STplot_interpolation: STplot_interpolation: Visualize gene expression surfaces

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

STplot_interpolation: Visualize gene expression surfaces

Description

Produces a gene expression surface from kriging interpolation of ST data.

Usage

STplot_interpolation(
  x = NULL,
  genes = NULL,
  top_n = 10,
  samples = NULL,
  color_pal = "BuRd"
)

Arguments

x	an STlist containing results from gene_krige for the genes selected.
genes	a vector of gene names (one or several) to plot. If 'top', the 10 genes with highest standard deviation from each spatial sample are plotted.
top_n	an integer indicating how many top genes to perform kriging. Default is 10.
samples	a vector indicating the spatial samples to plot. If vector of numbers, it follows the order of names(x@counts). If NULL, the function plots all samples
color_pal	a color scheme from khroma or RColorBrewer.

Details

This function produces a gene expression surface plot via kriging for one or several genes and spatial samples

Value

a list of plots

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='
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 <- gene_interpolation(melanoma, genes=c('MLANA', 'COL1A1'), samples='ST_mel1_rep2')
  kp = STplot_interpolation(melanoma, genes=c('MLANA', 'COL1A1'), samples='ST_mel1_rep2')
  ggpubr::ggarrange(plotlist=kp)
}, error = function(e) {
  message("Could not run example. Are you connected to the internet?")
  return(NULL)
})

spatialGE documentation built on June 8, 2025, 11:10 a.m.