SThet: SThet: Computes global spatial autocorrelation statistics on...

In FridleyLab/spatialGE: Visualization and Analysis of Spatial Heterogeneity in Spatially-Resolved Gene Expression

SThet: Computes global spatial autocorrelation statistics on gene expression

Description

Computes the global spatial autocorrelation statistics Moran's I and/or Geary's C for a set of genes

Usage

SThet(
  x = NULL,
  genes = NULL,
  samples = NULL,
  method = "moran",
  k = NULL,
  overwrite = T,
  cores = NULL
)

Arguments

x	an STlist
genes	a vector of gene names to compute statistics
samples	the samples to compute statistics
method	The spatial statistic(s) to estimate. It can be set to 'moran', 'geary' or both. Default is 'moran'
k	the number of neighbors to estimate weights. By default NULL, meaning that spatial weights will be estimated from Euclidean distances. If an positive integer is entered, then the faster k nearest-neighbors approach is used. Please keep in mind that estimates are not as accurate as when using the default distance-based method.
overwrite	logical indicating if previous statistics should be overwritten. Default to FALSE (do not overwrite)
cores	integer indicating the number of cores to use during parallelization. If NULL, the function uses half of the available cores at a maximum. The parallelization uses parallel::mclapply and works only in Unix systems.

Details

The function computes global spatial autocorrelation statistics (Moran's I and/or Geary's C) for the requested genes and samples. Then computation uses the package spdep. The calculated statistics are stored in the STlist, which can be accessed with the get_gene_meta function. For visual comparative analysis, the function compare_SThet can be used afterwards.

Value

an STlist containing spatial statistics

Examples

# Using included melanoma example (Thrane et al.)
# Download example data set from spatialGE_Data
thrane_tmp = tempdir()
unlink(thrane_tmp, recursive=TRUE)
dir.create(thrane_tmp)
lk='https://github.com/FridleyLab/spatialGE_Data/raw/refs/heads/main/melanoma_thrane.zip?download='
download.file(lk, destfile=paste0(thrane_tmp, '/', 'melanoma_thrane.zip'), mode='wb')
zip_tmp = list.files(thrane_tmp, pattern='melanoma_thrane.zip$', full.names=TRUE)
unzip(zipfile=zip_tmp, exdir=thrane_tmp)
# Generate the file paths to be passed to the STlist function
count_files <- list.files(paste0(thrane_tmp, '/melanoma_thrane'),
                          full.names=TRUE, pattern='counts')
coord_files <- list.files(paste0(thrane_tmp, '/melanoma_thrane'),
                          full.names=TRUE, pattern='mapping')
clin_file <- list.files(paste0(thrane_tmp, '/melanoma_thrane'),
                        full.names=TRUE, pattern='clinical')
# Create STlist
library('spatialGE')
melanoma <- STlist(rnacounts=count_files[c(1,2)],
                   spotcoords=coord_files[c(1,2)],
                   samples=clin_file) # Only first two samples
melanoma <- transform_data(melanoma, method='log')
melanoma <- SThet(melanoma, genes=c('MLANA', 'TP53'), method='moran')
get_gene_meta(melanoma, sthet_only=TRUE)

FridleyLab/spatialGE documentation built on April 14, 2025, 9:37 a.m.