Dual multiple change-point model leads to more accurate recombination detection

Minin, Vladimir N.; Dorman, Karin S.; Fang, Fang; Suchard, Marc A.

doi:10.1093/bioinformatics/bti459

Cited by 133 publications

(205 citation statements)

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“…Phylogenetic methods detect incongruence in the tree structure of different segments (5)(6)(7)(8). Nonphylogenetic methods probe for homoplasies (shared character traits independently arising in different lineages by convergent or parallel evolution) or similar inconsistencies in sequence alignment (9)(10)(11)(12)(13).…”

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confidence: 99%

Topology of viral evolution

Chan

Carlsson

Rabadán

2013

Proc. Natl. Acad. Sci. U.S.A.

225

189

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The tree structure is currently the accepted paradigm to represent evolutionary relationships between organisms, species or other taxa. However, horizontal, or reticulate, genomic exchanges are pervasive in nature and confound characterization of phylogenetic trees. Drawing from algebraic topology, we present a unique evolutionary framework that comprehensively captures both clonal and reticulate evolution. We show that whereas clonal evolution can be summarized as a tree, reticulate evolution exhibits nontrivial topology of dimension greater than zero. Our method effectively characterizes clonal evolution, reassortment, and recombination in RNA viruses. Beyond detecting reticulate evolution, we succinctly recapitulate the history of complex genetic exchanges involving more than two parental strains, such as the triple reassortment of H7N9 avian influenza and the formation of circulating HIV-1 recombinants. In addition, we identify recurrent, large-scale patterns of reticulate evolution, including frequent PB2-PB1-PA-NP cosegregation during avian influenza reassortment. Finally, we bound the rate of reticulate events (i.e., 20 reassortments per year in avian influenza). Our method provides an evolutionary perspective that not only captures reticulate events precluding phylogeny, but also indicates the evolutionary scales where phylogenetic inference could be accurate. n On the Origin of the Species in 1859, Darwin first proposed the phylogenetic tree as a structure to describe the evolution of phenotypic attributes. Since then, the advancement of modern sequencing has spurred development of a number of phylogenetic inference methods (1, 2). The tree structure effectively models vertical or clonal evolution, mediated by random mutations over multiple generations (Fig. 1A). Phylogenetic trees, however, cannot capture horizontal, or reticulate, events, which occur when distinct clades merge together to form a new hybrid lineage ( Fig. 1B and SI Appendix, Fig. S1). In nature, horizontal evolution can occur through species hybridization in eukaryotes, lateral gene transfer in bacteria, recombination and reassortment in viruses, viral integration in eukaryotes, and fusion of genomes of symbiotic species (e.g., mitochondria). These horizontal genetic exchanges create incompatibilities that mischaracterize the species tree (3). Doolittle (4) argued that molecular phylogeneticists have failed to identify the "true tree of life" because the history of living organisms cannot be understood as a tree. One may wonder what other mathematical structures beyond phylogeny can capture the richness of evolutionary processes.Current techniques that detect reticulate events can be divided into phylogenetic and nonphylogenetic methodologies. Phylogenetic methods detect incongruence in the tree structure of different segments (5-8). Nonphylogenetic methods probe for homoplasies (shared character traits independently arising in different lineages by convergent or parallel evolution) or similar inconsistencies in sequence alignment (9-...

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confidence: 99%

Topology of viral evolution

Chan

Carlsson

Rabadán

2013

Proc. Natl. Acad. Sci. U.S.A.

225

189

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“…A variety of Penalized Maximum Likelihood estimators have also been used to estimate and test structural breaks, such as the penalized contrast estimator (Lavielle 2005), the minimum description length principle (Davis, Lee, and Rodriguez-Yam 2006), and many others (e.g., Siegmund 2004;Zhang and Siegmund 2007). There is a large Bayesian literature on multiple change-point models (e.g., Carlin, Gelfand, and Smith 1992;Barry and Hartigan 1993;Chib 1996Chib , 1998Hawkins 2001;Minin et al 2005). The Bayesian methods for structural-break problems apply Markov chain Monte Carlo methods, which allow one to work with a rich set of models.…”

Section: A Multiple Change-point Modelmentioning

confidence: 99%

Endogenous Jurisprudential Regimes

Pang

Friedman²,

Martin³

et al. 2012

Polit. anal.

