Plot with ggtree

Here is an example of how the results can be plotted using ggtree in R.

Tree file

First, we load the necessary modules, read in the tree file, and do a quick analysis. We assume that we know the total number of extant species, and using that we can calculate the sampling fraction.

using Pesto

phy = readtree(Pesto.path("primates.tre"))
sampling_fraction = 0.635
primates = SSEdata(phy, sampling_fraction)
model, rates = pesto(primates)
nothing # hide

Tree plots in Makie

If we want to plot the results immediately, we will need to use the Makie dependency. Makie has several backends, but we will use CairoMakie for now, as it is designed to plot high-quality 2-dimensional figures.

using Makie, CairoMakie

treeplot(primates, rates)

Tree plots in ggtree

The plotting functionality include in Pesto is intended as an interactive tool, and its functionality is rather rudimentary. If you wish to make a publication-quality plot, we recommend instead to use a more established, well-tested and feature-rich library especially for this purpose. A good choice is to use the ggtree library in R, although other libraries could be used as well. In Pesto, we provide functionality to save the results as a Newick string with metadata for each node. If we want to save the newick string to a file, we can use the writenewick function

writenewick("primates_analysis.tre", primates, rates)

This tree file can be loaded in other programs such as R and can be opened using standard packages like ape and treeio or any other software that can handle extended Newick trees.

library(treeio)
phy <- treeio::read.beast.newick("primates_analysis.tre")

library(ggplot2)
library(ggtree)
p1 <- ggtree(td, aes(color = mean_lambda)) +  
    geom_tiplab(size=2) +
    labs(color = "Mean speciation rate")