articleBioinformaticsNov 16, 2007Closed access

Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R

University of California, Los Angeles · Rosetta Stone (United States)

PubMed
Indexed incrossrefdoajpubmed

Abstract

SUMMARY: Hierarchical clustering is a widely used method for detecting clusters in genomic data. Clusters are defined by cutting branches off the dendrogram. A common but inflexible method uses a constant height cutoff value; this method exhibits suboptimal performance on complicated dendrograms. We present the Dynamic Tree Cut R package that implements novel dynamic branch cutting methods for detecting clusters in a dendrogram depending on their shape. Compared to the constant height cutoff method, our techniques offer the following advantages: (1) they are capable of identifying nested clusters; (2) they are flexible-cluster shape parameters can be tuned to suit the application at hand; (3) they are suitable…

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