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Plot CellRank results

Source: R/CellRankPlot.R
CellRankPlot.Rd

Plot CellRank results

Usage

CellRankPlot(
  object,
  plot_type = c("fate", "states", "circular", "drivers", "projection", "random_walks",
    "flow"),
  lineage = NULL,
  reduction = NULL,
  group.by = NULL,
  top_n = 20L,
  n_sims = 100L,
  max_iter = 500L,
  seed = 0L,
  start_cells = NULL,
  cluster = NULL,
  clusters = NULL,
  palette = "Chinese",
  palcolor = NULL,
  feature_palette = "Spectral",
  feature_palcolor = NULL,
  theme_use = "theme_scop",
  theme_args = list(),
  srt = NULL,
  ...
)

Arguments

object

A Seurat object returned by [RunCellRank].

plot_type

One of `"fate"`, `"states"`, `"circular"`, `"drivers"`, `"projection"`, `"random_walks"`, or `"flow"`.

lineage

Lineage used for driver plots.

reduction

Reduction used for cell-space plots.

group.by

Group column used for state/random-walk plots.

top_n

Number of driver genes to display.

n_sims

Number of random walks.

max_iter

Maximum length of each random walk.

seed

Random seed. Random-walk plotting restores the caller's RNG state, including when plotting fails.

start_cells

Optional cell names used as random-walk starts. For a moscot result, omitted starts default to cells in the earliest time point.

cluster

Starting group for `plot_type = "flow"`.

clusters

Optional groups to display in a real-time flow plot.

palette, palcolor

Discrete SCOP palette for states and cell groups.

feature_palette, feature_palcolor

Continuous SCOP palette for fate, confidence, and pseudotime.

theme_use, theme_args

SCOP plot theme and arguments passed to it.

srt

Deprecated alias for `object`; supply exactly one of the two. It will be removed in scop 1.0.0.

...

Arguments passed to other functions.

Value

A ggplot or patchwork object.

See also

[DynamicHeatmap] and [DynamicPlot] for feature dynamics; [EnrichmentPlot] for enrichment results.

Examples

data(pancreas_sub)
pancreas_sub <- RunStandardWorkflow(pancreas_sub)
#> ℹ [2026-11-12 05:03:53] Start standard processing workflow...
#> ℹ [2026-11-12 05:03:53] Checking a list of <Seurat>...
#> ! [2026-11-12 05:03:53] Data 1/1 of the `srt_list` is "unknown"
#> Warning: Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-11-12 05:03:53] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-11-12 05:03:53] Perform `FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-11-12 05:03:54] Use the separate HVF from `srt_list`
#> ℹ [2026-11-12 05:03:54] Number of available HVF: 2000
#> ℹ [2026-11-12 05:03:54] Finished check
#> ℹ [2026-11-12 05:03:54] Perform `ScaleData()`
#> ℹ [2026-11-12 05:03:54] Perform pca linear dimension reduction
#> ℹ [2026-11-12 05:03:54] Use stored estimated dimensions 1:23 for Standardpca
#> ℹ [2026-11-12 05:03:55] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-11-12 05:03:55] Reorder clusters...
#> ℹ [2026-11-12 05:03:55] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-11-12 05:03:55] Perform umap nonlinear dimension reduction
#> ✔ [2026-11-12 05:04:01] Standard processing workflow completed
pancreas_sub <- RunCellRank(
  pancreas_sub,
  group.by = "SubCellType",
  kernel_type = "pseudotime",
  time_key = "palantir_pseudotime",
  schur_method = "brandts",
  backend = "cpp"
)
#> ! [2026-11-12 05:04:01] RunCellRank(backend = "cpp") uses an approximate C++ implementation; results may not be completely identical to the reference python workflow.
#> Warning: RunCellRank(backend = "cpp") uses an approximate C++ implementation; results may not be completely identical to the reference python workflow.
#> ℹ [2026-11-12 05:04:01] Running `RunSCVELO()` cpp backend before `RunCellRank()`
#> ℹ [2026-11-12 05:04:01] Running scanpy-compatible preprocessing (15998 features -> filter + normalize)...
#> ℹ [2026-11-12 05:04:05] Running scVelo "stochastic" mode with `backend = 'cpp'` (9699 features)
#> ✔ [2026-11-12 05:04:08] scVelo "stochastic" mode completed
#> ✔ [2026-11-12 05:04:08] scVelo cpp backend completed
#> ! [2026-11-12 05:04:08] Pseudotime not found; computing velocity pseudotime
#> Warning: Pseudotime not found; computing velocity pseudotime
#> ✔ [2026-11-12 05:04:11] CellRank cpp backend ("gpcca" + "pseudotime_connectivity_combined" kernel) completed

CellRankPlot(
  pancreas_sub,
  plot_type = "fate",
  reduction = "UMAP",
  xlab = "UMAP_1",
  ylab = "UMAP_2"
)

CellRankPlot(
  pancreas_sub,
  plot_type = "circular"
)
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.