进化基因组学中的一个重要问题是研究在每个样本上测量的某种性状是否与样本的系统发育树相关联。系统发育树代表样本共享的进化历史，通常根据一个位点的分子序列数据或其他类型的遗传数据进行估计。我们提出了一种受中国餐馆过程启发的性状进化模型，该模型包含一个控制优先连接程度的参数，即树中节点倾向于从同类型节点下生的趋势。该模型在没有优先连接的情况下等价于具有同时迁移和 coalescence 事件的结构化溯祖模型，并作为零模型。我们推导出一种具有线性计算复杂度的系统发育二元性状关联检验，并通过实证表明它比其他一些方法更强大。我们将我们的检验应用于研究剑尾鱼、乳腺癌、黄热病病毒和甲型流感 H1N1 病毒中某些性状的系统发育关联。我们方法的 R 包实现可在 https://github.com/jyzhang27/CRPTree 获取。
英文摘要：
An important problem in evolutionary genomics is to investigate whether a certain trait measured on each sample is associated with the sample phylogenetic tree. The phylogenetic tree represents the shared evolutionary history of the samples and it is usually estimated from molecular sequence data at a locus or from other type of genetic data. We propose a model for trait evolution inspired by the Chinese Restaurant Process that includes a parameter that controls the degree of preferential attachment, that is, the tendency of nodes in the tree to subtend from nodes of the same type. This model with no preferential attachment is equivalent to a structured coalescent model with simultaneous migration and coalescence events and serves as a null model. We derive a test for phylogenetic binary trait association with linear computational complexity and empirically demonstrate that it is more powerful than some other methods. We apply our test to study the phylogenetic association of some traits in swordtail fish, breast cancer, yellow fever virus and influenza A H1N1 virus. R package implementation of our methods is available at $\texttt{https://github.com/jyzhang27/CRPTree}$.
The phylogenetic effective sample size is a parameter that has as its goal the quantification of the amount of independent signal in a phylogenetically correlated sample. It was studied for Brownian motion and Ornstein-Uhlenbeck models of trait evolution. Here, we study this composite parameter when the trait is allowed to jump at speciation points of the phylogeny. Our numerical study indicates that there is a non-trivial limit as the effect of jumps grows. The limit depends on the value of the drift parameter of the Ornstein-Uhlenbeck process.
Phylogenetic comparative methods correct for shared evolutionary history among a set of non-independent organisms by modeling sample traits as arising from a diffusion process along on the branches of a possibly unknown history. To incorporate such uncertainty, we present a scalable Bayesian inference framework under a general Gaussian trait evolution model that exploits Hamiltonian Monte Carlo (HMC). HMC enables efficient sampling of the constrained model parameters and takes advantage of the tree structure for fast likelihood and gradient computations, yielding algorithmic complexity linear …
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 flexibility and computational efficiency to incorporate multiple continuous and discrete traits as data size increases. To accomplish this, we jointly model mixed-type traits by assuming latent parameters for binary outcome dimensions at the tips of an unknown tree informed by molecular sequences. This gives rise to a phylogenetic multivariate probit model. Wi…
Enumerating monophyletic characters in mathematical phylogenetics
Institute of Mathematics and Computer Science, Greifswald University（格赖夫斯瓦尔德大学数学与计算机科学研究所）；School of Mathematics and Statistics, University of New South Wales（新南威尔士大学数学与统计学院）；Department of Mathematical Sciences, New Jersey Institute of Technology（新泽西理工学院数学科学系）；National Institute for Theory and Mathematics in Biology, Northwestern University and The University of Chicago（西北大学和芝加哥大学生物理论与数学国家研究所）
Evaluating Phylogenetic Comparative Methods under Reticulate Evolutionary Scenarios
Texas A&M University（德克萨斯农工大学）；Lakehead University（湖首大学）；IISD Experimental Lakes Area（国际可持续发展研究所实验湖区）；The Institute for Computational and Experimental Research in Mathematics, Brown University（布朗大学计算与实验数学研究所）；RIKEN iTHEMS（理化学研究所创新智能数学科学中心）
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 state-of-the-art approach uses a phylogenetic multivariate probit model to accommodate binary and continuous traits via a latent variable framework, and utilizes an efficient bouncy particle sampler (BPS) to tackle the computational bottleneck -- integrating many latent variables from a high-dimensional truncated normal distribution. This approach breaks down as the number…
We introduce an R package, PCMBase, to rapidly calculate the likelihood for multivariate phylogenetic comparative methods. The package is not specific to particular models but offers the user the functionality to very easily implement a wide range of models where the transition along a branch is multivariate normal. We demonstrate the package's possibilities on the now standard, multitrait Ornstein-Uhlenbeck process as well as the novel multivariate punctuated equilibrium model. The package can handle trees of various types (e.g. ultrametric, nonultrametric, polytomies, e.t.c.), as well as mea…
