On the Matrix Condition of Phylogenetic Tree.
Ontology highlight
ABSTRACT:
SUBMITTER: Jhwueng DC
PROVIDER: S-EPMC7019399 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
On the Matrix Condition of Phylogenetic Tree.
Jhwueng Dwueng-Chwuan DC O'Meara Brian C BC
Evolutionary bioinformatics online 20200212
Phylogenetic comparative analyses use trees of evolutionary relationships between species to understand their evolution and ecology. A phylogenetic tree of <i>n</i> taxa can be algebraically transformed into an <i>n</i> by <i>n</i> squared symmetric phylogenetic covariance matrix <b><i>C</i></b> where each element c ij in <b><i>C</i></b> represents the affinity between extant species <i>i</i> and extant species <i>j</i>. This matrix <b><i>C</i></b> is used internally in several comparative ...[more]
Similar Datasets
Project description:The genus Flaveria has been extensively used as a model to study the evolution of C4 photosynthesis as it contains both C3 and C4 species as well as a number of species that exhibit intermediate types of photosynthesis. The current phylogenetic tree of the Flaveria genus contains 21 of the 23 known Flaveria species and has been constructed using a combination of morphologicial data and three non-coding DNA sequences (nuclear encoded ETS, ITS and chloroplast encoded trnl-F). However, recent studies have suggested that phylogenetic trees inferred using a small number of molecular sequences may often be incorrect. Moreover, studies in other genera have often shown substantial differences between trees inferred using morphological data and those using molecular sequence. To provide new insight into the phylogeny of the genus Flaveria we utilize RNA-Seq data to construct a multi-gene concatenated phylogenetic tree of 17 Flaveria species. Furthermore, we use this new data to identify 14 C4 specific non-synonymous mutation sites, 12 of which (86%) can be independently verified by public sequence data. We propose that the data collection method provided in this study can be used as a generic method for facilitating phylogenetic tree reconstruction in the absence of reference genomes for the target species.
2015-01-08 | GSE54339 | GEO
Project description:The genus Flaveria has been extensively used as a model to study the evolution of C4 photosynthesis as it contains both C3 and C4 species as well as a number of species that exhibit intermediate types of photosynthesis. The current phylogenetic tree of the Flaveria genus contains 21 of the 23 known Flaveria species and has been constructed using a combination of morphologicial data and three non-coding DNA sequences (nuclear encoded ETS, ITS and chloroplast encoded trnl-F). However, recent studies have suggested that phylogenetic trees inferred using a small number of molecular sequences may often be incorrect. Moreover, studies in other genera have often shown substantial differences between trees inferred using morphological data and those using molecular sequence. To provide new insight into the phylogeny of the genus Flaveria we utilize RNA-Seq data to construct a multi-gene concatenated phylogenetic tree of 17 Flaveria species. Furthermore, we use this new data to identify 14 C4 specific non-synonymous mutation sites, 12 of which (86%) can be independently verified by public sequence data. We propose that the data collection method provided in this study can be used as a generic method for facilitating phylogenetic tree reconstruction in the absence of reference genomes for the target species. 18 Flaveria sample including 11 species are sequenced, other three samples were also sequenced as out-group. In all, 21 samples.
2015-01-08 | E-GEOD-54339 | biostudies-arrayexpress
Project description:The shapes of evolutionary trees are influenced by the nature of the evolutionary process but comparisons of trees from different processes are hindered by the challenge of completely describing tree shape. We present a full characterization of the shapes of rooted branching trees in a form that lends itself to natural tree comparisons. We use this characterization to define a metric, in the sense of a true distance function, on tree shapes. The metric distinguishes trees from random models known to produce different tree shapes. It separates trees derived from tropical versus USA influenza A sequences, which reflect the differing epidemiology of tropical and seasonal flu. We describe several metrics based on the same core characterization, and illustrate how to extend the metric to incorporate trees' branch lengths or other features such as overall imbalance. Our approach allows us to construct addition and multiplication on trees, and to create a convex metric on tree shapes which formally allows computation of average tree shapes.
