sub_clustering for selected cells

Source: R/CORE_clustering.R

performs 40 clustering runs or more depending on windows

sub_clustering(
  object = NULL,
  ngenes = 1500,
  windows = seq(from = 0.025, to = 1, by = 0.025),
  select_cell_index = NULL
)

Arguments

object

is a SingleCellExperiment object from the train mixed population
ngenes

number of genes used for clustering calculations.
windows

a numeric vector specifying the ranges of each window.
select_cell_index

a vector containing indexes for cells in selected clusters to be reclustered

Value

clustering results

Author

Quan Nguyen, 2018-01-31

Examples

day5 <- day_5_cardio_cell_sample
mixedpop2 <-new_summarized_scGPS_object(ExpressionMatrix = day5$dat5_counts, 
    GeneMetadata = day5$dat5geneInfo, CellMetadata = day5$dat5_clusters)
test_sub_clustering <-sub_clustering(mixedpop2,
    select_cell_index = c(seq_len(100)))

#> Calculating distance matrix
#> Performing hierarchical clustering
#> Finding clustering information
#> writing clustering result for run 1
#> Done clustering, moving to stability calculation...