scholarly journals The Multispecies Coalescent Model Outperforms Concatenation Across Diverse Phylogenomic Data Sets

2020 ◽  
Vol 69 (4) ◽  
pp. 795-812 ◽  
Author(s):  
Xiaodong Jiang ◽  
Scott V Edwards ◽  
Liang Liu
Keyword(s):  
Data Analysis ◽  
Model Validation ◽  
Bayesian Model ◽  
Statistical Tests ◽  
Gc Content ◽  
Data Sets ◽  
Gene Trees ◽  
Coalescent Model ◽  
Multispecies Coalescent ◽  
Substitution Models

Abstract A statistical framework of model comparison and model validation is essential to resolving the debates over concatenation and coalescent models in phylogenomic data analysis. A set of statistical tests are here applied and developed to evaluate and compare the adequacy of substitution, concatenation, and multispecies coalescent (MSC) models across 47 phylogenomic data sets collected across tree of life. Tests for substitution models and the concatenation assumption of topologically congruent gene trees suggest that a poor fit of substitution models, rejected by 44% of loci, and concatenation models, rejected by 38% of loci, is widespread. Logistic regression shows that the proportions of GC content and informative sites are both negatively correlated with the fit of substitution models across loci. Moreover, a substantial violation of the concatenation assumption of congruent gene trees is consistently observed across six major groups (birds, mammals, fish, insects, reptiles, and others, including other invertebrates). In contrast, among those loci adequately described by a given substitution model, the proportion of loci rejecting the MSC model is 11%, significantly lower than those rejecting the substitution and concatenation models. Although conducted on reduced data sets due to computational constraints, Bayesian model validation and comparison both strongly favor the MSC over concatenation across all data sets; the concatenation assumption of congruent gene trees rarely holds for phylogenomic data sets with more than 10 loci. Thus, for large phylogenomic data sets, model comparisons are expected to consistently and more strongly favor the coalescent model over the concatenation model. We also found that loci rejecting the MSC have little effect on species tree estimation. Our study reveals the value of model validation and comparison in phylogenomic data analysis, as well as the need for further improvements of multilocus models and computational tools for phylogenetic inference. [Bayes factor; Bayesian model validation; coalescent prior; congruent gene trees; independent prior; Metazoa; posterior predictive simulation.]

scholarly journals The Multispecies Coalescent Model Outperforms Concatenation across Diverse Phylogenomic Data Sets

2019 ◽  
Author(s):  
Xiaodong Jian ◽  
Scott V. Edwards ◽  
Liang Liu
Keyword(s):  
Data Analysis ◽  
Model Validation ◽  
Bayesian Model ◽  
Model Comparison ◽  
Phylogenetic Inference ◽  
Data Sets ◽  
Gene Trees ◽  
Substitution Model ◽  
Multispecies Coalescent ◽  
Substitution Models

ABSTRACTA statistical framework of model comparison and model validation is essential to resolving the debates over concatenation and coalescent models in phylogenomic data analysis. A set of statistical tests are here applied and developed to evaluate and compare the adequacy of substitution, concatenation, and multispecies coalescent (MSC) models across 47 phylogenomic data sets collected across tree of life. Tests for substitution models and the concatenation assumption of topologically concordant gene trees suggest that a poor fit of substitution models (44% of loci rejecting the substitution model) and concatenation models (38% of loci rejecting the hypothesis of topologically congruent gene trees) is widespread. Logistic regression shows that the proportions of GC content and informative sites are both negatively correlated with the fit of substitution models across loci. Moreover, a substantial violation of the concatenation assumption of congruent gene trees is consistently observed across 6 major groups (birds, mammals, fish, insects, reptiles, and others, including other invertebrates). In contrast, among those loci adequately described by a given substitution model, the proportion of loci rejecting the MSC model is 11%, significantly lower than those rejecting the substitution and concatenation models, and Bayesian model comparison strongly favors the MSC over concatenation across all data sets. Species tree inference suggests that loci rejecting the MSC have little effect on species tree estimation. Due to computational constraints, the Bayesian model validation and comparison analyses were conducted on the reduced data sets. A complete analysis of phylogenomic data requires the development of efficient algorithms for phylogenetic inference. Nevertheless, the concatenation assumption of congruent gene trees rarely holds for phylogenomic data with more than 10 loci. Thus, for large phylogenomic data sets, model comparison analyses are expected to consistently and more strongly favor the coalescent model over the concatenation model. Our analysis reveals the value of model validation and comparison in phylogenomic data analysis, as well as the need for further improvements of multilocus models and computational tools for phylogenetic inference.

