We usually use text to label taxa, i.e. displaying taxa names. If the text is the image file name (either local or remote), ggtree can read the image and display the actual image as the label of the taxa (Figure 8.1). The
geom_nodelab() are capable to render silhouette images by internally called the ggimage package.
Online tools such as iTOL (Letunic and Bork 2007) and EvolView (Zilong He et al. 2016) support displaying subplots on a phylogenetic tree. However only bar and pie charts are supported by these tools. Users may want to visualize node-associated data with other visualization methods, such as violin plot (Grubaugh et al. 2017), venn diagram (Lott et al. 2015), sequence logo, etc., and display them on the tree. In ggtree, all kinds of subplots are supported as we can export all subplots to image files and use them to label corresponding nodes on the tree.
library(ggimage) library(ggtree) nwk <- paste0("((((bufonidae, dendrobatidae), ceratophryidae),", "(centrolenidae, leptodactylidae)), hylidae);") imgdir <- system.file("extdata/frogs", package = "TDbook") x = read.tree(text = nwk) ggtree(x) + xlim(NA, 7) + ylim(NA, 6.2) + geom_tiplab(aes(image=paste0(imgdir, '/', label, '.jpg')), geom="image", offset=2, align=2, size=.2) + geom_tiplab(geom='label', offset=1, hjust=.5) + geom_image(x=.8, y=5.5, image=paste0(imgdir, "/frog.jpg"), size=.2)
Phylopic contains more than 3200 silhouettes and covers almost all life forms. The ggtree package supports using phylopic13 to annotate the tree by setting
geom="phylopic" and mapping phylopic UID to the
image aesthetics. The ggimage package supports querying phylopic UID from the scientific name, which is very handy for annotating tree with phylopic. In the following example, tip labels were used to query phylopic UID and phylopic images were used to label the tree as another layer of tip labels. Most importantly, we can color or resize the images using numerical/categorical variables and here the values of body mass were used to encode the color of the images (Figure 8.2).
library(ggtree) newick <- paste0("((Pongo_abelii,(Gorilla_gorilla_gorilla,(Pan_paniscus,", "Pan_troglodytes)Pan,Homo_sapiens)Homininae)Hominidae,", "Nomascus_leucogenys)Hominoidea;") tree <- read.tree(text=newick) d <- ggimage::phylopic_uid(tree$tip.label) d$body_mass <- c(52, 114, 47, 45, 58, 6) p <- ggtree(tree) %<+% d + geom_tiplab(aes(image=uid, colour=body_mass), geom="phylopic", offset=2.5) + geom_tiplab(aes(label=label), offset = .2) + xlim(NA, 7) + scale_color_viridis_c()
The ggtree package provides a layer,
geom_inset(), for adding subplots to a phylogenetic tree. The input is a named list of
ggplot graphic objects (can be any kind of chart). These objects should be named by node numbers. Users can also use ggplotify to convert plots generated by other functions (even implemented by base graphics) to
ggplot objects, which can then be used in the
geom_inset() layer. To facilitate adding bar and pie charts (e.g. summarized stats of results from ancestral reconstruction) to the phylogenetic tree, ggtree provides the
nodebar() functions to create a list of pie or bar charts.
This example uses
ape::ace() function to estimate ancestral character states. The likelihoods of the stats were visualized as stacked bar charts which were overlayed onto internal nodes of the tree using the
geom_inset() layer (Figure 8.3A).
library(phytools) data(anoletree) x <- getStates(anoletree,"tips") tree <- anoletree cols <- setNames(palette()[1:length(unique(x))],sort(unique(x))) fitER <- ape::ace(x,tree,model="ER",type="discrete") ancstats <- as.data.frame(fitER$lik.anc) ancstats$node <- 1:tree$Nnode+Ntip(tree) ## cols parameter indicate which columns store stats bars <- nodebar(ancstats, cols=1:6) bars <- lapply(bars, function(g) g+scale_fill_manual(values = cols)) tree2 <- full_join(tree, data.frame(label = names(x), stat = x ), by = 'label') p <- ggtree(tree2) + geom_tiplab() + geom_tippoint(aes(color = stat)) + scale_color_manual(values = cols) + theme(legend.position = "right") + xlim(NA, 8) p1 <- p + geom_inset(bars, width = .08, height = .05, x = "branch")
x position can be one of ‘node’ or ‘branch’ and can be adjusted by the parameters,
vjust, for horizontal and vertical adjustment respectively. The
height parameters restict the size of the inset plots.
