pseudobulk_samples: Aggregates counts into "pseudo bulk" samples

Aggregates spot/cell counts into "pseudo bulk" samples for data exploration

pseudobulk_samples(x = NULL, max_var_genes = 5000)

Arguments

x

an STlist.

max_var_genes

number of most variable genes (standard deviation) to use in pseudobulk analysis

Value

an STlist with appended pseudobulk counts and PCA coordinates

Details

This function takes an STlist and aggregates the spot/cell counts into "pseudo bulk" counts by summing all counts from all cell/spots for each gene. Then performs Principal Component Analysis (PCA) to explore non-spatial sample-to-sample variation

Examples

# Using included melanoma example (Thrane et al.)
library('spatialGE')
data_files <- list.files(system.file("extdata", package="spatialGE"), recursive=T, full.names=T)
count_files <- grep("counts", data_files, value=T)
coord_files <- grep("mapping", data_files, value=T)
clin_file <- grep("thrane_clinical", data_files, value=T)
melanoma <- STlist(rnacounts=count_files[c(1:4)], spotcoords=coord_files[c(1:4)], samples=clin_file) # Only first two samples
#> Warning: Sample ST_mel3_rep1 was not found among the count/coordinate files.
#> Warning: Sample ST_mel3_rep2 was not found among the count/coordinate files.
#> Warning: Sample ST_mel4_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 <- pseudobulk_samples(melanoma)
pseudobulk_pca_plot(melanoma)