Plot CellRank outputs without rerunning a Python backend.
Usage
CellRankPlot(
srt,
plot_type = c("fate", "states", "circular", "drivers", "trends", "clusters",
"enrichment", "projection", "random_walks"),
lineage = NULL,
database = NULL,
reduction = NULL,
group.by = NULL,
top_n = 20L,
n_sims = 100L,
max_iter = 500L,
seed = 0L,
palette = "Chinese",
palcolor = NULL,
feature_palette = "Spectral",
feature_palcolor = NULL,
theme_use = "theme_scop",
theme_args = list(),
...
)Arguments
- srt
A Seurat object returned by [RunCellRank].
- plot_type
One of `"fate"`, `"states"`, `"circular"`, `"drivers"`, `"trends"`, `"clusters"`, `"enrichment"`, `"projection"`, or `"random_walks"`.
- lineage
Lineage used for driver/trend plots.
- database
Enrichment database used when `plot_type = "enrichment"`. If `NULL`, the first stored non-empty database is used.
- palette, palcolor
Discrete SCOP palette for states, modules, and cell groups.
- feature_palette, feature_palcolor
Continuous SCOP palette for fate, trends, pseudotime, and enrichment strength.
- theme_use, theme_args
SCOP plot theme and arguments passed to it.
- 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.
- ...
Arguments passed to the underlying SCOP plotting function.