Hex-binned entropy map on embeddings

Compute per-bin Shannon entropy of group composition on UMAP/PCA and visualize as a tile heatmap.

Usage

VisHexEntropy(
  object,
  group.by = "seurat_clusters",
  reduction = "umap",
  bins = 30,
  palette = "C"
)

Arguments

object

A Seurat object; UMAP/PCA is computed when absent.

group.by

Metadata column for groups. Default: "seurat_clusters".

reduction

Reduction name ('umap' or 'pca'). Default: 'umap'.

bins

Number of bins per axis. Default: 30 (must be ≥2).

palette

Viridis palette option for color/fill. Default: "C".

Value

A ggplot heatmap of entropy.

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 <- VisHexEntropy(
  obj,
  group.by = "seurat_clusters",
  reduction = "umap",
  bins = 30,
  palette = "C")
p