spatialGE (version 1.2.2)

SThet: 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 = TRUE,
  cores = NULL,
  verbose = TRUE
)

Value

an STlist containing spatial statistics

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

verbose

logical, whether to print text to console

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.

Examples

# \donttest{
# 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='
tryCatch({ # In case data is not available from network
  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,
                     spotcoords=coord_files,
                     samples=clin_file)
  melanoma <- transform_data(melanoma)
  melanoma <- SThet(melanoma, genes=c('MLANA', 'TP53'), method='moran')
  get_gene_meta(melanoma, sthet_only=TRUE)
}, error = function(e) {
  message("Could not run example. Are you connected to the internet?")
  return(NULL)
})
# }