scholarly journals Gene tree discord, simplex plots, and statistical tests under the coalescent

2020 ◽  
Author(s):  
Elizabeth S. Allman ◽  
Jonathan D. Mitchell ◽  
John A. Rhodes
Keyword(s):  
Incomplete Lineage Sorting ◽  
Statistical Tests ◽  
Gene Tree ◽  
Complex Model ◽  
Species Tree ◽  
Data Sets ◽  
Gene Trees ◽  
Lineage Sorting ◽  
Multispecies Coalescent ◽  
Tree Inference

AbstractA simple graphical device, the simplex plot of quartet concordance factors, is introduced to aid in the exploration of a collection of gene trees on a common set of taxa. A single plot summarizes all gene tree discord, and allows for visual comparison to the expected discord from the multispecies coalescent model (MSC) of incomplete lineage sorting on a species tree. A formal statistical procedure is described that can quantify the deviation from expectation for each subset of four taxa, suggesting when the data is not in accord with the MSC, and thus either gene tree inference error is substantial or a more complex model such as that on a network may be required. If the collection of gene trees appears to be in accord with the MSC, the plots may reveal when substantial incomplete lineage sorting is present and coalescent based species tree inference is preferred over concatenation approaches. Applications to both simulated and empirical multilocus data sets illustrate the insights provided.

scholarly journals Gene Tree Discord, Simplex Plots, and Statistical Tests under the Coalescent

2021 ◽  
Author(s):  
Elizabeth S Allman ◽  
Jonathan D Mitchell ◽  
John A Rhodes
Keyword(s):  
Incomplete Lineage Sorting ◽  
Hypothesis Test ◽  
Statistical Tests ◽  
Gene Tree ◽  
Complex Model ◽  
Species Tree ◽  
Gene Trees ◽  
Lineage Sorting ◽  
Coalescent Model ◽  
Multispecies Coalescent

Abstract A simple graphical device, the simplex plot of quartet concordance factors, is introduced to aid in the exploration of a collection of gene trees on a common set of taxa. A single plot summarizes all gene tree discord and allows for visual comparison to the expected discord from the multispecies coalescent model (MSC) of incomplete lineage sorting on a species tree. A formal statistical procedure is described that can quantify the deviation from expectation for each subset of four taxa, suggesting when the data are not in accord with the MSC, and thus that either gene tree inference error is substantial or a more complex model such as that on a network may be required. If the collection of gene trees is in accord with the MSC, the plots reveal when substantial incomplete lineage sorting is present. Applications to both simulated and empirical multilocus data sets illustrate the insights provided. [Gene tree discordance; hypothesis test; multispecies coalescent model; quartet concordance factor; simplex plot; species tree].

scholarly journals Detecting destabilizing species in the phylogenetic backbone of Potentilla (Rosaceae) using low-copy nuclear markers

AoB Plants ◽  
2020 ◽  
Vol 12 (3) ◽  
Author(s):  
Nannie L Persson ◽  
Ingrid Toresen ◽  
Heidi Lie Andersen ◽  
Jenny E E Smedmark ◽  
Torsten Eriksson
Keyword(s):  
Incomplete Lineage Sorting ◽  
Gene Tree ◽  
Data Sets ◽  
Gene Trees ◽  
Lineage Sorting ◽  
Nuclear Markers ◽  
Data Set ◽  
Multispecies Coalescent ◽  
Single Marker ◽  
Named Groups

Abstract The genus Potentilla (Rosaceae) has been subjected to several phylogenetic studies, but resolving its evolutionary history has proven challenging. Previous analyses recovered six, informally named, groups: the Argentea, Ivesioid, Fragarioides, Reptans, Alba and Anserina clades, but the relationships among some of these clades differ between data sets. The Reptans clade, which includes the type species of Potentilla, has been noticed to shift position between plastid and nuclear ribosomal data sets. We studied this incongruence by analysing four low-copy nuclear markers, in addition to chloroplast and nuclear ribosomal data, with a set of Bayesian phylogenetic and Multispecies Coalescent (MSC) analyses. A selective taxon removal strategy demonstrated that the included representatives from the Fragarioides clade, P. dickinsii and P. fragarioides, were the main sources of the instability seen in the trees. The Fragarioides species showed different relationships in each gene tree, and were only supported as a monophyletic group in a single marker when the Reptans clade was excluded from the analysis. The incongruences could not be explained by allopolyploidy, but rather by homoploid hybridization, incomplete lineage sorting or taxon sampling effects. When P. dickinsii and P. fragarioides were removed from the data set, a fully resolved, supported backbone phylogeny of Potentilla was obtained in the MSC analysis. Additionally, indications of autopolyploid origins of the Reptans and Ivesioid clades were discovered in the low-copy gene trees.

