Applications of Dendrograms
Genetics: Dendrograms are widely used in genetics to analyze DNA sequences and determine evolutionary relationships between species or individuals.
Market Segmentation: In marketing, dendrograms can be used to group customers or products based on similarities in their purchasing behavior or characteristics.
Phylogenetics: Biologists use dendrograms to construct evolutionary trees and understand the evolutionary history of species.
The hierarchical clustering of the data may be learned a lot by adding a dendrogram to a R ggplot2 heatmap. The ggtree package, which enables the addition of dendrograms to ggplot2 displays, can be used to accomplish this. A step-by-step tutorial for adding a dendrogram to a ggplot2 heatmap is provided below:
Hierarchical Clustering: Hierarchical clustering is a method that organizes data points into a hierarchical tree-like structure called a dendrogram. It is commonly used to group similar observations together based on their similarity or dissimilarity.
Adding a Dendrogram to a ggplot2 Heatmap in R
A potent technique that improves the visualisation of hierarchical clustering patterns inside data is to add a dendrogram to a ggplot2 heatmap in R. Dendrograms shed light on the connections and resemblances among data points, assisting in the discovery of distinct clusters or groups. We will examine how to combine dendrograms with ggplot2 heatmaps using R in this article, enabling a more thorough comprehension of intricate data structures and patterns.