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Updated: Jan 19, 2026
02:34
Arrhenius Plot: Determining Activation Energy of a Reaction
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The multifurcating skyline plot
Patrick Hoscheit1, Oliver G Pybus2
1MaIAGE, INRA, Université Paris-Saclay, Domaine de Vilvert, Jouy-en-Josas 78350, France.
Virus Evolution
|September 19, 2019
Summary
This study introduces the multifurcating skyline plot, a new method for analyzing demographic history using gene sequences. It accurately estimates population size changes over time, even with complex phylogenetic trees and superspreading events.
Area of Science:
- Population Genetics
- Phylogenetics
- Epidemiology
Background:
- Coalescent theory methods infer demographic history from gene sequences.
- Skyline plots are common Bayesian priors for phylogenetic trees in pathogen analysis.
Purpose of the Study:
- Extend skyline plot methods to phylogenies with multifurcations (hard polytomies).
- Develop the multifurcating skyline plot using Λ-coalescents to estimate effective population size through time.
Main Methods:
- Utilized Λ-coalescents theory to develop the multifurcating skyline plot.
- Implemented smoothing and extended the method for serially sampled (heterochronous) data.
- Validated the estimator on simulated data using maximum likelihood.
Main Results:
- Accurate estimation of Λ-coalescent process parameters on simulated data.
- Application to superspreading models showed consistency with high-variance assumptions.
- Estimated Λ-coalescent parameters provide insights into superspreading levels.
Conclusions:
- The multifurcating skyline plot effectively estimates demographic history from complex phylogenies.
- The method is robust and provides valuable information for epidemiological studies, particularly those involving superspreading.
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