scholarly journals A Bayesian Implementation of the Multispecies Coalescent Model with Introgression for Phylogenomic Analysis

2019 ◽  
Vol 37 (4) ◽  
pp. 1211-1223 ◽  
Author(s):  
Tomáš Flouri ◽  
Xiyun Jiao ◽  
Bruce Rannala ◽  
Ziheng Yang
Keyword(s):  
Gene Flow ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Incomplete Lineage Sorting ◽  
Mosquito Species ◽  
Phylogenomic Analysis ◽  
Data Sets ◽  
Lineage Sorting ◽  
Coalescent Model ◽  
Multispecies Coalescent

Abstract Recent analyses suggest that cross-species gene flow or introgression is common in nature, especially during species divergences. Genomic sequence data can be used to infer introgression events and to estimate the timing and intensity of introgression, providing an important means to advance our understanding of the role of gene flow in speciation. Here, we implement the multispecies-coalescent-with-introgression model, an extension of the multispecies-coalescent model to incorporate introgression, in our Bayesian Markov chain Monte Carlo program Bpp. The multispecies-coalescent-with-introgression model accommodates deep coalescence (or incomplete lineage sorting) and introgression and provides a natural framework for inference using genomic sequence data. Computer simulation confirms the good statistical properties of the method, although hundreds or thousands of loci are typically needed to estimate introgression probabilities reliably. Reanalysis of data sets from the purple cone spruce confirms the hypothesis of homoploid hybrid speciation. We estimated the introgression probability using the genomic sequence data from six mosquito species in the Anopheles gambiae species complex, which varies considerably across the genome, likely driven by differential selection against introgressed alleles.

scholarly journals Practical Speedup of Bayesian Inference of Species Phylogenies by Restricting the Space of Gene Trees

2019 ◽  
Author(s):  
Yaxuan Wang ◽  
Huw A. Ogilvie ◽  
Luay Nakhleh
Keyword(s):  
Bayesian Inference ◽  
Species Tree ◽  
Biological Data ◽  
Small Data ◽  
Data Sets ◽  
Gene Trees ◽  
Multispecies Coalescent ◽  
Tree Inference ◽  
The Individual ◽  
Species Tree Inference

AbstractSpecies tree inference from multi-locus data has emerged as a powerful paradigm in the post-genomic era, both in terms of the accuracy of the species tree it produces as well as in terms of elucidating the processes that shaped the evolutionary history. Bayesian methods for species tree inference are desirable in this area as they have been shown to yield accurate estimates, but also to naturally provide measures of confidence in those estimates. However, the heavy computational requirements of Bayesian inference have limited the applicability of such methods to very small data sets.In this paper, we show that the computational efficiency of Bayesian inference under the multispecies coalescent can be improved in practice by restricting the space of the gene trees explored during the random walk, without sacrificing accuracy as measured by various metrics. The idea is to first infer constraints on the trees of the individual loci in the form of unresolved gene trees, and then to restrict the sampler to consider only resolutions of the constrained trees. We demonstrate the improvements gained by such an approach on both simulated and biological data.

scholarly journals Practical Speedup of Bayesian Inference of Species Phylogenies by Restricting the Space of Gene Trees

2020 ◽  
Vol 37 (6) ◽  
pp. 1809-1818
Author(s):  
Yaxuan Wang ◽  
Huw A Ogilvie ◽  
Luay Nakhleh
Keyword(s):  
Bayesian Inference ◽  
Species Tree ◽  
Biological Data ◽  
Small Data ◽  
Data Sets ◽  
Gene Trees ◽  
Multispecies Coalescent ◽  
Tree Inference ◽  
The Individual ◽  
Species Tree Inference

Abstract Species tree inference from multilocus data has emerged as a powerful paradigm in the postgenomic era, both in terms of the accuracy of the species tree it produces as well as in terms of elucidating the processes that shaped the evolutionary history. Bayesian methods for species tree inference are desirable in this area as they have been shown not only to yield accurate estimates, but also to naturally provide measures of confidence in those estimates. However, the heavy computational requirements of Bayesian inference have limited the applicability of such methods to very small data sets. In this article, we show that the computational efficiency of Bayesian inference under the multispecies coalescent can be improved in practice by restricting the space of the gene trees explored during the random walk, without sacrificing accuracy as measured by various metrics. The idea is to first infer constraints on the trees of the individual loci in the form of unresolved gene trees, and then to restrict the sampler to consider only resolutions of the constrained trees. We demonstrate the improvements gained by such an approach on both simulated and biological data.

