Integrate Spatial Clusters From Multiple Samples Via Similarity Network Fusion

This function identifies conserved spatial ecotypes based on cell type specific gene expression signature of spatial clusters from all samples.

Usage

Integrate(
  avgexprs,
  Region = NULL,
  downsample.by.region = TRUE,
  nfeatures = 200,
  min.features = 5,
  minibatch = 5000,
  ncores = 1,
  seed = 1
)

Arguments

avgexprs: Gene expression signature of spatial clusters, where each column represents a spatial cluster (celltype..gene x spatial cluster matrix).
Region: A character vector specifying the region annotations for all spatial clusters.
downsample.by.region: A Boolean indicating whether to perform downsampling to balance the number of spatial clusters across regions.
nfeatures: Integer specifying the maximum number of top variable genes to select for each cell type.
min.features: Integer specifying the minimum number of shared features (genes) required across samples.
minibatch: Integer specifying the number of columns to process in each minibatch in the SNF analysis. Default is 5000. This option splits the matrix into smaller chunks (minibatch), thus reducing memory usage.
ncores: Integer specifying the number of cores for parallel processing. Default is 1.
seed: An integer used to seed the random number generator.

Value

Integrated similarity matrix of spatial clusters across all samples.