CMAPLE: Efficient Phylogenetic Inference in the Pandemic Era

Mol Biol Evol. 2024 Jul 3;41(7):msae134. doi: 10.1093/molbev/msae134.

Abstract

We have recently introduced MAPLE (MAximum Parsimonious Likelihood Estimation), a new pandemic-scale phylogenetic inference method exclusively designed for genomic epidemiology. In response to the need for enhancing MAPLE's performance and scalability, here we present two key components: (i) CMAPLE software, a highly optimized C++ reimplementation of MAPLE with many new features and advancements, and (ii) CMAPLE library, a suite of application programming interfaces to facilitate the integration of the CMAPLE algorithm into existing phylogenetic inference packages. Notably, we have successfully integrated CMAPLE into the widely used IQ-TREE 2 software, enabling its rapid adoption in the scientific community. These advancements serve as a vital step toward better preparedness for future pandemics, offering researchers powerful tools for large-scale pathogen genomic analysis.

Keywords: epidemiology; maximum likelihood; models of sequence evolution; phylogenetics; phylogenomics.

MeSH terms

  • Algorithms
  • Humans
  • Likelihood Functions
  • Pandemics
  • Phylogeny*
  • Software*