Plot CellRank outputs without rerunning a Python backend.
Usage
CellRankPlot(
object,
plot_type = c("fate", "states", "circular", "drivers", "trends", "clusters",
"enrichment", "projection", "random_walks", "flow"),
lineage = NULL,
database = 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"`, `"trends"`, `"clusters"`, `"enrichment"`, `"projection"`, or `"random_walks"`, or `"flow"`.
- 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.
- 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.
- 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, 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.
- ...
Arguments passed to the underlying SCOP plotting function.
- srt
Deprecated alias for `object`; supply exactly one of the two. It will be removed in scop 1.0.0.
Examples
if (FALSE) { # \dontrun{
data(pancreas_sub)
pancreas_sub <- RunStandardWorkflow(pancreas_sub)
pancreas_sub <- RunCellRank(
pancreas_sub,
group.by = "SubCellType",
kernel_type = "pseudotime",
time_key = "palantir_pseudotime",
schur_method = "brandts",
backend = "python"
)
CellRankPlot(pancreas_sub, plot_type = "fate", reduction = "UMAP")
CellRankPlot(pancreas_sub, plot_type = "circular")
} # }