| S-EPMC5790134 | biostudies-literature
Project description:Phylogenetic analyses often produce large numbers of trees. Mapping trees' distribution in "tree space" can illuminate the behavior and performance of search strategies, reveal distinct clusters of optimal trees, and expose differences between different data sources or phylogenetic methods-but the high-dimensional spaces defined by metric distances are necessarily distorted when represented in fewer dimensions. Here, I explore the consequences of this transformation in phylogenetic search results from 128 morphological data sets, using stratigraphic congruence-a complementary aspect of tree similarity-to evaluate the utility of low-dimensional mappings. I find that phylogenetic similarities between cladograms are most accurately depicted in tree spaces derived from information-theoretic tree distances or the quartet distance. Robinson-Foulds tree spaces exhibit prominent distortions and often fail to group trees according to phylogenetic similarity, whereas the strong influence of tree shape on the Kendall-Colijn distance makes its tree space unsuitable for many purposes. Distances mapped into two or even three dimensions often display little correspondence with true distances, which can lead to profound misrepresentation of clustering structure. Without explicit testing, one cannot be confident that a tree space mapping faithfully represents the true distribution of trees, nor that visually evident structure is valid. My recommendations for tree space validation and visualization are implemented in a new graphical user interface in the "TreeDist" R package. [Multidimensional scaling; phylogenetic software; tree distance metrics; treespace projections.].
| S-EPMC9366458 | biostudies-literature
Project description:In order to gain an understanding of the effectiveness of phylogenetic Markov chain Monte Carlo (MCMC), it is important to understand how quickly the empirical distribution of the MCMC converges to the posterior distribution. In this article, we investigate this problem on phylogenetic tree topologies with a metric that is especially well suited to the task: the subtree prune-and-regraft (SPR) metric. This metric directly corresponds to the minimum number of MCMC rearrangements required to move between trees in common phylogenetic MCMC implementations. We develop a novel graph-based approach to analyze tree posteriors and find that the SPR metric is much more informative than simpler metrics that are unrelated to MCMC moves. In doing so, we show conclusively that topological peaks do occur in Bayesian phylogenetic posteriors from real data sets as sampled with standard MCMC approaches, investigate the efficiency of Metropolis-coupled MCMC (MCMCMC) in traversing the valleys between peaks, and show that conditional clade distribution (CCD) can have systematic problems when there are multiple peaks.
| S-EPMC4395846 | biostudies-literature
Project description:SummaryThe assessment of novel phylogenetic models and inference methods is routinely being conducted via experiments on simulated as well as empirical data. When generating synthetic data it is often unclear how to set simulation parameters for the models and generate trees that appropriately reflect empirical model parameter distributions and tree shapes. As a solution, we present and make available a new database called 'RAxML Grove' currently comprising more than 60 000 inferred trees and respective model parameter estimates from fully anonymized empirical datasets that were analyzed using RAxML and RAxML-NG on two web servers. We also describe and make available two simple applications of RAxML Grove to exemplify its usage and highlight its utility for designing realistic simulation studies and analyzing empirical model parameter and tree shape distributions.Availability and implementationRAxML Grove is freely available at https://github.com/angtft/RAxMLGrove.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC8896636 | biostudies-literature
Project description:Advances in experimental technologies, such as DNA sequencing, have opened up new avenues for the applications of phylogenetic methods to various fields beyond their traditional application in evolutionary investigations, extending to the fields of development, differentiation, cancer genomics, and immunogenomics. Thus, the importance of phylogenetic methods is increasingly being recognized, and the development of a novel phylogenetic approach can contribute to several areas of research. Recently, the use of hyperbolic geometry has attracted attention in artificial intelligence research. Hyperbolic space can better represent a hierarchical structure compared to Euclidean space, and can therefore be useful for describing and analyzing a phylogenetic tree. In this study, we developed a novel metric that considers the characteristics of a phylogenetic tree for representation in hyperbolic space. We compared the performance of the proposed hyperbolic embeddings, general hyperbolic embeddings, and Euclidean embeddings, and confirmed that our method could be used to more precisely reconstruct evolutionary distance. We also demonstrate that our approach is useful for predicting the nearest-neighbor node in a partial phylogenetic tree with missing nodes. Furthermore, we proposed a novel approach based on our metric to integrate multiple trees for analyzing tree nodes or imputing missing distances. This study highlights the utility of adopting a geometric approach for further advancing the applications of phylogenetic methods.
