leiden_dis — leiden_dis • Clonotrace

Leiden Clustering from Precomputed Distance Matrix

Usage

leiden_dis(
  dismat,
  k = 10,
  prune.snn = 0,
  weight = "jaccard",
  resolution = 1,
  if_umap = TRUE
)

dismat: A symmetric distance matrix (e.g., from `dist()`).
k: Integer. Number of neighbors for SNN construction (default: 10).
prune.snn: Numeric threshold to prune SNN edges (default: 0).
weight: Character. Column to use as edge weight (`"jaccard"` or `"dis"`) (default: `"jaccard"`).
resolution: Numeric resolution parameter for Leiden clustering (default: 1).
if_umap: Logical. If `TRUE`, returns UMAP coordinates with cluster annotations (default: TRUE).

If `if_umap = TRUE`, returns a data frame with UMAP coordinates and cluster labels. Otherwise, returns a factor vector of cluster memberships.

Constructs an SNN graph from a distance matrix, applies Leiden clustering, and optionally returns a UMAP layout annotated with clusters.

mat <- matrix(rnorm(500), nrow = 100)
dmat <- dist(mat)
clusters <- leiden_dis(as.matrix(dmat), k = 15, if_umap = FALSE)