View source: R/local_correlations.R
createClusters | R Documentation |
Create cluster from list of hclust objects
createClusters(
treeList,
method = c("capushe", "bstick", "meanClusterSize"),
meanClusterSize = 50,
pct = 0.15
)
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 |
Convert hierarchical clustering into discrete clusters based on selection criteria method
library(GenomicRanges)
library(EnsDb.Hsapiens.v86)
# load data
data('decorateData')
# load gene locations
ensdb = EnsDb.Hsapiens.v86
# Evaluate hierarchical clustering
treeList = runOrderedClusteringGenome( simData, simLocation )
# Choose cutoffs and return clusters
treeListClusters = createClusters( treeList )
# Plot correlations and clusters in region defined by query
query = range(simLocation)
plotDecorate( ensdb, treeList, treeListClusters, simLocation, query)
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