TripNet: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets

Poormohammadi, Hadi; Eslahchi, Changiz; Tusserkani, Ruzbeh

doi:10.1371/journal.pone.0106531

Cited by 10 publications

(38 citation statements)

References 13 publications

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“…This finding has important implications for species tree estimation. Several new methods for estimating species trees from large data sets have used the “rooted triples” method to build trees for subsets of the overall data set, with a second step in which the trees based on triplets are assembled into an overall species tree estimate (Ewing et al, 2008; DeGiorgio and Degnan, 2010; Liu et al, 2010; Poormohammadi et al, 2014). This method is expected to work well in the absence of gene flow, because the rooted triple with the highest probability under the coalescent model is known to be displayed on the species tree (Degnan et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

Distribution of gene tree histories under the coalescent model with gene flow

Tian

Kubatko²

2015

Preprint

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We propose a coalescent model for three species that allows gene flow be-23 tween both pairs of sister populations. The model is designed to analyze multilocus genomic 24 sequence alignments, with one sequence sampled from each of the three species. The model 25 is formulated using a Markov chain representation, which allows use of matrix exponentia-26 tion to compute analytical expressions for the probability density of gene tree genealogies. 27 The gene tree history distribution as well as the gene tree topology distribution under this 28 coalescent model with gene flow are then calculated via numerical integration. We analyze 29 the model to compare the distributions of gene tree topologies and gene tree histories for 30 species trees with differing effective population sizes and gene flow rates. Our results suggest 31 conditions under which the species tree and associated parameters are not identifiable from 32 the gene tree topology distribution when gene flow is present, but indicate that the gene 33 tree history distribution may identify the species tree and associated parameters. Thus, the 34 gene tree history distribution can be used to infer parameters such as the ancestral effective 35 population sizes and the rates of gene flow in a maximum likelihood (ML) framework. We 36 conduct computer simulations to evaluate the performance of our method in estimating these 37 parameters, and we apply our method to an Afrotropical mosquito data set (Fontaine et al., 38 2015) to demonstrate the usefulness of our method for the analysis of empirical data. 39 40 maximum likelihood, speciation. 41 42 gruence between a gene tree and the species tree for the same set of species (Maddison, 43 1997). Incomplete lineage sorting (also called deep coalescence) has long been recognized to 44 be one of the major causes of variation in gene trees across a genome (Pamilo and Nei, 1988; 45 Takahata, 1989). Another important factor leading to discord between gene trees and the 46 species tree is gene flow between populations following speciation (Maddison, 1997; Leaché 47 et al., 2013; Degnan et al., 2012). With some exceptions (noted below), these two pro-48 cesses have been studied in isolation. When carrying out phylogenetic analyses for species 49 that are substantially divergent, ignoring gene flow following speciation may not bias the 50 resulting estimates. However, with the advent of large-scale genomic data sets that allow 51 study of evolutionary relationships among closely related populations or species, the neces-52 sity of simultaneously examining these factors is becoming increasingly apparent (Eckert 53 and Carstens, 2008; Leaché et al., 2013; Huang et al., 2014). In particular, since gene flow 54 may easily occur between sister taxa following speciation, even in the presence of incomplete 55 lineage sorting (Yu et al., 2011), it is necessary to incorporate these processes simultaneously 56 into models used to analyze data for closely related species or populations. 57Degnan and Sal...

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Section: Discussionmentioning

confidence: 99%

Distribution of gene tree histories under the coalescent model with gene flow

Tian

Kubatko²

2015

Preprint

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“…When more complex networks are needed (e.g. Fig 8), not restricted algorithms such as NCHB, TripNet, RPNCH and SIMPLISTIC are applicable which try to construct a consistent network with the optimality criterions (the level or the number of reticulation nodes) [6][7][8]16]. Among the above four mentioned algorithms, SIMPLISTIC is not exact and just works for dense sets of triplets while for the other three methods there is no constraint on the input triplets.…”

Section: Plos Onementioning

confidence: 99%

“…Also inner nodes i.e. nodes except root and leaves, has in-degree 1 and out-degree at least 2 [2,7].…”

Section: Definitions and Notationsmentioning

confidence: 99%

“…The main disadvantage of the tree model is its disability to show non-treelike events (more abstractly, reticulate events) like recombination, hybridization and horizontal gene transfer [2,6]. To overcome this weakness, phylogenetic networks are introduced to generalize phylogenetic trees and represent reticulate events [1,2,[7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Netcombin: An algorithm for constructing optimal phylogenetic network from rooted triplets

Poormohammadi

Zarchi

2020

PLoS ONE

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Phylogenetic networks construction is one the most important challenge in phylogenetics. These networks can present complex non-treelike events such as gene flow, horizontal gene transfers, recombination or hybridizations. Among phylogenetic networks, rooted structures are commonly used to represent the evolutionary history of a species set, explicitly. Triplets are well known input for constructing the rooted networks. Obtaining an optimal rooted network that contains all given triplets is main problem in network construction. The optimality criteria include minimizing the level or the number of reticulation nodes. The complexity of this problem is known to be NP-hard. In this research, a new algorithm called Netcombin is introduced to construct approximately an optimal network which is consistent with input triplets. The innovation of this algorithm is based on binarization and expanding processes. The binarization process innovatively uses a measure to construct a binary rooted tree T consistent with the approximately maximum number of input triplets. Then T is expanded using a heuristic function by adding minimum number of edges to obtain final network with the approximately minimum number of reticulation nodes. In order to evaluate the proposed algorithm, Netcombin is compared with four state of the art algorithms, RPNCH, NCHB, TripNet, and SIMPLISTIC. The experimental results on simulated data obtained from biologically generated sequences data indicate that by considering the trade-off between speed and precision, the Netcombin outperforms the others.

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“…[10,18,19,22]). Even so, it has been observed that the set of triplets displayed by a level-1 network does not necessarily provide all of the information required to uniquely define or encode the network [5].…”

Section: Introductionmentioning

confidence: 99%

Reconstructing Phylogenetic Level-1 Networks from Nondense Binet and Trinet Sets

et al. 2015

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Binets and trinets are phylogenetic networks with two and three leaves, respectively. Here we consider the problem of deciding if there exists a binary level-1 phylogenetic network displaying a given set T of binary binets or trinets over a taxon set X , and constructing such a network whenever it exists. We show that this is NP-hard for trinets but polynomial-time solvable for binets. Moreover, we show that the problem is still polynomial-time solvable for inputs consisting of binets and trinets as long as the cycles in the trinets have size three. Finally, we present an O(3 |X | poly(|X |)) time algorithm for general sets of binets and trinets. The latter two algorithms generalise to instances containing level-1 networks with arbitrarily many leaves, and thus provide some of the first supernetwork algorithms for computing networks from a set of rooted phylogenetic networks. B Leo van Iersel

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TripNet: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets

Cited by 10 publications

References 13 publications

Distribution of gene tree histories under the coalescent model with gene flow

Distribution of gene tree histories under the coalescent model with gene flow

Netcombin: An algorithm for constructing optimal phylogenetic network from rooted triplets

Reconstructing Phylogenetic Level-1 Networks from Nondense Binet and Trinet Sets

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