Embedding density contours per group — VisEmbeddingContour • SeuratVisPro

Overlay 2D density contours for groups on UMAP/PCA to highlight boundaries.

Usage

VisEmbeddingContour(
  object,
  group.by = "seurat_clusters",
  reduction = "umap",
  levels = 5,
  palette = "C",
  point_size = 1,
  point_alpha = 0.5,
  contour_alpha = 0.1
)

Arguments

object: A Seurat object; UMAP/PCA is computed when absent.
group.by: Metadata column for grouping. Default: "seurat_clusters".
reduction: Reduction name ('umap' or 'pca'). Default: 'umap'.
levels: Number of contour levels. Default: 5.
palette: Viridis palette option for color/fill. Default: "C".
point_size: Point size. Default: 1.
point_alpha: Point alpha. Default: 0.5.
contour_alpha: Contour alpha. Default: 0.1.

Value

A ggplot with contours.

Author

benben-miao

Examples

obj <- SeuratVisProExample(
    n_cells = 300,
    n_genes = 1000,
    n_clusters = 10,
    seed = 123,
    genes_mt = "^MT-",
    neighbor_dims = 10,
    cluster_res = 0.5,
    umap_dims = 10,
    spatial = FALSE)
#> Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
#> 
#> Number of nodes: 300
#> Number of edges: 4508
#> 
#> Running Louvain algorithm...
#> Maximum modularity in 10 random starts: 0.9485
#> Number of communities: 10
#> Elapsed time: 0 seconds

p <- VisEmbeddingContour(
  obj,
  group.by = "seurat_clusters",
  reduction = "umap",
  levels = 5,
  palette = "C",
  point_size = 1,
  point_alpha = 0.5,
  contour_alpha = 0.1)
p