| S-EPMC8058397 | biostudies-literature
Project description:Evidence from grassland experiments suggests that a plant community's phylogenetic diversity (PD) is a strong predictor of ecosystem processes, even stronger than species richness per se This has, however, never been extended to species-rich forests and host-parasitoid interactions. We used cavity-nesting Hymenoptera and their parasitoids collected in a subtropical forest as a model system to test whether hosts, parasitoids, and their interactions are influenced by tree PD and a comprehensive set of environmental variables, including tree species richness. Parasitism rate and parasitoid abundance were positively correlated with tree PD. All variables describing parasitoids decreased with elevation, and were, except parasitism rate, dependent on host abundance. Quantitative descriptors of host-parasitoid networks were independent of the environment. Our study indicates that host-parasitoid interactions in species-rich forests are related to the PD of the tree community, which influences parasitism rates through parasitoid abundance. We show that effects of tree community PD are much stronger than effects of tree species richness, can cascade to high trophic levels, and promote trophic interactions. As during habitat modification phylogenetic information is usually lost non-randomly, even species-rich habitats may not be able to continuously provide the ecosystem process parasitism if the evolutionarily most distinct plant lineages vanish.
| S-EPMC4947881 | biostudies-literature
Project description:Bayesian inference of phylogeny with Markov chain Monte Carlo plays a key role in the study of evolution. Yet, this method still suffers from a practical challenge identified more than two decades ago: designing tree topology proposals that efficiently sample tree spaces. In this article, I introduce the concept of adaptive tree proposals for unrooted topologies, that is, tree proposals adapting to the posterior distribution as it is estimated. I use this concept to elaborate two adaptive variants of existing proposals and an adaptive proposal based on a novel design philosophy in which the structure of the proposal is informed by the posterior distribution of trees. I investigate the performance of these proposals by first presenting a metric that captures the performance of each proposal within a mixture of proposals. Using this metric, I compare the performance of the adaptive proposals to the performance of standard and parsimony-guided proposals on 11 empirical data sets. Using adaptive proposals led to consistent performance gains and resulted in up to 18-fold increases in mixing efficiency and 6-fold increases in convergence rate without increasing the computational cost of these analyses. [Bayesian phylogenetic inference; Markov chain Monte Carlo; posterior probability distribution; tree proposals.].
| S-EPMC8357345 | biostudies-literature
Project description:Background and objectivesWhole-genome sequencing is becoming popular as a tool for understanding outbreaks of communicable diseases, with phylogenetic trees being used to identify individual transmission events or to characterize outbreak-level overall transmission dynamics. Existing methods to infer transmission dynamics from sequence data rely on well-characterized infectious periods, epidemiological and clinical metadata which may not always be available, and typically require computationally intensive analysis focusing on the branch lengths in phylogenetic trees. We sought to determine whether the topological structures of phylogenetic trees contain signatures of the transmission patterns underlying an outbreak.MethodologyWe use simulated outbreaks to train and then test computational classifiers. We test the method on data from two real-world outbreaks.ResultsWe show that different transmission patterns result in quantitatively different phylogenetic tree shapes. We describe topological features that summarize a phylogeny's structure and find that computational classifiers based on these are capable of predicting an outbreak's transmission dynamics. The method is robust to variations in the transmission parameters and network types, and recapitulates known epidemiology of previously characterized real-world outbreaks.Conclusions and implicationsThere are simple structural properties of phylogenetic trees which, when combined, can distinguish communicable disease outbreaks with a super-spreader, homogeneous transmission and chains of transmission. This is possible using genome data alone, and can be done during an outbreak. We discuss the implications for management of outbreaks.
| S-EPMC4097963 | biostudies-literature