detectSpatialPatterns: detectSpatialPatterns

In RubD/Giotto: Spatial Single-Cell Transcriptomics Toolbox

detectSpatialPatterns

Description

Identify spatial patterns through PCA on average expression in a spatial grid.

Usage

detectSpatialPatterns(
  gobject,
  expression_values = c("normalized", "scaled", "custom"),
  spatial_grid_name = "spatial_grid",
  min_cells_per_grid = 4,
  scale_unit = F,
  ncp = 100,
  show_plot = T,
  PC_zscore = 1.5
)

Arguments

gobject	giotto object
expression_values	expression values to use
spatial_grid_name	name of spatial grid to use (default = 'spatial_grid')
min_cells_per_grid	minimum number of cells in a grid to be considered
scale_unit	scale features
ncp	number of principal components to calculate
show_plot	show plots
PC_zscore	minimum z-score of variance explained by a PC

Details

Steps to identify spatial patterns:

• 1. average gene expression for cells within a grid, see createSpatialGrid

• 2. perform PCA on the average grid expression profiles

• 3. convert variance of principlal components (PCs) to z-scores and select PCs based on a z-score threshold

Value

spatial pattern object 'spatPatObj'

RubD/Giotto documentation built on April 29, 2023, 5:52 p.m.