detectSpatialCorGenes

detectSpatialCorGenes

Description

Detect genes that are spatially correlated

Usage

detectSpatialCorGenes(
  gobject,
  method = c("grid", "network"),
  expression_values = c("normalized", "scaled", "custom"),
  subset_genes = NULL,
  spatial_network_name = "Delaunay_network",
  network_smoothing = NULL,
  spatial_grid_name = "spatial_grid",
  min_cells_per_grid = 4,
  cor_method = c("pearson", "kendall", "spearman")
)

Arguments

Argument	Description
gobject	giotto object
method	method to use for spatial averaging
expression_values	gene expression values to use
subset_genes	subset of genes to use
spatial_network_name	name of spatial network to use
network_smoothing	smoothing factor beteen 0 and 1 (default: automatic)
spatial_grid_name	name of spatial grid to use
min_cells_per_grid	minimum number of cells to consider a grid
cor_method	correlation method

Details

For method = network, it expects a fully connected spatial network. You can make sure to create a

fully connected network by setting minimal_k > 0 in the ``createSpatialNetwork` <#createspatialnetwork>`_ function.

• list(“1. grid-averaging: “) list(“average gene expression values within a predefined spatial grid”)

• list(“2. network-averaging: “) list(“smoothens the gene expression matrix by averaging the expression within one celln”, ” by using the neighbours within the predefined spatial network. b is a smoothening factorn”, ” that defaults to 1 - 1/k, where k is the median number of k-neighbors in then”, ” selected spatial network. Setting b = 0 means no smoothing and b = 1 means no contributionn”, ” from its own expression.”)
  The spatCorObject can be further explored with showSpatialCorGenes()

Value

returns a spatial correlation object: “spatCorObject”

Seealso

``showSpatialCorGenes` <#showspatialcorgenes>`_