Plot VECTOR results — VECTORPlot • scop

Visualize VECTOR grid-level scores or direction arrows on the embedding used by RunVECTOR().

Usage

VECTORPlot(
  object,
  plot_type = c("grid", "raw"),
  tool_name = "VECTOR",
  score.name = "VECTOR_Score",
  group.by = NULL,
  background = c("auto", "score", "group", "none"),
  point.size = NULL,
  point.alpha = 0.7,
  grid.size = 2,
  arrow.linewidth = 0.5,
  arrow.length = grid::unit(0.035, "inches"),
  arrow.angle = 20,
  arrow.color = "grey20",
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  aspect.ratio = 1,
  legend.position = "right",
  legend.direction = "vertical",
  theme_use = "theme_scop",
  theme_args = list(),
  ...
)

Arguments

object: A Seurat object processed by RunVECTOR().
plot_type: Plot type. "grid" colors occupied grid centers by grid score, and "raw" draws VelocityPlot-style grid arrows.
tool_name: Name used in srt@tools.
score.name: Metadata column containing VECTOR scores.
group.by: Optional metadata column used as the background cell color for direction-field plots.
background: Background for plots. "score" uses FeatureDimPlot(), "group" uses CellDimPlot() and requires group.by, and "none" draws the flow field without cell points.
point.size: Cell point size. If NULL, uses the same default as FeatureDimPlot().
point.alpha: Cell point alpha.
grid.size: Grid-center point size.
arrow.linewidth: Direction arrow line width.
arrow.length: Arrow head length passed to grid::arrow().
arrow.angle: Arrow head angle passed to grid::arrow().
arrow.color: Direction arrow color.
title, subtitle, xlab, ylab: Plot labels. By default no title is shown.
aspect.ratio: Fixed aspect ratio.
legend.position, legend.direction: Legend position and direction.
theme_use, theme_args: Theme function and arguments.
...: Additional arguments passed to FeatureDimPlot() or CellDimPlot() when a cell background is requested.

Value

A ggplot object.

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2026-07-28 03:33:57] Start standard processing workflow...
#> ℹ [2026-07-28 03:33:57] Checking a list of <Seurat>...
#> ! [2026-07-28 03:33:58] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-07-28 03:33:58] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-07-28 03:33:58] Perform `FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-07-28 03:33:58] Use the separate HVF from `srt_list`
#> ℹ [2026-07-28 03:33:58] Number of available HVF: 2000
#> ℹ [2026-07-28 03:33:58] Finished check
#> ℹ [2026-07-28 03:33:58] Perform `ScaleData()`
#> ℹ [2026-07-28 03:33:58] Perform pca linear dimension reduction
#> ℹ [2026-07-28 03:33:59] Use stored estimated dimensions 1:23 for Standardpca
#> ℹ [2026-07-28 03:33:59] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-07-28 03:33:59] Reorder clusters...
#> ℹ [2026-07-28 03:33:59] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-07-28 03:33:59] Perform umap nonlinear dimension reduction
#> ✔ [2026-07-28 03:34:05] Standard processing workflow completed
pancreas_sub <- RunVECTOR(pancreas_sub, verbose = FALSE)
VECTORPlot(pancreas_sub, plot_type = "grid")

VECTORPlot(pancreas_sub, plot_type = "raw", group.by = "SubCellType")