get_gene_meta | R Documentation |
Extracts gene-level metadata and spatial statistics (if already computed)
get_gene_meta(x = NULL, sthet_only = F)
x |
an STlist |
sthet_only |
logical, return only genes with spatial statistics |
This function extracts data from the x@gene_meta
slot, optionally subsetting
only to those genes for which spatial statistics (Moran's I or Geary's C, see SThet
)
have been calculated. The output is a data frame with data from all samples in the
STlist
a data frame with gene-level data
# 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)
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