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相关论文: The coalescent and its descendants

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The coalescent is a stochastic process representing ancestral lineages in a population undergoing neutral genetic drift. Originally defined for a well-mixed population, the coalescent has been adapted in various ways to accommodate spatial,…

种群与进化 · 定量生物学 2024-07-02 Benjamin Allen , Alex McAvoy

Studying how diverse human populations are related is of historical and anthropological interest, in addition to providing a realistic null model for testing for signatures of natural selection or disease associations. Furthermore,…

种群与进化 · 定量生物学 2018-07-10 Jeffrey P. Spence , Matthias Steinrücken , Jonathan Terhorst , Yun S. Song

We propose in this article a brief description of the work, over almost a decade, resulting from a collaboration between mathematicians and biologists from four different research laboratories, identifiable as the co-authors of the articles…

种群与进化 · 定量生物学 2023-05-30 Olivier Mazet , Camille Noûs

Identifiability of evolutionary tree models has been a recent topic of discussion and some models have been shown to be non-identifiable. A coalescent-based rooted population tree model, originally proposed by Nielsen et al. 1998 [2], has…

种群与进化 · 定量生物学 2013-04-15 Arindam RoyChoudhury

In mathematical population genetics, it is well known that one can represent the genealogy of a population by a tree, which indicates how the ancestral lines of individuals in the population coalesce as they are traced back in time. As the…

概率论 · 数学 2014-02-20 Götz Kersting , Jason Schweinsberg , Anton Wakolbinger

Many population genetic models have been developed for the purpose of inferring population size and growth rates from random samples of genetic data. We examine two popular approaches to this problem, the coalescent and the…

种群与进化 · 定量生物学 2014-08-29 Erik M. Volz , Simon DW Frost

Coalescent theory combined with statistical modeling allows us to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. When sequences are sampled serially through…

种群与进化 · 定量生物学 2021-11-02 Michael D. Karcher , Marc A. Suchard , Gytis Dudas , Vladimir N. Minin

Compared to a neutral model, purifying selection distorts the structure of genealogies and hence alters the patterns of sampled genetic variation. Although these distortions may be common in nature, our understanding of how we expect…

种群与进化 · 定量生物学 2011-05-30 Aleksandra M. Walczak , Lauren E. Nicolaisen , Joshua B. Plotkin , Michael M. Desai

Recovery of population size history from molecular sequence data is an important problem in population genetics. Inference commonly relies on a coalescent model linking the population size history to genealogies. The high computational cost…

统计理论 · 数学 2018-01-17 James E. Johndrow , Julia A. Palacios

Recent improvements in high-throughput genotyping and sequencing technologies have afforded the collection of massive, genome-wide datasets of DNA information from hundreds of thousands of individuals. These datasets, in turn, provide…

种群与进化 · 定量生物学 2014-12-19 Pier Francesco Palamara

Widely used models in genetics include the Wright-Fisher diffusion and its moment dual, Kingman's coalescent. Each has a multilocus extension but under neither extension is the sampling distribution available in closed-form, and their…

概率论 · 数学 2015-06-24 Paul A. Jenkins , Paul Fearnhead , Yun S. Song

Kingman's coalescent is one of the most popular models in population genetics. It describes the genealogy of a population whose genetic composition evolves in time according to the Wright-Fisher model, or suitable approximations of it…

统计方法学 · 统计学 2018-04-20 Stefano Favaro , Shui Feng , Paul A. Jenkins

The development of coalescent theory paved the way to statistical inference from population genetic data. In the genomic era, however, coalescent models are limited due to the complexity of the underlying ancestral recombination graph. The…

种群与进化 · 定量生物学 2021-06-30 Julien Y. Dutheil

When an advantageous mutation occurs in a population, the favorable allele may spread to the entire population in a short time, an event known as a selective sweep. As a result, when we sample $n$ individuals from a population and trace…

概率论 · 数学 2007-05-23 Rick Durrett , Jason Schweinsberg

Study sample sizes in human genetics are growing rapidly, and in due course it will become routine to analyze samples with hundreds of thousands if not millions of individuals. In addition to posing computational challenges, such large…

种群与进化 · 定量生物学 2015-06-24 Anand Bhaskar , Andrew G. Clark , Yun S. Song

In population genetics, extant samples are usually used for inference of past population genetic forces. With the Kingman coalescent and the backward diffusion equation, inference of the marginal likelihood proceeds from an extant sample…

种群与进化 · 定量生物学 2020-04-03 Claus Vogl , Sandra Peer

Effective population size characterizes the genetic variability in a population and is a parameter of paramount importance in population genetics. Kingman's coalescent process enables inference of past population dynamics directly from…

统计方法学 · 统计学 2016-01-20 Mandev S. Gill , Philippe Lemey , Shannon N. Bennett , Roman Biek , Marc A. Suchard

We examine genetic statistics used in the study of structured populations. In a 1999 paper, Wakeley observed that the coalescent process associated with the finite island model can be decomposed into a scattering phase and a collecting…

种群与进化 · 定量生物学 2008-11-11 Sivan Leviyang

Population balance framework is a useful tool that can be used to describe size distribution of droplets in a liquid-liquid dispersion. Breakup and coalescence models provide closures for mathematical formulation of the population balance…

流体动力学 · 物理学 2015-11-25 Marcin Traczyk , Robert Sawko , Chris Thompson

We analyse sequential Markov coalescent algorithms for populations with demographic structure: for a bottleneck model, a population-divergence model, and for a two-island model with migration. The sequential Markov coalescent method is an…

种群与进化 · 定量生物学 2025-10-01 A. Eriksson , B. Mahjani , B. Mehlig
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