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Edited by R. Michael AlvarezJurisprudential regime theory is a legal explanation of decision-making on the U.S. Supreme Court that asserts that a key precedent in an area of law fundamentally restructures the relationship between case characteristics and the outcomes of future cases. In this article, we offer a multivariate multiple change-point probit model that can be used to endogenously test for the existence of jurisprudential regimes. Unlike the previously employed methods, our model does so by estimating the locations of many possible changepoints along with structural parameters. We estimate the model using Markov chain Monte Carlo methods, and use Bayesian model comparison to determine the number of change-points. Our findings are consistent with jurisprudential regimes in the Establishment Clause and administrative law contexts. We find little support for hypothesized regimes in the areas of free speech and search-and-seizure. The Bayesian multivariate change-point model we propose has broad potential applications to studying structural breaks in either regular or irregular time-series data about political institutions or processes.1 Modeling Decision-Making on the U.S. Supreme Court Supreme Court decisions do two things: they award a judgment, and they provide a rationale for that judgment in the form of a written opinion. The judgment of the case determines who wins and who loses in the legal dispute, and the terms of the victory or defeat. Opinions are important because they provide justifications for the judgment. Those who subscribe to the attitudinal model of judging (Segal and Spaeth 2002)-which asserts that the decisions the Justices reach are due solely to politics-argue that opinions are nothing more than disingenuous post hoc rationalizations of behavior that merely serve to cover up nothing more than unfettered politics.Authors' note: The authors thank Bert Kritzer, Mark Richards, and Jeff Segal for sharing replication data; Jude Hayes and Robert Walker, along with seminar participants at SLAMM 2010, NYU, and USC for helpful comments; Katie Schon, Jee Seon Jeon, and Rachael Hinkle for their research assistance; and the Filomen D'Agostino and Max E. Greenberg Research Fund at NYU School of Law, the Center for Empirical Research in the Law at Washington University, the Wang Xuelian Fund at Tsinghua University, and the National Science Foundation for supporting our research. The editor, R. Michael Alvarez, and two anonymous referees made suggestions that improved the article significantly. For replication data and code, see Pang et al. (2012). Supplementary materials for this article are available on the Political Analysis Web site.Political Analysis (2012) On the other hand, from a legal standpoint, it is hard to believe that opinions are inconsequential (Friedman 2006). To be sure, opinions are justifications, but they also provide legal rules that govern in future disputes. In our common law system, lower court judges rely on the collection of these rules-called precedents-when deciding s...

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“…We used a Bayesian phylogenetic approach, DualBrothers [9] for this purpose. DualBrothers is a program that implements reversible jump Markov chain Monte Carlo and dual multiple change-point model in inferring changes in tree topologies and evolutionary rates across sites within a sequence set.…”

Section: Phase Ii: Identification Of Recombination Breakpointsmentioning

confidence: 99%

“…Recombination breakpoints in these famihes were analysed using DualBrothers [9]. Figure 1 shows an example of a recombination event detected in a five-sequence gene family, s6914, a family of conserved hypothetical proteins.…”

Section: Application To Large-scale Datamentioning

confidence: 99%

“…The profile reveals a single breakpoint corresponding to a change in tree topologies, located between positions 120-160 in the sequence alignment. To determine the location of the breakpoints, we sub-sampled the COP mPP under a peak, of which we define a 95% Bayesian Confidence Interval [9,11]. The median of the sub-sampled distribution was defined as the breakpoint.…”

Section: Application To Large-scale Datamentioning

confidence: 99%

See 1 more Smart Citation

Large-scale detection of recombination in nucleotide sequences

Chan¹,

Beiko²,

Ragan³

2008

AIP Conference Proceedings

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Abstract. Genetic recombination following a genetic transfer event can produce heterogeneous phylogenetic histories within sets of genes that share a common ancestral origin. Delineating recombination events will enhance our understanding in genome evolution. However, the task of detecting recombination is not trivial due to effect of more-recent evolutionary changes that can obscure such event from detection. In this paper, we demonstrate the use of a two-phase strategy for detecting recombination events on a large-scale dataset.

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Dual multiple change-point model leads to more accurate recombination detection

Abstract: We use primate mitochondrial DNA data with simulated recombination break-points at specific locations to compare the two models. We also analyze two real HIV sequences to identify recombination break-points using the dual MCP model.

Cited by 133 publications

References 35 publications

Topology of viral evolution

Topology of viral evolution

Endogenous Jurisprudential Regimes

Large-scale detection of recombination in nucleotide sequences

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