mergeClusters

mergeClusters

Description

Merge selected clusters based on pairwise correlation scores and size of cluster.

Usage

mergeClusters(
  gobject,
  expression_values = c("normalized", "scaled", "custom"),
  cluster_column,
  cor = c("pearson", "spearman"),
  new_cluster_name = "merged_cluster",
  min_cor_score = 0.8,
  max_group_size = 20,
  force_min_group_size = 10,
  max_sim_clusters = 10,
  return_gobject = TRUE,
  verbose = TRUE
)

Arguments

Argument	Description
gobject	giotto object
expression_values	expression values to use
cluster_column	name of column to use for clusters
cor	correlation score to calculate distance
new_cluster_name	new name for merged clusters
min_cor_score	min correlation score to merge pairwise clusters
max_group_size	max cluster size that can be merged
force_min_group_size	size of clusters that will be merged with their most similar neighbor(s)
max_sim_clusters	maximum number of clusters to potentially merge to reach force_min_group_size
return_gobject	return giotto object
verbose	be verbose

Details

Merge selected clusters based on pairwise correlation scores and size of cluster.

To avoid large clusters to merge the max_group_size can be lowered. Small clusters can be forcibly merged with their most similar pairwise cluster by adjusting the force_min_group_size parameter. Clusters smaller than this value will be merged independent on the provided min_cor_score value. The force_min_group_size might not always be reached if clusters have already been merged before list() A giotto object is returned by default, if FALSE then the merging vector will be returned.

Value

Giotto object

Examples

data("mini_giotto_single_cell")

pDataDT(mini_giotto_single_cell)
mini_giotto_single_cell = mergeClusters(mini_giotto_single_cell,
cluster_column = 'leiden_clus',
min_cor_score = 0.7,
force_min_group_size = 4)
pDataDT(mini_giotto_single_cell)
plotUMAP_2D(mini_giotto_single_cell, cell_color = 'merged_cluster', point_size = 3)