sub_clustering (optional) after running CORE 'test'

CORE_subcluster allows re-cluster the CORE clustering result

CORE_subcluster(
  mixedpop = NULL,
  windows = seq(from = 0.025, to = 1, by = 0.025),
  select_cell_index = NULL,
  ngenes = 1500
)

Arguments

mixedpop	is a SingleCellExperiment object from the train mixed population
windows	a numeric specifying the number of windows to test
select_cell_index	a vector containing indexes for cells in selected clusters to be reclustered
ngenes	number of genes used for clustering calculations.

Value

a list with clustering results of all iterations, and a selected optimal resolution

Author

Quan Nguyen, 2017-11-25

Examples

day5 <- day_5_cardio_cell_sample
mixedpop2 <-new_summarized_scGPS_object(ExpressionMatrix = day5$dat5_counts,
    GeneMetadata = day5$dat5geneInfo, CellMetadata = day5$dat5_clusters)
test <- CORE_clustering(mixedpop2,remove_outlier= c(0))
#> Performing 1 round of filtering
#> Identifying top variable genes
#> Calculating distance matrix
#> Performing hierarchical clustering
#> Finding clustering information
#> No more outliers detected in filtering round 1
#> Identifying top variable genes
#> Calculating distance matrix
#> Performing hierarchical clustering
#> Finding clustering information
#> Done clustering, moving to stability calculation...
#> Done calculating stability...
#> Start finding optimal clustering...
#> Done finding optimal clustering...