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Related Experiment Videos

Bayesian Estimation of Population Size Changes by Sampling Tajima's Trees.

Julia A Palacios1,2, Amandine Véber3, Lorenzo Cappello4

  • 1Department of Statistics, Stanford University, California 94305 juliapr@stanford.edu.

Genetics
|September 13, 2019
PubMed
Summary

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This summary is machine-generated.

We introduce Tajima's coalescent, a computationally efficient Bayesian method for inferring past population sizes. This novel approach, implemented in the R package phylodyn, offers an accurate alternative to Kingman's coalescent for population genetics studies.

Area of Science:

  • Population Genetics
  • Computational Biology
  • Bioinformatics

Background:

  • Inference of past population sizes is crucial for understanding evolutionary dynamics.
  • Kingman's coalescent, a standard model, faces computational challenges due to its large state space.
  • Efficient methods are needed to overcome these hurdles in population genetics research.

Purpose of the Study:

  • To present a novel Bayesian approach for inferring past population sizes using Tajima's coalescent.
  • To develop a computationally efficient alternative to Kingman's coalescent.
  • To validate the accuracy and efficiency of the new method against existing approaches.

Main Methods:

  • Development of Tajima's coalescent, a lower-resolution coalescent process with a smaller state space.
Keywords:
Bayesian nonparametricsTajima coalescentcoalescenteffective population size

Related Experiment Videos

  • Implementation of a new algorithm for efficient and exact likelihood calculations using directed acyclic graphs and Markov Chain Monte Carlo (MCMC).
  • Comparison of the Bayesian Estimation of population size changes by Sampling Tajima's Trees (BESTT) method with BEAST using simulated and human genetic data.

    • Main Results:

    • Tajima's coalescent significantly reduces the state space, leading to more computationally efficient inference.
    • The BESTT method demonstrates accurate inference of effective population sizes.
    • BESTT provides a viable and efficient alternative to the standard Kingman's coalescent.

    Conclusions:

    • Tajima's coalescent offers a computationally advantageous model for population genetics inference.
    • The BESTT method provides an accurate and efficient tool for reconstructing past population size changes.
    • The phylodyn R package facilitates the application of these novel algorithms in population genetics research.