26 01:52:13] Finished check
#> ℹ [2026-04-26 01:52:14] Perform `Seurat::ScaleData()`
#> ℹ [2026-04-26 01:52:14] Perform pca linear dimension reduction
#> ℹ [2026-04-26 01:52:14] Use stored estimated dimensions 1:20 for Standardpca
#> ℹ [2026-04-26 01:52:15] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-04-26 01:52:15] Reorder clusters...
#> ℹ [2026-04-26 01:52:15] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-04-26 01:52:15] Perform umap nonlinear dimension reduction
#> ℹ [2026-04-26 01:52:15] Perform umap nonlinear dimension reduction using Standardpca (1:20)
#> ℹ [2026-04-26 01:52:20] Perform umap nonlinear dimension reduction using Standardpca (1:20)
#> ✔ [2026-04-26 01:52:25] Standard processing workflow completed
pancreas_sub <- RunSlingshot(
  pancreas_sub,
  reduction = "UMAP",
  group.by = "SubCellType"
)
#> Warning: Removed 9 rows containing missing values or values outside the scale range
#> (`geom_path()`).
#> Warning: Removed 9 rows containing missing values or values outside the scale range
#> (`geom_path()`).


PseudotimeProjectionPlot(
  pancreas_sub,
  reduction = "UMAP",
  group.by = "SubCellType",
  time_key = "Lineage1",
  method = "gradient",
  plot_type = "raw"
)
#> ! [2026-04-26 01:52:27] Removed 339 cells with NA pseudotime values


PseudotimeProjectionPlot(
  pancreas_sub,
  reduction = "UMAP",
  time_key = "Lineage1",
  group.by = "SubCellType",
  plot_type = "stream",
  show_cells = TRUE,
  label = TRUE
)
#> ! [2026-04-26 01:52:31] Removed 339 cells with NA pseudotime values
#> ℹ [2026-04-26 01:52:31] Computing KNN graph from embedding...


PseudotimeProjectionPlot(
  pancreas_sub,
  reduction = "UMAP",
  time_key = "Lineage2",
  plot_type = "grid"
)
#> ! [2026-04-26 01:52:44] Removed 185 cells with NA pseudotime values
#> ℹ [2026-04-26 01:52:44] Computing KNN graph from embedding...


PseudotimeProjectionPlot(
  pancreas_sub,
  reduction = "UMAP",
  time_key = "Lineage1",
  method = "gradient",
  plot_type = "raw"
)
#> ! [2026-04-26 01:52:53] Removed 339 cells with NA pseudotime values