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There are few, if any, algorithms in statistical phylogenetics which are used more heavily than Felsenstein's 1973 pruning method for computing the likelihood of a tree. We present LvD, (Likelihood via Decomposition), an alternative to…

Populations and Evolution · Quantitative Biology 2026-01-28 David Bryant , Celine Scornavacca , David Swofford

We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele frequency dynamics…

Populations and Evolution · Quantitative Biology 2019-09-18 Marnus Stoltz , Boris Bauemer , Remco Bouckaert , Colin Fox , Gordon Hiscott , David Bryant

Phylogeny is the field of modelling the temporal discrete dynamics of speciation. Complex models can nowadays be studied using the Approximate Bayesian Computation approach which avoids likelihood calculations. The field's progression is…

Populations and Evolution · Quantitative Biology 2020-11-23 Krzysztof Bartoszek , Pietro Liò

The evolution of molecular and phenotypic traits is commonly modelled using Markov processes along a phylogeny. This phylogeny can be a tree, or a network if it includes reticulations, representing events such as hybridization or admixture.…

Populations and Evolution · Quantitative Biology 2024-08-28 Benjamin Teo , Paul Bastide , Cécile Ané

Discovering evolutionary traits that are heritable across species on the tree of life (also referred to as a phylogenetic tree) is of great interest to biologists to understand how organisms diversify and evolve. However, the measurement of…

Inferring concerted changes among biological traits along an evolutionary history remains an important yet challenging problem. Besides adjusting for spurious correlation induced from the shared history, the task also requires sufficient…

We present the first sub-quadratic time algorithm that with high probability correctly reconstructs phylogenetic trees for short sequences generated by a Markov model of evolution. Due to rapid expansion in sequence databases, such very…

Populations and Evolution · Quantitative Biology 2012-06-01 Daniel G. Brown , Jakub Truszkowski

Inferring dependencies between complex biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible when trait and specimen counts grow large. The…

We present an extension of Felsenstein's algorithm to indel models defined on entire sequences, without the need to condition on one multiple alignment. The algorithm makes use of a generalization from probabilistic substitution matrices to…

Populations and Evolution · Quantitative Biology 2014-10-24 Oscar Westesson , Gerton Lunter , Benedict Paten , Ian Holmes

We present an algorithm for phylogenetic reconstruction using quartets that returns the correct topology for $n$ taxa in $O(n \log n)$ time with high probability, in a probabilistic model where a quartet is not consistent with the true…

Populations and Evolution · Quantitative Biology 2010-10-12 Daniel G. Brown , Jakub Truszkowski

Comparative and evolutive ecologists are interested in the distribution of quantitative traits among related species. The classical framework for these distributions consists of a random process running along the branches of a phylogenetic…

Applications · Statistics 2017-08-24 Paul Bastide , Mahendra Mariadassou , Stéphane Robin

Phylogenetic trait evolution models allow for the estimation of evolutionary correlations between a set of traits observed in a sample of related organisms. By directly modeling the evolution of the traits along an estimable phylogenetic…

Many biological characteristics of evolutionary interest are not scalar variables but continuous functions. Given a dataset of function-valued traits generated by evolution, we develop a practical statistical approach to infer ancestral…

Phylogenetic trees describe the relationships between species in the evolutionary process, and provide information about the rates of diversification. To understand the mechanisms behind macroevolution, we consider a class of multitype…

Populations and Evolution · Quantitative Biology 2024-10-07 Mingqi He , Sophie Hautphenne , Yao-ban Chan

Gene gain-loss-duplication models are commonly based on continuous-time birth-death processes. Employed in a phylogenetic context, such models have been increasingly popular in studies of gene content evolution across multiple genomes.…

Populations and Evolution · Quantitative Biology 2021-07-27 Miklos Csuros

A probabilistic reconstruction of genealogies in a polyploid population (from 2x to 4x) is investigated, by considering genetic data analyzed as the probability of allele presence in a given genotype. Based on the likelihood of all possible…

Populations and Evolution · Quantitative Biology 2018-11-29 Frédéric Proïa , Fabien Panloup , Chiraz Trabelsi , Jérémy Clotault

Inference of the marginal likelihood of sample allele configurations using backward algorithms yields identical results with the Kingman coalescent, the Moran model, and the diffusion model (up to a scaling of time). For inference of…

Populations and Evolution · Quantitative Biology 2021-12-20 Claus Vogl , Sandra Peer , Lynette Caitlin Mikula

We introduce new methods for phylogenetic tree quartet construction by using machine learning to optimize the power of phylogenetic invariants. Phylogenetic invariants are polynomials in the joint probabilities which vanish under a model of…

Populations and Evolution · Quantitative Biology 2007-05-23 Nicholas Eriksson , Yuan Yao

Recently much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here we present an efficient, practical algorithm for…

Populations and Evolution · Quantitative Biology 2009-10-22 Katharina T. Huber , Leo van Iersel , Steven Kelk , Radoslaw Suchecki

We present an alternative method for calculating likelihoods in molecular phylogenetics. Our method is based on partial likelihood tensors, which are generalizations of partial likelihood vectors, as used in Felsenstein's approach.…

Quantitative Methods · Quantitative Biology 2008-07-23 J. G. Sumner , M. A. Charleston
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