Build a Shared Nearest-Neighbor Graph

Convenience wrapper that calls fastFindKNN then delegates graph construction to bluster::neighborsToSNNGraph.

Usage

fastMakeSNNGraph(
  X,
  k = 15L,
  type = c("ann", "knn"),
  metric = c("euclidean", "cosine", "dot_product"),
  num.threads = NULL,
  BPPARAM = BiocParallel::bpparam(),
  ef.search = 0L,
  M = 16L,
  oversample.factor = 1,
  pq.subspaces = 0L,
  verbose = getOption("jvecfor.verbose", FALSE),
  snn.type = "rank",
  ...
)

Arguments

X

A numeric matrix, data.frame, or sparse matrix (Matrix::dgCMatrix) with rows = cells, cols = features/PCs.

k

Integer. Number of nearest neighbors. Default 15.

type

Character. "ann" or "knn". Default "ann".

metric

Character. "euclidean", "cosine", or "dot_product". Default "euclidean". See fastFindKNN for the dot_product restriction.

num.threads

Integer or NULL. Number of Java threads. If NULL, defaults to BiocParallel::bpworkers(BPPARAM).

BPPARAM

A BiocParallelParam object controlling the thread count. Defaults to bpparam().

ef.search

Integer. HNSW-DiskANN beam width override (0 = auto). Default 0L.

M

Integer. HNSW-DiskANN max connections per node. Default 16L.

oversample.factor

Numeric. Oversampling multiplier. Default 1.0.

pq.subspaces

Integer. PQ subspaces (0 = disabled). Default 0L.

verbose

Logical. Enable Java verbose logging. Default getOption("jvecfor.verbose", FALSE).

snn.type

Character. SNN weighting scheme passed to bluster::neighborsToSNNGraph: "rank", "jaccard", or "number". Default "rank".

...

Additional arguments forwarded to bluster::neighborsToSNNGraph.

Value

An igraph object (weighted, undirected SNN graph).

Examples

set.seed(42)
X <- matrix(rnorm(5000), nrow = 100, ncol = 50)

# Full examples require Java >= 20 on PATH
g <- fastMakeSNNGraph(X, k = 10)
igraph::vcount(g)  # 100
#> [1] 100

# Higher recall with larger beam and more connections
g2 <- fastMakeSNNGraph(X, k = 10, M = 32, oversample.factor = 2.0)