Similarly, users can use the
nodepie() function to generate a list of pie charts and place these charts to annotate corresponding nodes (Figure 8.3B). Both
nodepie() accept a parameter of
alpha to allow transparency.
pies <- nodepie(ancstats, cols = 1:6) pies <- lapply(pies, function(g) g+scale_fill_manual(values = cols)) p2 <- p + geom_inset(pies, width = .1, height = .1) plot_list(p1, p2, guides='collect', tag_levels='A')
geom_inset() layer accepts a list of ‘ggplot’ graphic objects and these input objects are not restricted to pie or bar charts. They can be any kind of charts or hybrid of these charts. The
geom_inset() is not only useful to display ancestral stats, but also applicable to visualize different types of data that are associated to selected nodes in the tree. Here, we use a mixure of pie and bar charts to annotate the tree as an example (Figure 8.4).
pies_and_bars <- pies i <- sample(length(pies), 20) pies_and_bars[i] <- bars[i] p + geom_inset(pies_and_bars, width=.08, height=.05)
Phylomoji is a phylogenetic tree of emoji. It is fun14 and very useful for education of the evolution concept. The ggtree supports producing phylomoji since 201515. Here, we will use ggtree to recreate the following phylomoji figure16:
library(ggplot2) library(ggtree) tt = '((snail,mushroom),(((sunflower,evergreen_tree),leaves),green_salad));' tree = read.tree(text = tt) d <- data.frame(label = c('snail','mushroom', 'sunflower', 'evergreen_tree','leaves', 'green_salad'), group = c('animal', 'fungi', 'flowering plant', 'conifers', 'ferns', 'mosses')) p <- ggtree(tree, linetype = "dashed", size=1, color='firebrick') %<+% d + xlim(0, 4.5) + ylim(0.5, 6.5) + geom_tiplab(parse="emoji", size=15, vjust=.25) + geom_tiplab(aes(label = group), geom="label", x=3.5, hjust=1)
Note that the output may depend on what emoji fonts is installed in your system17.
With ggtree, it is easy to generate phylomoji. The emoji is treated as text, like ‘abc.’ We can use emojis to label taxa, clade, color and rotate emoji with any given color and angle. This functionality is internally supported by the emojifont package.
p <- ggtree(tree, layout = "circular", size=1) + geom_tiplab(parse="emoji", size=10, vjust=.25) print(p) ## fan layout p2 <- open_tree(p, angle=200) print(p2) p2 %>% rotate_tree(-90)
Parsing clade labels as emojis is also supported in the
geom_cladelab() layer. For example, in a phylogenetic tree of influenza viuses, we can use emojis to label clades to represent host species similar to Figure 8.7.
set.seed(123) tr <- rtree(30) dat <- data.frame( node = c(41, 53, 48), name = c("chicken", "duck", "family") ) p <- ggtree(tr) + xlim(NA, 5.2) + geom_cladelab( data = dat, mapping = aes( node = node, label = name, color = name ), parse = "emoji", fontsize = 12, align = TRUE, show.legend = FALSE ) + scale_color_manual( values = c( chicken="firebrick", duck="steelblue", family = "darkkhaki" ) ) p
R’s graphical devices don’t support
AppleColorEmoji font on MacOS, it’s still possible to use it. We can export the
plot to a
svg file and render it in
library(ggtree) tree_text <- paste0("(((((cow, (whale, dolphin)), (pig2, boar)),", "camel), fish), seedling);") x <- read.tree(text=tree_text) library(ggimage) p <- ggtree(x, size=2) + geom_tiplab(size=20, parse='emoji') + xlim(NA, 7) + ylim(NA, 8.5) svglite::svglite("emoji.svg", width = 10, height = 7) print(p) dev.off() # or use `grid.export()` # ps = gridSVG::grid.export("emoji.svg", addClass=T)
Producing phylomoji as an ASCII art is also possible. Users can refer to Appendix D for details.
The ggtree supports parsing labels, including tip labels, internal node labels, and clade labels, as images, math expression, and emoji, in case the labels can be parsed as image file names,
plotmath expression, or emoji names respectively. It can be fun, but it’s also very useful for scientific research. The use of images on phylogenetic trees can help to present species-related characteristics, including morphological, anatomical, and even macromolecular structures. Moreover, ggtree supports summarizing statistical inferences (e.g., biogeographic range reconstruction and posterior distribution) or associated data of the nodes as subplots to be displayed on a phylogenetic tree.