Data from: Phylogenetic signal and noise: predicting the power of a data set to resolve phylogeny

A principal objective for phylogenetic experimental design is to predict
the power of a dataset to resolve nodes in a phylogenetic tree. However,
proactively assessing the potential for phylogenetic noise compared to
signal in a candidate dataset has been a formidable challenge.
Understanding the impact of collection of additional sequence data to
resolve recalcitrant internodes at diverse historical times will
facilitate increasingly accurate and cost-effective phylogenetic research.
Here, we derive theory based on the fundamental unit of the phylogenetic
tree, the quartet, that applies estimates of the state space and the rates
of evolution of characters in a dataset to predict phylogenetic signal and
phylogenetic noise and therefore to predict the power to resolve
internodes. We develop and implement a Monte Carlo approach to estimating
power to resolve as well as deriving a nearly equivalent, faster
deterministic calculation. These approaches are applied to describe the
distribution of potential signal, polytomy, or noise for two example
datasets, one recent (CO1 and 28S sequences from Diplazontinae parasitoid
wasps) and one deep (eight nuclear genes and a phylogenomic sequence for
diverse microbial eukaryotes including Stramenopiles, Alveolata, and
Rhizaria). The predicted power of resolution for the loci analyzed is
consistent with the historic use of the genes in phylogenetics.