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RunBanksy() computes a BANKSY matrix that augments each cell’s expression with the average expression of its spatial neighbors. The resulting matrix enables clustering that captures both cell type identity and spatial tissue domains.

​
Syntax

RunBanksy(
  object,
  lambda,
  assay = "RNA",
  slot = "data",
  use_agf = FALSE,
  dimx = NULL,
  dimy = NULL,
  dimz = NULL,
  ndim = 2,
  features = "variable",
  group = NULL,
  split.scale = TRUE,
  k_geom = 15,
  n = 2,
  sigma = 1.5,
  alpha = 0.05,
  k_spatial = 10,
  spatial_mode = "kNN_median",
  assay_name = "BANKSY",
  M = NULL,
  verbose = TRUE
)

​
Parameters

​
object
Seurat
required
A Seurat object with spatial coordinate metadata.
​
lambda
numeric
required
Spatial weight parameter. 0 uses only cell-intrinsic expression (equivalent to standard clustering). 1 uses only neighborhood expression. Values around 0.2 typically give good cell-type results; 0.8 is better for tissue domain segmentation.
​
assay
character
default:"RNA"
Assay in the Seurat object to use.
​
slot
character
default:"data"
Slot within the assay to use.
​
use_agf
logical
default:"FALSE"
Whether to use the Azimuthal Gabor Filter (AGF) for higher-order neighborhood features.
​
dimx
character
default:"NULL"
Column name in cell metadata containing the spatial x-coordinate.
​
dimy
character
default:"NULL"
Column name in cell metadata containing the spatial y-coordinate.
​
dimz
character
default:"NULL"
Column name in cell metadata containing the spatial z-coordinate (3D data only).
​
ndim
integer
default:"2"
Number of spatial dimensions to use (2 or 3).
​
features
character
default:"variable"
Features to compute. One of "all", "variable", or a character vector of feature names.
​
group
character
default:"NULL"
Column name of a grouping variable in metadata. Used to compute neighbors within groups.
​
split.scale
logical
default:"TRUE"
Whether to scale expression separately by group.
​
k_geom
numeric
default:"15"
Number of neighbors for the kNN spatial graph (used with kNN-based spatial_mode).
​
n
numeric
default:"2"
Exponent of radius for kNN_rn spatial mode.
​
sigma
numeric
default:"1.5"
Standard deviation of the Gaussian kernel for rNN_gauss mode.
​
alpha
numeric
default:"0.05"
Determines the radius used in rNN_gauss mode.
​
k_spatial
numeric
default:"10"
Number of neighbors for radial nearest neighbor modes.
​
spatial_mode
character
default:"kNN_median"
Kernel for spatial neighborhood computation. Options:
  • kNN_median — k-nearest neighbors with median-scaled Gaussian kernel
  • kNN_r — k-nearest neighbors with 1/r kernel
  • kNN_rn — k-nearest neighbors with 1/r^n kernel
  • kNN_rank — k-nearest neighbors with rank Gaussian kernel
  • kNN_unif — k-nearest neighbors with uniform kernel
  • rNN_gauss — radial nearest neighbors with Gaussian kernel
​
assay_name
character
default:"BANKSY"
Name for the new BANKSY assay stored in the Seurat object.
​
M
numeric
default:"NULL"
Highest azimuthal harmonic for AGF computation. Advanced usage.
​
verbose
logical
default:"TRUE"
Print progress messages.

​
Returns

A Seurat object with a new assay (default name BANKSY) containing the BANKSY-augmented expression matrix. Downstream analysis (PCA, UMAP, clustering) should be run on this assay.

​
Examples

library(SeuratWrappers)

# Run BANKSY with spatial coordinates in metadata
object <- RunBanksy(
  object = seurat_obj,
  lambda = 0.2,
  assay = "RNA",
  slot = "data",
  dimx = "x",
  dimy = "y",
  features = "variable",
  spatial_mode = "kNN_median",
  k_geom = 15
)

# Downstream clustering on BANKSY assay
DefaultAssay(object) <- "BANKSY"
object <- ScaleData(object)
object <- RunPCA(object)
object <- FindNeighbors(object)
object <- FindClusters(object, resolution = 0.5)

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See Also

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