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Activity Number: 257
Type: Contributed
Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Graphics
Abstract #316836 View Presentation
Title: Visualizing, Adjusting, and Comparing Dendrograms Using the dendextend R Package
Author(s): Tal Galili*
Companies: Tel Aviv University
Keywords: dendrogram ; unsupervised learning ; hierarchical clustering ; R ; R package ; Visualization

A dendrogram is a tree diagram which is often used to visualize a hierarchical clustering of items. Dendrograms are used in many disciplines, ranging from Phylogenetic Trees in computational biology to Lexomic Trees in text analysis. Hierarchical clustering in R is commonly performed using the hclust function. When a more sophisticated visualization is desired, the hclust object is often coerced into a dendrogram object, which in turn is modified and plotted.

The dendextend R package extends the palette of base R functions for the dendrogram class, offering easier manipulation of a dendrogram's shape, color and content through functions such as rotate, prune, color_labels, color_branches, cutree, and more. These can be plotted in based R and ggplot2.

dendextend also provides the tools for comparing the similarity of two dendrograms to one another: either graphically (using a tanglegram plot, or Bk plots), or statistically (with Cophenetic correlation, Baker's Gamma, etc) - while enabling bootstrap and permutation tests for comparing the trees. The dendextendRcpp package provides C++ faster implementations for some of the more computationally intensive functions.

Authors who are presenting talks have a * after their name.

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