Evidence map›Paper›PMID 39976412›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2025

Multiple merger coalescent inference of effective population size.

Julie Zhang, Julia A Palacios

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Rare variation in malaria parasites biases population-genetic inference.bioRxiv : the preprint server for biology · 2026
    Article
  2. "A mathematical theory of evolution": phylogenetic models dating back 100 years.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Article
  3. Multiple merger coalescent inference of effective population size.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Julie ZhangDepartment of Statistics, Stanford University, CA 94305, USA.ORCID 0000-0002-1384-1517
Julia A PalaciosDepartment of Statistics, Stanford University, CA 94305, USA.ORCID 0000-0003-4501-7378

Funding

Novel Coalescent Approaches for Studying Evolutionary ProcessesR35GM148338 · NIGMS · STANFORD UNIVERSITY · PI Julia Palacios · 2023 to 2026
$1.5M
National Science FoundationNIGMS NIH HHS R35 GM148338NIH HHS
6 · The paper itself

Abstract

Variation in a sample of molecular sequence data informs about the past evolutionary history of the sample's population. Traditionally, Bayesian modelling coupled with the standard coalescent is used to infer the sample's bifurcating genealogy and demographic and evolutionary parameters such as effective population size and mutation rates. However, there are many situations where binary coalescent models do not accurately reflect the true underlying ancestral processes. Here, we propose a Bayesian non-parametric method for inferring effective population size trajectories from a multifurcating genealogy under the [Formula: see text]-coalescent. In particular, we jointly estimate the effective population size and the model parameter for the Beta-coalescent model, a special type of [Formula: see text]-coalescent. Finally, we test our methods on simulations and apply them to study various viral dynamics as well as Japanese sardine population size changes over time. The code and vignettes can be found in the phylodyn package.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Indexed as

Models, GeneticPhylogenyPopulation DensityBayes TheoremBiological EvolutionGenetics, PopulationBeta-coalescentGaussian processesLambda-coalescentMultiple mergers coalescent

Identifiers

PMID39976412
PMCPMC11867189

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.