Using ggtree to Visualize Data on Tree‐Like Structures

By Guangchuang Yu. Current Protocols in Bioinformatics, 2020

1,254 citations recorded by the source corpus.

Ggtree is an R/Bioconductor package for visualizing tree‐like structures and associated data. After 5 years of continual development, ggtree has been evolved as a package suite that contains treeio for tree data input and output, tidytree for tree data manipulation, and ggtree for tree data visualization. Ggtree was originally designed to work with phylogenetic trees, and has been expanded to support other tree‐like structures, which extends the application of ggtree to present tree data in other disciplines. This article contains five basic protocols describing how to visualize trees using the grammar of graphics syntax, how to visualize hierarchical clustering results with associated data, how to estimate bootstrap values and visualize the values on the tree, how to estimate continuous and discrete ancestral traits and visualize ancestral states on the tree, and how to visualize a multiple sequence alignment with a phylogenetic tree. The ggtree package is freely available at https://www.bioconductor.org/packages/ggtree. © 2020 by John Wiley & Sons, Inc.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/81ff054b4f9f1d535098d55ff2ab0aa8709f5304

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. Li Zhan
2. Meijun Chen
3. Wenli Tang
4. Zehan Dai
5. Yi Guan
6. T. T. Lam
7. Shuangbin Xu
8. Xiao Luo

In Ecology, Evolution, Behavior and Systematics

1. Guangchuang Yu
2. Zehan Dai
3. Li Zhan
4. Meijun Chen
5. Wenli Tang
6. Yi Guan
7. T. T. Lam
8. Shuangbin Xu

In Molecular Biology

1. Guangchuang Yu
2. Zehan Dai
3. Li Zhan
4. Meijun Chen
5. Wenli Tang
6. Tianzhi Wu
7. Erqiang Hu
8. Yi Guan

Citations in the corpus

• iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria (2023, neutral): “4.1 package [73], with clades collapsed at the phylum level.”
• ggtreeExtra: Compact Visualization of Richly Annotated Phylogenetic Data (2021, methodology): “It allows us to visualize multiple associated data sets in different panels and serves as a general tool since there is no prerequisite for the input data type (Yu et al. 2018; Yu 2020).”
• Integrative approaches for species delimitation in Ascomycota (2021, methodology): “The result was visualized using ggtree (Yu 2020).”
• Ggtree: A serialized data object for visualization of a phylogenetic tree and annotation data (2022, methodology): “A ggtree object can be constructed using the ggtree function, which supports multiple tree ‐ like classes defined in R [6], such as phylo , phylo4 , pvclust , hclust , diana , phylog , phyloseq , and so forth.”