Run spatial variable feature detection

Score genes by spot-level spatial autocorrelation using a lightweight coordinate KNN graph. Moran's I is ranked high-to-low, while Geary's C is converted to 1 - C for the stored ranking score.

Usage

RunSpatialVariableFeatures(
  srt,
  assay = NULL,
  layer = "data",
  features = NULL,
  method = c("moran", "geary"),
  image = NULL,
  coord.cols = c("x", "y"),
  k = 6,
  nfeatures = 2000,
  min_spots = 5,
  nperm = 0,
  set_variable_features = TRUE,
  store_results = TRUE,
  verbose = TRUE,
  seed = 11
)

Arguments

srt

A Seurat object.

assay

Which assay to use. If NULL, the default assay of the Seurat object will be used. When the object also contains ChromatinAssay, the default assay and additional ChromatinAssay will be preprocessed sequentially.

layer

Assay layer used for expression values.

features

Features to score. If NULL, current variable features are used; if no variable features are present, all assay features are used.

method

Spatial autocorrelation statistic.

image

Name of the Seurat spatial image used by the spatial workflow. If NULL, the first image is used when present.

coord.cols

Metadata coordinate columns used by the spatial workflow when no image is available.

k

Number of nearest spatial neighbors per spot.

nfeatures

Number of top spatial features stored in srt@misc[["SpatialVariableFeatures"]].

min_spots

Minimum number of spots with non-zero expression required for a feature to be tested.

nperm

Number of label permutations used for empirical p values. The default 0 skips p-value calculation.

set_variable_features

Whether to set the top spatial features as variable features for assay.

store_results

Whether to store the full result in srt@tools.

verbose

Whether to print the message. Default is TRUE.

seed

Random seed used for permutation tests.

Value

A Seurat object with spatial variable feature results stored in srt@tools[["SpatialVariableFeatures"]] and top feature names stored in srt@misc[["SpatialVariableFeatures"]].

Examples

data(visium_human_pancreas_sub)
spatial <- Seurat::NormalizeData(
  visium_human_pancreas_sub,
  assay = "Spatial",
  verbose = FALSE
)
spatial <- Seurat::FindVariableFeatures(
  spatial,
  assay = "Spatial",
  nfeatures = 100,
  verbose = FALSE
)

SpatialSpotPlot(
  spatial,
  features = Seurat::VariableFeatures(spatial, assay = "Spatial")[1:2]
)

spatial <- RunSpatialVariableFeatures(
  spatial,
  assay = "Spatial",
  nfeatures = 50
)
SpatialSpotPlot(
  spatial,
  features = spatial@misc[["SpatialVariableFeatures"]][1:2]
)