get_gene_meta: Extract gene-level metadata and statistics

Extracts gene-level metadata and spatial statistics (if already computed)

get_gene_meta(x = NULL, sthet_only = F)

Arguments

x

an STlist

sthet_only

logical, return only genes with spatial statistics

Value

a data frame with gene-level data

Details

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

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
#> Warning: Sample ST_mel3_rep1 was not found among the count/coordinate files.
#> Warning: Sample ST_mel4_rep2 was not found among the count/coordinate files.
#> Found matrix data
#> Matching gene expression and coordinate data...
#> Converting counts to sparse matrices
#> Completed STlist!
melanoma <- transform_data(melanoma, method='log')
melanoma <- SThet(melanoma, genes=c('MLANA', 'TP53'), method='moran')
#> SThet started.
#> 	Calculating spatial weights...
#> SThet completed in 0.01 min.
get_gene_meta(melanoma, sthet_only=TRUE)
#> # A tibble: 4 × 15
#>   sample     patient slice gender BRAF_status NRAS_status CDKN2A_status survival
#>   <chr>        <dbl> <chr> <chr>  <chr>       <chr>       <chr>         <chr>   
#> 1 ST_mel1_r…       1 B     Male   mut         wt          hd            10_plus…
#> 2 ST_mel1_r…       1 B     Male   mut         wt          hd            10_plus…
#> 3 ST_mel2_r…       2 A     Female wt          wt          hd            401_days
#> 4 ST_mel2_r…       2 A     Female wt          wt          hd            401_days
#> # ℹ 7 more variables: survival_months <dbl>, RIN <dbl>, gene <chr>,
#> #   gene_mean <dbl>, gene_stdevs <dbl>, moran_i <dbl>, geary_c <lgl>