Run Giotto spatial gene detection

Usage

GiottoSpatialGenes(
  x,
  features = NULL,
  network_method = c("Delaunay", "kNN"),
  network_name = NULL,
  bin_method = c("kmeans", "rank"),
  top_n = 100,
  params = list(),
  verbose = TRUE,
  seed = 11
)

Arguments

x: A `giotto2` workflow object.
features: Features to test.
network_method: Spatial network method.
network_name: Name for the Giotto spatial network.
bin_method: Binarization method passed to `Giotto::binSpect()`.
top_n: Number of top spatial genes to store.
params: Additional parameters passed to `Giotto::binSpect()`.
verbose: Whether to print progress messages.
seed: Random seed for reproducible Giotto calls.

Value

A `giotto2` workflow object.

Examples

data(visium_human_pancreas_sub)
spatial <- visium_human_pancreas_sub
coords <- data.frame(
  cell_ID = colnames(spatial),
  sdimx = spatial$x,
  sdimy = spatial$y,
  row.names = colnames(spatial)
)
spatial_gene_table <- data.frame(
  feat_ID = rownames(spatial)[1:8],
  spatGeneRank = seq_len(8),
  adj.p.value = seq(0.001, 0.04, length.out = 8)
)
g <- structure(
  list(
    source = list(cells = colnames(spatial), coordinates = coords),
    results = list(
      spatial_genes = list(
        table = spatial_gene_table,
        top_features = spatial_gene_table$feat_ID
      )
    )
  ),
  class = c("giotto2", "list")
)
GiottoPlot(g, plot_type = "spatial_genes", top_n = 6)


if (
  isTRUE(check_r("giotto-suite/Giotto", verbose = FALSE))
) {
  g <- SeuratToScopGiotto(spatial, coord.cols = c("x", "y"))
  g <- GiottoPreprocess(g)
  g <- GiottoSpatialNetwork(g)
  g <- GiottoSpatialGenes(g, features = rownames(spatial)[1:50], top_n = 10)
}
#> Error in check_r("giotto-suite/Giotto", verbose = FALSE): could not find function "check_r"