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RunVelocity() estimates RNA velocity by comparing spliced and unspliced RNA counts, storing the result in the Seurat object’s Tool slot for downstream visualization.

​
Syntax

RunVelocity(
  object,
  spliced = "spliced",
  unspliced = "unspliced",
  ambiguous = NULL,
  spliced.average = 0.2,
  unspliced.average = 0.05,
  reduction = "pca",
  group.by = "ident",
  cells = NULL,
  graph = NULL,
  ncores = 1,
  verbose = TRUE,
  ...
)

​
Parameters

​
object
Seurat
required
A Seurat object with spliced and unspliced assays loaded (e.g., via ReadVelocity() + as.Seurat()).
​
spliced
character
default:"spliced"
Name of the assay containing spliced RNA counts.
​
unspliced
character
default:"unspliced"
Name of the assay containing unspliced RNA counts.
​
ambiguous
character
default:"NULL"
Optional name of the assay containing ambiguous RNA counts.
​
spliced.average
numeric
default:"0.2"
Minimum required average expression in the spliced matrix for a gene to be included.
​
unspliced.average
numeric
default:"0.05"
Minimum required average expression in the unspliced matrix for a gene to be included.
​
reduction
character
default:"pca"
Name of the reduction to use for computing the embedding distance matrix.
​
group.by
character
default:"ident"
Metadata column to use for grouping cells when filtering genes.
​
cells
character vector
default:"NULL"
Specific cells to include. Defaults to all cells.
​
graph
character
default:"NULL"
Name of a nearest-neighbor graph to use. If NULL, one is computed from the reduction.
​
ncores
integer
default:"1"
Number of CPU cores for parallel computation.
​
...
any
Additional parameters passed to velocyto.R::gene.relative.velocity.estimates().

​
Returns

A Seurat object with velocity estimates stored in Tool(object). Use velocyto.R::show.velocity.on.embedding.cor() to visualize the velocity field on a 2D embedding.

​
Examples

library(SeuratWrappers)
remotes::install_github("velocyto-team/velocyto.R")

# Read velocity data from loom file
ldat <- ReadVelocity(file = "sample.loom")
object <- as.Seurat(ldat)

# Preprocess and run velocity
DefaultAssay(object) <- "spliced"
object <- SCTransform(object, assay = "spliced")
object <- RunPCA(object)
object <- RunVelocity(
  object = object,
  reduction = "pca",
  ncores = 8,
  verbose = TRUE
)

# Visualize
ident.colors <- setNames(palette(), levels(Idents(object)))
velocyto.R::show.velocity.on.embedding.cor(
  emb = Embeddings(object, reduction = "umap"),
  vel = Tool(object = object, slot = "RunVelocity"),
  n = 200,
  scale = "sqrt",
  cell.colors = ident.colors[Idents(object)]
)

​
See Also

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