For instance, the data could be the geographic positions of the sampled avian influenza viruses (informed by the survey locations) and the ancestral nodes (by phylogeographic inference) in the viral gene tree ( Lam et al., 2012). that are associated with the taxa from real samples, or with the internal nodes representing hypothetic ancestor strain/species, or with the tree branches indicating evolutionary time courses ( Wang et al., 2020). These data could come from users or analysis programs and might include evolutionary rates, ancestral sequences, etc. The ggtree package ( Yu et al., 2017) is designed for annotating phylogenetic trees with their associated data of different types and from various sources. The ggtree package also inherits versatile properties of ggplot2, and more importantly allows constructing complex tree figures by freely combining multiple layers of annotations (see also Chapter 5) using the tree associated data imported from different sources (see detailed in Chapter 1 and ( Wang et al., 2020)).Ĥ.2 Visualizing Phylogenetic Tree with ggtree However, these packages were designed for epidemiology and microbiome data respectively and did not aim to provide a general solution for tree visualization and annotation. The ggplot2 system of graphics allows rapid customization and exploration of design solutions. OutbreakTools ( Jombart et al., 2014) and phyloseq ( McMurdie & Holmes, 2013) extended ggplot2 to plot phylogenetic trees. However, the base graphics system is relatively difficult to extend and limits the complexity of the tree figure to be displayed. In particular, ape is one of the fundamental packages for phylogenetic analysis and data processing. Some packages, including ape ( Paradis et al., 2004) and phytools ( Revell, 2012), which are capable of displaying and annotating trees, are developed using the base graphics system of R. Most of the R packages in phylogenetics focus on specific statistical analyses rather than viewing and annotating the trees with more generalized phylogeny-associated data. However, a comprehensive package, designed for viewing and annotating phylogenetic trees, particularly with complex data integration, is not yet available. The R language is increasingly used in phylogenetics. The ggtree is built to work with treedata objects (see Chapters 1 and 9), and display tree graphics with the ggplot2 package ( Wickham, 2016) that was based on the grammar of graphics ( Wilkinson et al., 2005). To fill this gap, we developed ggtree ( Yu et al., 2017), a package for the R programming language ( R Core Team, 2016) released under the Bioconductor project ( Gentleman et al., 2004). Therefore, in addition to standalone applications that focus on each of the specific analysis and data types, researchers studying molecular evolution need a robust and programmable platform that allows the high levels of integration and visualization of many of these different aspects of data (raw or from other primary analyses) over the phylogenetic trees to identify their associations and patterns. For instance, the influenza virus has a wide host range, diverse and dynamic genotypes, and characteristic transmission behaviors that are mostly associated with the virus’s evolution and essentially among themselves. As phylogenetic trees are becoming more widely used in multidisciplinary studies, there is an increasing need to incorporate various types of phylogenetic covariates and other associated data from different sources into the trees for visualizations and further analyses. However, their pre-defined annotating functions are usually limited to some specific phylogenetic data. Only a few of them, such as FigTree, TreeDyn and iTOL, allow users to annotate the trees with colored branches, highlighted clades with tree features.
Xy high phlo low software#
There are many software packages and web tools that are designed for displaying phylogenetic trees, such as TreeView ( Page, 2002), FigTree, TreeDyn ( Chevenet et al., 2006), Dendroscope ( Huson & Scornavacca, 2012), EvolView ( He et al., 2016), and iTOL ( Letunic & Bork, 2007), etc.
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