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November 20, 2025Molecular Biology and EvolutionOpen Access

Bayesian model-averaging of parametric coalescent models for phylodynamic inference

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Authors

YXYuan XuKCKylie ChenDXDong Xie

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Overview

Bayesian model-averaging demonstrates accurate demographic histories in metastatic colorectal cancer and viral populations, suggesting new insights.

Key Points

  • This research aims to improve the inference of population histories using Bayesian model-averaging of parametric coalescent models.
  • Introduced a Bayesian Model Averaging framework for integrating multiple demographic models.
  • Utilized Metropolis-coupled MCMC for effective sampling among candidate growth functions.
  • Applied the framework to real datasets including Egyptian Hepatitis C virus and metastatic colorectal cancer sequences.
  • Successfully identified models of rapid population expansion in HCV sequences with a preference for Gompertz-like models.
  • Revealed plausible exponential-like growth patterns in metastatic colorectal cancer, indicating maintained proliferative capacity.

Cite This Study

Xu et al. (2025) studied this question.

synapsesocial.com/papers/6924f08cc0ce034ddc350678https://doi.org/10.1093/molbev/msaf297
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