cutreeDynamicTree {dynamicTreeCut} | R Documentation |
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).
cutreeDynamicTree(dendro, maxTreeHeight = 1, deepSplit = TRUE, minModuleSize = 50)
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. |
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
.
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.
Bin Zhang, binzhang.ucla@gmail.com, with contributions by Peter Langfelder, Peter.Langfelder@gmail.com.
http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/BranchCutting