DOI: 10.5061/dryad.s342d
title: Data from: More on the best evolutionary rate for phylogenetic analysis

description: The accumulation of genome-scale molecular datasets for non-model taxa
 brings us ever closer to resolving the tree of life of all living
 organisms. However, despite the depth of data available, a number of
 studies that each used thousands of genes have reported conflicting
 results. The focus of phylogenomic projects must thus shift to more
 careful experimental design. Even though we still have a limited
 understanding of what are the best predictors of the phylogenetic
 informativeness of a gene, there is wide agreement that one key factor is
 its evolutionary rate; but there is no consensus as to whether the rates
 derived as optimal in various analytical, empirical, and simulation
 approaches have any general applicability. We here use simulations to
 infer optimal rates in a set of realistic phylogenetic scenarios with
 varying tree sizes, numbers of terminals, and tree shapes. Furthermore, we
 study the relationship between the optimal rate and rate-variation among
 sites and among lineages. Finally, we examine how well the predictions
 made by a range of experimental-design methods correlate with the observed
 performance in our simulations. We find that the optimal level of
 divergence is surprisingly robust to differences in taxon sampling and
 even to among-site and among-lineage rate variation as often encountered
 in empirical datasets. This finding encourages the use of methods that
 rely on a single optimal rate to predict a gene’s utility. Focusing on
 correct recovery either of the most basal node in the phylogeny or of the
 entire topology, the optimal rate is about 0.45 substitutions from root to
 tip in average Yule trees and about 0.2 in difficult trees with short
 basal and long apical branches, but all rates leading to divergence levels
 between about 0.1 and 0.5 perform reasonably well.Testing the performance
 of six methods that can be used to predict a gene’s utility against our
 simulation results, we find that the probability of resolution,
 signal-noise analysis, and Fisher information are good predictors of
 phylogenetic informativeness, but they require specification of at least
 part of a model tree. Likelihood quartet mapping also shows very good
 performance, but only requires sequence alignments and is thus applicable
 without making assumptions about the phylogeny. Despite them being the
 most commonly used methods for experimental design, geometric quartet
 mapping and the integration of phylogenetic informativeness curves perform
 rather poorly in our comparison. Instead of derived predictors of
 phylogenetic informativeness, we suggest that the number of sites in a
 gene that evolve at near-optimal rates (as inferred here) could be used
 directly to prioritize genes for phylogenetic inference. In combination
 with measures of model fit, especially with respect to compositional
 biases and among-site and among-lineage rate variation, such an approach
 has the potential to greatly improve marker choice and should be tested on
 empirical data.
description: Supplementary_File_1_ScriptsR scripts and simulation trees. Explanations are given in the file "Overview_Scripts.pdf"Supplementary_File_2_Nb_of_QuartetsTable containing the number of quartets needed for likelihood and geometric quartet mapping to get below a certain threshold of the final tree-likeness value, under different phylogenetic settings.Supplementary_File_3_Influence_NbBpFigure detailing the influence of the number of base pairs sampled on the best evolutionary rate.