Cluster-Level Communication Analysis — cluster

Aggregate and analyze cell-cell communication at cluster level.

Aggregate cell-cell communication to cluster-cluster level and optionally perform permutation testing.

Usage

cluster_communication(
  seurat_obj,
  database_name,
  clustering,
  lr_pair = NULL,
  pathway_name = NULL,
  n_permutations = 100L,
  seed = NULL,
  verbose = TRUE
)

Arguments

seurat_obj: Seurat object with COMMOTR results.
database_name: Name of database.
clustering: Name of metadata column containing cluster assignments, or a factor/character vector of cluster assignments.
lr_pair: Specific LR pair (if NULL, uses pathway_name or total).
pathway_name: Pathway name (if lr_pair is NULL).
n_permutations: Number of permutations for significance testing (default: 100). Set to 0 to skip.
seed: Random seed for permutation.
verbose: Print progress messages.

Value

Seurat object with cluster communication results stored.

Details

For each cluster pair (i, j), computes the total communication from cells in cluster i to cells in cluster j. If permutation testing is enabled, p-values are computed by randomly permuting cluster labels.

Examples

if (FALSE) { # \dontrun{
# After running spatial_communication
seurat_obj <- cluster_communication(
    seurat_obj,
    database_name = "CellChat",
    clustering = "seurat_clusters",
    pathway_name = "TGFb",
    n_permutations = 100
)

# Plot results
plot_cluster_communication(
    seurat_obj,
    database_name = "CellChat",
    clustering = "seurat_clusters",
    key = "TGFb"
)
} # }