Clustering Workflow

Cluster and Reduce Dimensions of a object

Usage

sce_clustering_workflow(
  object,
  excluded_cells,
  resolution = seq(0.2, 1, by = 0.2),
  organism = "human",
  experiment_name = "default_experiment",
  ...
)

Arguments

object

a SingleCellExperiment object

excluded_cells

named list of cells to exclude

resolution

resolution(s) to use for clustering cells

organism

Organism

experiment_name

name of the experiment

...

extra args passed to sce_process

Value

a clustered SingleCellExperiment object

Examples

data("small_example_dataset")
sce_clustering_workflow(small_example_dataset, experiment_name = "tiny_sce", 
organism = "human")
#> Warning: You're computing too large a percentage of total singular values, use a standard svd instead.
#> [01:59:49] Clustering Cells...
#> clustering at 0.2 resolution
#> clustering at 0.4 resolution
#> clustering at 0.6 resolution
#> clustering at 0.8 resolution
#> clustering at 1 resolution
#> stashing markers for gene_snn_res.1
#> [01:59:50 
#> Logging Technical Details...