BEAST X for Bayesian phylogenetic, phylogeographic and phylodynamic inference

2025/07/07 by Guy Baele, Xiang Ji, Gabriel W. Hassler +8 · 2 voices · 22 citations
Earth and Planetary Sciences · Biochemistry, Genetics and Molecular Biology · #Evolution and Paleontology Studies #Genomics and Phylogenetic Studies #Genetic diversity and population structure

paper · pdf · doi:10.1038/s41592-025-02751-x

Abstract

Here we present the open-source and cross-platform BEAST X software that combines molecular phylogenetic reconstruction with complex trait evolution, divergence-time dating and coalescent demographics in an efficient statistical inference engine. BEAST X significantly advances the flexibility and scalability of evolutionary models supported. Novel clock and substitution models leverage a large variety of evolutionary processes; discrete, continuous and mixed traits with missingness and measurement errors; and fast, gradient-informed integration techniques that rapidly traverse high-dimensional parameter spaces.

Cited by

• Protein Structural Phylogenetics
• Unravelling the epidemiological and dispersal dynamics of the 2024-2025 chikungunya virus epidemic on Réunion island
• BEAGLE 4.1: A high-performance library for computation on phylogenetic trees across diverse parallel architectures
• Information on hidden birth events restores identifiability in phylodynamic inference
• Assessing the Validity of the Fixed Tree Topology Assumption in Phylodynamic Inference
• Amortized Phylodynamic Inference with Neural Bayes Estimators and Recursive Neural Networks
• Coalescent Inference for Epidemics with Latent Periods
• RNA virus genomes from centuries- to millennia-old Adélie penguin mummies
• Generalizing matrix representations to fully heterochronous ranked tree shapes
• DiagnoDating: diagnostics for dated phylogenies in microbial population genetics
• Navigating Sampling Bias in Discrete Phylogeographic Analysis: Assessing the Performance of an Adjusted Bayes Factor
• The Phylodynamic Threshold of Measurably Evolving Populations
• Inhomogeneous continuous-time Markov chains to infer flexible time-varying evolutionary rates
• Using drift coefficients as a basis for inferring times, effective population sizes, and genetic adaptations
• Revisiting Algorithms, Tools, and Applications for Sequence and Phylogenetic Analyses in the NGS-Based Omics Era
• Evolutionary history of Jamestown Canyon virus reveals complex multi-vector ecology
• Parallel algorithms for phylogenetic inference under a structured coalescent approximation
• Phylogenetic Inference from Atomized 3D Morphometric Data: A Case Study using Kangaroos
• HIPSTR: highest independent posterior subtree reconstruction in TreeAnnotator X
• DNA barcoding of Messor ants of Bulgaria with insights into their taxonomic diversity
• Dispersal, adaptation and persistence of H5N1 in the sub-Antarctic and Antarctica
• Scalable Generative Modeling of Weighted Graphs

Discussions

• BEAST X accelerates Bayesian phylogenetic and phylodynamic inference with enhanced scalability and geo spread modeling. #BEASTX #Phylodynamics #VirusEvolution 👤EVBC: Philippe Lemey 🔗 [bsky, 17 points, 0 comments]
• Can also read a paper about Beast X here: doi.org/10.1038/s415... [bsky, 7 points, 0 comments]

Related

• piBUSS: a parallel BEAST/BEAGLE utility for sequence simulation under complex evolutionary scenarios
• RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language
• Phylotrack: C++ and Python libraries for in silico phylogenetic tracking
• Online Bayesian phylodynamic inference in BEAST with application to epidemic reconstruction
• E<scp>vo</scp>P<scp>hylo</scp>: An <scp>r</scp> package for pre‐ and postprocessing of morphological data from relaxed clock Bayesian phylogenetics