Construct a SNN neighbour list from assay.

Usage

findNbrsSNN(
  spe,
  assay = NULL,
  dimred = "PCA",
  n_dimred = 10,
  k = 20,
  BNPARAM = BiocNeighbors::AnnoyParam(),
  type = c("rank", "number", "jaccard"),
  nbrs_name = NULL,
  cpu_threads = 6
)

Arguments

spe: A SpatialExperiment object.
assay: Name of assay for clustering. Incompatible with dimred.
dimred: Name of the dimensionality reduction (e.g. PCA) for clustering. Incompatible with assay
n_dimred: Integer scalar or vector specifying the dimensions to use if dimred is specified.
k: Integer scalar for number of nearest neighbors to find.
BNPARAM: BiocNeighborParam object specifying the nearest neighbor algorithm. Default is Annoy.
type: Type of weighting scheme for shared neighbors. Options are rank, number, and jaccard. type="rank" is defined in Xu and Su (2015).
nbrs_name: Name of the neighbour list to be stored in spe. Default to be assay/dimred + "_snn".
cpu_threads: Number of cpu threads for parallel computation.

Value

A spe with the clusters stored in reducedDims.

A SpatialExperiment object

Details

Construct a SNN neighbour list using either the spe's assay or reduced dimension and store it in spe@metadata$nbrs$cell

neighbour list contain

Examples


data("xenium_bc_spe")
spe <- runPCA(spe)
#> Default assay logcounts not found. Switching to counts assay instead.
#> Genes with 0 variance are excluded: ENSG00000135218 NegControlProbe_00002 NegControlCodeword_0504 NegControlCodeword_0509 NegControlCodeword_0510 NegControlCodeword_0511 NegControlCodeword_0512 NegControlCodeword_0516 NegControlCodeword_0517 NegControlCodeword_0518 NegControlCodeword_0519 NegControlCodeword_0520 NegControlCodeword_0522 NegControlCodeword_0526 NegControlCodeword_0527 NegControlCodeword_0530 NegControlCodeword_0536 NegControlCodeword_0537 BLANK_0030 BLANK_0163 BLANK_0165 BLANK_0212 BLANK_0221 BLANK_0230 BLANK_0237 BLANK_0311 BLANK_0361 BLANK_0365 BLANK_0382 BLANK_0384 BLANK_0387 BLANK_0388 BLANK_0391 BLANK_0393 BLANK_0397 BLANK_0399 BLANK_0404 BLANK_0406 BLANK_0410 BLANK_0411 BLANK_0418 BLANK_0425 BLANK_0432 BLANK_0447
spe <- findNbrsSNN(spe,dimred="PCA")
#> [1] "Getting K-nearest neighbour"
#> [1] "Getting shared nearest neighbour"