cutreeDynamicTree: Dynamic Dendrogram Pruning Based on Dendrogram Only

Description

Detect clusters in a hierarchical dendrogram using a variable cut height approach. Uses only the information in the dendrogram itself is used (which may give incorrect assignment for outlying objects).

Usage

cutreeDynamicTree(dendro, maxTreeHeight = 1, deepSplit = TRUE, minModuleSize = 50)

Arguments

dendro

Hierarchical clustering dendrogram such produced by hclust.

maxTreeHeight

Maximum joining height of objects to be considered part of clusters.

deepSplit

If TRUE, method will favor sensitivity and produce more smaller clusters. When FALSE, there will be fewer bigger clusters.

minModuleSize

Minimum module size. Branches containing fewer than minModuleSize objects will be left unlabeled.

Value

A vector of numerical labels giving assignment of objects to modules. Unassigned objects are labeled 0, the largest module has label 1, next largest 2 etc.

Details

A variable height branch pruning technique for dendrograms produced by hierarchical clustering. Initially, branches are cut off at the height maxTreeHeight; the resulting clusters are then examined for substructure and if subclusters are detected, they are assigned separate labels. Subclusters are detected by structure and are required to have a minimum of minModuleSize objects on them to be assigned a separate label. A rough degree of control over what it means to be a subcluster is implemented by the parameter deepSplit.

References