FindSpatiallyVariableFeatures: Find spatially variable features
In ibseq/scs-analysis: Tools for Single Cell Genomics

Identify features whose variability in expression can be explained to some degree by spatial location.

FindSpatiallyVariableFeatures(object, ...)

## Default S3 method:
FindSpatiallyVariableFeatures(
  object,
  spatial.location,
  selection.method = c("markvariogram", "moransi"),
  r.metric = 5,
  x.cuts = NULL,
  y.cuts = NULL,
  verbose = TRUE,
  ...
)

## S3 method for class 'Assay'
FindSpatiallyVariableFeatures(
  object,
  slot = "scale.data",
  spatial.location,
  selection.method = c("markvariogram", "moransi"),
  features = NULL,
  r.metric = 5,
  x.cuts = NULL,
  y.cuts = NULL,
  nfeatures = nfeatures,
  verbose = TRUE,
  ...
)

## S3 method for class 'Seurat'
FindSpatiallyVariableFeatures(
  object,
  assay = NULL,
  slot = "scale.data",
  features = NULL,
  image = NULL,
  selection.method = c("markvariogram", "moransi"),
  r.metric = 5,
  x.cuts = NULL,
  y.cuts = NULL,
  nfeatures = 2000,
  verbose = TRUE,
  ...
)

`object`	A Seurat object, assay, or expression matrix
`...`	Arguments passed to other methods
`spatial.location`	Coordinates for each cell/spot/bead
`selection.method`	Method for selecting spatially variable features. `markvariogram`: See `RunMarkVario` for details `moransi`: See `RunMoransI` for details.
`r.metric`	r value at which to report the "trans" value of the mark variogram
`x.cuts`	Number of divisions to make in the x direction, helps define the grid over which binning is performed
`y.cuts`	Number of divisions to make in the y direction, helps define the grid over which binning is performed
`verbose`	Print messages and progress
`slot`	Slot in the Assay to pull data from
`features`	If provided, only compute on given features. Otherwise, compute for all features.
`nfeatures`	Number of features to mark as the top spatially variable.
`assay`	Assay to pull the features (marks) from
`image`	Name of image to pull the coordinates from