plot_counts: plot_counts: Generates plots for the distribution of counts

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

plot_counts: Generates plots for the distribution of counts

Description

Generates density plots, violin plots, and/or boxplots for the distribution of count values

Usage

plot_counts(
  x = NULL,
  samples = NULL,
  data_type = "tr",
  plot_type = "density",
  color_pal = "okabeito",
  cvalpha = 0.5,
  distrib_subset = 0.5,
  subset_seed = 12345
)

Arguments

x	an STlist
samples	samples to include in the plot. Default (NULL) includes all samples
data_type	one of tr or raw, to plot transformed or raw counts
plot_type	one or several of density, violin, and box, to generate density plots, violin plots, and/or boxplots
color_pal	a string of a color palette from khroma or RColorBrewer, or a vector with colors
cvalpha	the transparency of the density plots
distrib_subset	the proportion of spots/cells to plot. Generating these plots can be time consuming due to the large amount of elements to plot. This argument provides control on how many randomly values to show to speed plotting
subset_seed	related to distrib_subset. Sets the seed number to ensure the same subset of values is selected for plotting

Details

The function allows to visualize the distribution counts across all genes and spots in the STlist. The user can select between density plots, violin plots, or box plots as visualization options. Useful for assessment of the effect of filtering and data transformations and to assess zero-inflation. To plot counts or genes per spot/cell, the function distribution_plots should be used instead.

Value

a list of ggplot objects

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
cp <- plot_counts(melanoma, data_type='raw', plot_type=c('violin', 'box'))
ggpubr::ggarrange(plotlist=cp)

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