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Create cluster from list of hclust objects

Usage

createClusters(
  treeList,
  method = c("capushe", "bstick", "meanClusterSize"),
  meanClusterSize = 50,
  pct = 0.15
)

Arguments

treeList

list of hclust objects

method

'capushe': slope heuristic. 'bstick': broken stick. 'meanClusterSize': create clusters based on target mean value.

meanClusterSize

select target mean cluster size. Can be an array of values

pct

minimum percentage of points for the plateau selection in capushe selection. Can be an array of values

Value

Convert hierarchical clustering into discrete clusters based on selection criteria method

Examples

library(GenomicRanges)
library(EnsDb.Hsapiens.v86)

# load data
data('decorateData')

# load gene locations
ensdb = EnsDb.Hsapiens.v86

# Evaluate hierarchical clustering
treeList = runOrderedClusteringGenome( simData, simLocation ) 
#> 
Evaluating:chr20          
#> 

# Choose cutoffs and return clusters
treeListClusters = createClusters( treeList )
#> Method:capushe

# Plot correlations and clusters in region defined by query
query = range(simLocation)

plotDecorate( ensdb, treeList, treeListClusters, simLocation, query)