Plot dendrogram tree for CORE result

This function plots CORE and all clustering results underneath

plot_CORE(original.tree, list_clusters = NULL, color_branch = NULL)

Arguments

original.tree	the original dendrogram before clustering
list_clusters	a list containing clustering results for each of the
color_branch	is a vector containing user-specified colors (the number of unique colors should be equal or larger than the number of clusters). This parameter allows better selection of colors for the display.

Value

a plot with clustering bars underneath the tree

Examples

day5 <- day_5_cardio_cell_sample
cellnames <- colnames(day5$dat5_counts)
cluster <-day5$dat5_clusters
cellnames <-data.frame('Cluster'=cluster, 'cellBarcodes' = cellnames)
mixedpop2 <-new_summarized_scGPS_object(ExpressionMatrix = day5$dat5_counts,
    GeneMetadata = day5$dat5geneInfo, CellMetadata = cellnames)
CORE_cluster <- 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...
plot_CORE(CORE_cluster$tree, CORE_cluster$Cluster)