High-performance computing in Bayesian Phylogenetics and Phylodynamics using BEAGLE

Guy Baele, Daniel L. Ayres, Andrew Rambaut, Marc A. Suchard, Philippe Lemey

Research output: Chapter in Book/Report/Conference proceedingChapter


In this chapter, we focus on the computational challenges associated with statistical phylogenomics and how use of the broad-platform evolutionary analysis general likelihood evaluator (BEAGLE), a high-performance library for likelihood computation, can help to substantially reduce computation time in phylogenomic and phylodynamic analyses. We discuss computational improvements brought about by the BEAGLE library on a variety of state-of-the-art multicore hardware, and for a range of commonly used evolutionary models. For data sets of varying dimensions, we specifically focus on comparing performance in the Bayesian evolutionary analysis by sampling trees (BEAST) software between multicore central processing units (CPUs) and a wide range of graphics processing cards (GPUs). We put special emphasis on computational benchmarks from the field of phylodynamics, which combines the challenges of phylogenomics with those of modelling trait data associated with the observed sequence data. In conclusion, we show that for increasingly large molecular sequence data sets, GPUs can offer tremendous computational advancements through the use of the BEAGLE library, which is available for software packages for both Bayesian inference and maximum-likelihood frameworks.
Original languageEnglish
Title of host publicationEvolutionary Genomics
Subtitle of host publicationStatistical and Computational Methods
ISBN (Electronic)978-1-4939-9074-0
ISBN (Print)978-1-4939-9073-3
Publication statusPublished - 6 Jul 2019

Publication series

NameMethods in Molecular Biology


  • Adaptive Markov chain Monte Carlo
  • Multipartite data
  • Generalized linear model
  • High-performance computing
  • Pathogen phylodynamics
  • Data integration
  • Bayesian phylogenetics
  • Phylogenomics


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