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Final clustering step for meta-clustering

Source: R/finalClustering.R
finalClustering.Rd

Merge initial clusters into final clusters based on the matrix of IDEr.

Usage

finalClustering(
  seu,
  dist,
  cutree.by = "h",
  cutree.h = 0.45,
  cutree.k = 3,
  hc.method = "complete"
)

Arguments

seu

Seurat S4 object after the step of `getIDEr`. Required.

dist

A list. Output of `getIDEr`. Required.

cutree.by

Character. Cut the tree by which parameter, height ("h") or number of clusters ("k"). (Default: h)

cutree.h

Numeric between 0 and 1. The height used to cut the tree. Ignored if `cutree.by = 'k`. (Default: 0.45)

cutree.k

Numeric/integer. Used to cut the tree. Ignored if `cutree.by = 'h`. (Default: 3)

hc.method

Character. Used to choose the hierarchical clustering method.

Value

Seurat S4 object with final clustering results in `CIDER_clusters` of meta.data.

See also

getIDEr.

Examples

library(CIDER)
data("pancreas")
ider <- getIDEr(pancreas, downsampling.size = 30)
#> Generating distance matrix...
#> 
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seu <- finalClustering(pancreas, ider)
head(seu$CIDER_cluster)
#> mouse1_lib2.final_cell_0006 mouse1_lib2.final_cell_0276 
#>                         "1"                         "1" 
#> mouse2_lib2.final_cell_0183 mouse2_lib3.final_cell_0217 
#>                         "1"                         "1" 
#> mouse1_lib2.final_cell_0230 mouse2_lib3.final_cell_0053 
#>                         "1"                         "1"