Summary: The assessment of novel phylogenetic models and inference methods is routinely being conducted via experiments on simulated as well as empirical data. When generating synthetic data it is often unclear how to set simulation parameters for the models and generate trees that appropriately reflect empirical model parameter distributions and tree shapes. As a solution, we present and make available a new database called 'RAxML Grove' currently comprising more than 60 000 inferred trees and respective model parameter estimates from fully anonymized empirical datasets that were analyzed using RAxML and RAxML-NG on two web servers. We also describe and make available two simple applications of RAxML Grove to exemplify its usage and highlight its utility for designing realistic simulation studies and analyzing empirical model parameter and tree shape distributions.
Availability and implementation: RAxML Grove is freely available at https://github.com/angtft/RAxMLGrove.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2021. Published by Oxford University Press.