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Benchmark spatial domain clustering methods

Source: R/RunSpatialBenchmark.R
RunSpatialBenchmark.Rd

Run supported spatial domain clustering methods from the same immutable input, compare their aligned labels with a gold standard, and record classification quality, elapsed time, and sampled peak process-tree memory. Each method runs in an isolated R process so one failed backend does not corrupt the input or prevent the remaining methods from being assessed.

Usage

RunSpatialBenchmark(
  srt,
  gold_standard,
  methods = NULL,
  method_params = list(),
  n_clusters = NULL,
  metrics = c("ARI", "NMI"),
  keep_objects = FALSE,
  install_missing = FALSE,
  seed = 1,
  timeout = Inf,
  poll_interval = 0.1,
  verbose = TRUE
)

Arguments

srt

A spatial Seurat object.

gold_standard

Either one metadata column in srt or a named vector whose names match the spot names in srt.

methods

Spatial domain methods to benchmark. NULL uses every benchmarked producer (BayesSpace, BANKSY, and SmoothClust). Method names may be written with or without the Run prefix.

method_params

Named list of per-method argument lists. Arguments are passed to the corresponding SCOP producer, never directly to its backend.

n_clusters

Optional common number of domains. When NULL, methods that require a cluster count use the number of non-missing gold-standard classes. A method-specific q or n_clusters in method_params wins.

metrics

Quality metrics selected by default when plotting. Supported values are "ARI", "NMI", and "purity". All three are retained in the result summary.

keep_objects

Whether to keep each successful method's full producer result. The default keeps only aligned labels and compact run metadata.

install_missing

Whether missing optional backends may enter their producer's normal check_r() installation path. The default records them as unavailable without changing the R library.

seed

Seed set inside each isolated method process and forwarded to producers with a public seed argument unless overridden in method_params.

timeout

Maximum wall time in seconds for each isolated run, including process start and result serialization. Inf disables the timeout.

poll_interval

Seconds between process-tree memory samples.

verbose

Whether to print the message. Default is TRUE.

Value

A spatial_benchmark_result object (also inherits benchmark_result). Use result$summary for the quality table, SpatialBenchmarkPlot() for visualization, and $predictions for the aligned labels.

See also

SpatialBenchmarkPlot, RunIntegrationBenchmark

Examples

if (FALSE) { # \dontrun{
data(visium_human_pancreas_sub)
visium_human_pancreas_sub$gold_domain <- factor(
  paste0("domain_", (seq_len(ncol(visium_human_pancreas_sub)) - 1) %% 3 + 1)
)
bench <- RunSpatialBenchmark(
  visium_human_pancreas_sub,
  gold_standard = "gold_domain",
  method_params = list(
    BayesSpace = list(n.PCs = 5, n.HVGs = 200),
    BANKSY = list(layer = "counts"),
    SmoothClust = list(layer = "counts", min_spots = 1)
  )
)
bench
SpatialBenchmarkPlot(data = bench)
} # }