scholarly journals Consistency of SVDQuartets and Maximum Likelihood for Coalescent-based Species Tree Estimation

2019 ◽  
Author(s):  
Matthew Wascher ◽  
Laura Kubatko
Keyword(s):  
Maximum Likelihood ◽  
Species Tree ◽  
Gene Trees ◽  
Data Types ◽  
Coalescent Model ◽  
Multispecies Coalescent ◽  
Consistency Results ◽  
True Tree ◽  
Tree Inference ◽  
Statistical Consistency

AbtractNumerous methods for inferring species-level phylogenies under the coalescent model have been proposed within the last 20 years, and debates continue about the relative strengths and weaknesses of these methods. One desirable property of a phylogenetic estimator is that of statistical consistency, which means intuitively that as more data are collected, the probability that the estimated tree has the same topology as the true tree goes to 1. To date, consistency results for species tree inference under the multispecies coalescent have been derived only for summary statistics methods, such as ASTRAL and MP-EST. These methods have been found to be consistent given true gene trees, but may be inconsistent when gene trees are estimated from data for loci of finite length (Roch et al., 2019). Here we consider the question of statistical consistency for four taxa for SVDQuartets for general data types, as well as for the maximum likelihood (ML) method in the case in which the data are a collection of sites generated under the multispecies coalescent model such that the sites are conditionally independent given the species tree (we call these data Coalescent Independent Sites (CIS) data). We show that SVDQuartets is statistically consistent for all data types (i.e., for both CIS data and for multilocus data), and we derive its rate of convergence. We additionally show that ML is consistent for CIS data under the JC69 model, and discuss why a proof for the more general multilocus case is difficult. Finally, we compare the performance of maximum likelihood and SDVQuartets using simulation for both data types.

scholarly journals Identifiability of speciation times under the multispecies coalescent

2020 ◽  
Author(s):  
Laura Kubatko ◽  
Julia Chifman
Keyword(s):  
Sequence Data ◽  
Hypothesis Test ◽  
Gene Trees ◽  
Species Trees ◽  
Computationally Efficient ◽  
Coalescent Model ◽  
Sequencing Technologies ◽  
Multispecies Coalescent ◽  
Branch Lengths ◽  
And Performance

AbstractThe advent of rapid and inexpensive sequencing technologies has necessitated the development of computationally efficient methods for analyzing sequence data for many genes simultaneously in a phylogenetic framework. The coalescent process is the most commonly used model for linking the underlying genealogies of individual genes with the global species-level phylogeny, but inference under the coalescent model is computationally daunting in the typical inference frameworks (e.g., the likelihood and Bayesian frameworks) due to the dimensionality of the space of both gene trees and species trees. Here we consider estimation of the branch lengths in a fixed species tree, and show that these branch lengths are identifiable. We also show that in the case of four taxa simple estimators for the branch lengths can be derived based on observed site pattern frequencies. Properties of these estimators, such as their asymptotic variances and large-sample distributions, are examined, and performance of the estimators is assessed using simulation. Finally, we use these estimators to develop a hypothesis test that can be limit species under the coalescent model.

SPSS for Applied Sciences

2013 ◽  
Author(s):  
Cole Davis
Keyword(s):  
Applied Sciences ◽  
Data Analysis ◽  
Computer Science ◽  
Statistical Tests ◽  
Farm Management ◽  
Data Sets ◽  
Statistical Software ◽  
Sports Science ◽  
Different Types ◽  
Test User

This book offers a quick and basic guide to using SPSS and provides a general approach to solving problems using statistical tests. It is both comprehensive in terms of the tests covered and the applied settings it refers to, and yet is short and easy to understand. Whether you are a beginner or an intermediate level test user, this book will help you to analyse different types of data in applied settings. It will also give you the confidence to use other statistical software and to extend your expertise to more specific scientific settings as required. The author does not use mathematical formulae and leaves out arcane statistical concepts. Instead, he provides a very practical, easy and speedy introduction to data analysis, offering examples from a range of scenarios from applied science, handling both continuous and rough-hewn data sets. Examples are given from agriculture, arboriculture, biology, computer science, ecology, engineering, farming and farm management, hydrology, medicine, ophthalmology, pharmacology, physiotherapy, spectroscopy, sports science, audiology and epidemiology.

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