Ready-made SingleCells object for examples and tests

Wires generate_single_cell_test_data() into a SingleCells object on disk in one call, so examples do not have to repeat the whole ingestion dance. The default is deliberately tiny (500 cells x 50 genes) and the quality thresholds are loose enough that every cell survives. This is synthetic data for demonstration and testing, not something to analyse.

Usage

demo_single_cells(
  dir = tempfile("bixverse_demo"),
  prepped = TRUE,
  syn_data_params = params_sc_synthetic_data(n_cells = 500L, n_genes = 50L),
  hvg_no = 30L,
  no_pcs = 10L,
  k = 15L,
  seed = 42L,
  .verbose = FALSE
)

Arguments

dir

String. Directory to hold the object. Created if it does not exist. Defaults to a fresh path under the session tempdir(). Remove it with unlink(dir, recursive = TRUE) when you are done.

prepped

Boolean. Run the standard HVG -> PCA -> kNN chain before returning? Defaults to TRUE.

syn_data_params

List. Parameters for the synthetic data, see params_sc_synthetic_data().

hvg_no

Integer. Number of highly variable genes, prepped only.

no_pcs

Integer. Number of principal components, prepped only.

k

Integer. Number of nearest neighbours, prepped only.

seed

Integer. Seed for the data generation.

.verbose

Boolean. Controls verbosity of the function.

Value

A SingleCells object backed by dir.

Examples

# a prepped object, ready for clustering
sc <- demo_single_cells()
sc <- find_clusters_sc(sc, res = 1.0)
sc
#> Single cell experiment (Single Cells).
#>   No cells (original): 500
#>    To keep n: 500
#>   No genes: 50
#>   HVG calculated: TRUE
#>   PCA calculated: TRUE
#>   Other embeddings: none
#>   KNN generated: TRUE
#>   SNN generated: TRUE
#>   MAGIC imputed: none
#>   Residual model: none
#>   Stale artefacts: none

unlink(sc@dir_data, recursive = TRUE, force = TRUE)