Metrics on rooted phylogenetic trees are integral to a number of areas of phylogenetic analysis. Cluster-similarity metrics have recently been introduced in order to limit skew in the distribution of distances, and to ensure that trees in the neighbourhood of each other have similar hierarchies. In the present paper we introduce a new cluster-similarity metric on rooted phylogenetic tree space that has an associated local operation, allowing for easy calculation of neighbourhoods, a trait that is desirable for MCMC calculations. The metric is defined by the distance on the Hasse diagram induce…
Identifying undocumented or potential future interactions among species is a challenge facing modern ecologists. Recent link prediction methods rely on trait data, however large species interaction databases are typically sparse and covariates are limited to only a fraction of species. On the other hand, evolutionary relationships, encoded as phylogenetic trees, can act as proxies for underlying traits and historical patterns of parasite sharing among hosts. We show that using a network-based conditional model, phylogenetic information provides strong predictive power in a recently published g…
Biological phenotypes are products of complex evolutionary processes in which selective forces influence multiple biological trait measurements in unknown ways. Phylogenetic factor analysis disentangles these relationships across the evolutionary history of a group of organisms. Scientists seeking to employ this modeling framework confront numerous modeling and implementation decisions, the details of which pose computational and replicability challenges. General and impactful community employment requires a data scientific analysis plan that balances flexibility, speed and ease of use, while …
Recently, the perfect phylogeny model with persistent characters has attracted great attention in the literature. It is based on the assumption that complex traits or characters can only be gained once and lost once in the course of evolution. Here, we consider a generalization of this model, namely Dollo parsimony, that allows for multiple character losses. More precisely, we take a combinatorial perspective on the notion of Dollo-$k$ characters, i.e. traits that are gained at most once and lost precisely $k$ times throughout evolution. We first introduce an algorithm based on the notion of s…
The aim of this review is to present and analyze the probabilistic models of mathematical phylogenetics which have been intensively used in recent years in biology as the cornerstone of attempts to infer and reconstruct the ancestral relationships between species. We outline the development of theoretical phylogenetics, from the earliest studies based on morphological characters, through to the use of molecular data in a wide variety of forms. We bring the lens of mathematical physics to bear on the formulation of theoretical models, focussing on the applicability of many methods from the tool…
Broad presence of ferromagnetism in bees and relationship to phylogeny, natural history, and sociality
University of Tennessee（田纳西大学）；York University（约克大学）；University of Oldenburg（奥尔登堡大学）；Carl von Ossietzky University of Oldenburg（卡尔·冯·奥西茨基奥尔登堡大学）；Smithsonian Institution（史密森尼学会）
Maximum likelihood estimators are used extensively to estimate unknown parameters of stochastic trait evolution models on phylogenetic trees. Although the MLE has been proven to converge to the true value in the independent-sample case, we cannot appeal to this result because trait values of different species are correlated due to shared evolutionary history. In this paper, we consider a $2$-state symmetric model for a single binary trait and investigate the theoretical properties of the MLE for the transition rate in the large-tree limit. Here, the large-tree limit is a theoretical scenario w…
Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution
Virginia Tech（弗吉尼亚理工大学）；Oak Ridge National Laboratory（橡树岭国家实验室）；University of California, Irvine（加利福尼亚大学欧文分校）；Tulane University（杜兰大学）；Battelle（巴特尔公司）；Duke University（杜克大学）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；The Ohio State University（俄亥俄州立大学）；Rensselaer Polytechnic Institute（伦斯勒理工学院）
Siamese networks for Poincaré embeddings and the reconstruction of evolutionary trees
Departamento de Matemática, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires（数学系，精确自然科学学院，布宜诺斯艾利斯大学）；Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires（物理系，精确自然科学学院，布宜诺斯艾利斯大学）；CONICET - Universidad de Buenos Aires, Instituto de Física Interdisciplinaria y Aplicada (INFINA)（CONICET-布宜诺斯艾利斯大学，跨学科与应用物理研究所（INFINA））；CONICET - Universidad de Buenos Aires, Instituto de Matemática Luis A. Santaló (IMAS)（CONICET-布宜诺斯艾利斯大学，路易斯·A·桑塔洛数学研究所（IMAS））
