Who is Who in Phylogenetic Networks

Publications related to 'likelihood'   Order by:   Type | Year

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abstract-network AIC ancestral-trait-reconstruction APX-hard bayesian BIC branch-length coalescent duplication explicit-network from-multilabeled-tree from-network from-quartets from-rooted-trees from-sequences from-splits from-trees from-unrooted-trees heuristic HMM hybridization incomplete-lineage-sorting lateral-gene-transfer likelihood lineage-sorting loss median-network netting NP-complete parsimony phylogenetic-network phylogeny population-genetics Program-ALE Program-Arlequin Program-Hybrid-coal Program-Hybrid-Lambda Program-Nepal Program-PhyloDAG Program-PhyloNet Program-PhyloNetwork Program-PhyloNetworks-SNaQ Program-SplitsTree Program-T-REX Program-TCS Program-TERA Program-TreeMix pyramid recombination reconstruction reticulogram semidirected-network software split split-decomposition split-network statistical-model statistical-parsimony statistical-test survey tripartition-distance uniqueness

2019

1 Steven Kelk, Fabio Pardi, Celine Scornavacca and Leo van Iersel. Finding the most parsimonious or likely tree in a network with respect to an alignment. In JOMB, Vol. 78:527-547, 2019. Keywords: APX hard, from network, from sequences, likelihood, NP complete, parsimony. Note: https://arxiv.org/abs/1707.03648.         2 Christopher Blair and Cécile Ané. Phylogenetic trees and networks can serve as powerful and complementary approaches for analysis of genomic data. In SB, Vol. 69(3):593-601, 2019. Keywords: likelihood, phylogenetic network, phylogeny, Program PhyloNetwork, Program PhyloNetworks SNaQ, survey.

2018

3 Paul Bastide, Claudia Solís-Lemus, Ricardo Kriebel, Kenneth William Sparks and Cécile Ané. Phylogenetic Comparative Methods on Phylogenetic Networks with Reticulations. In SB, Vol. 67(5):800-820, 2018. Keywords: ancestral trait reconstruction, from network, likelihood, Program PhyloNetworks SNaQ, software, statistical model, statistical test. Note: https://doi.org/10.1101/194050.         4 Dingqiao Wen, Yun Yu, Jiafan Zhu and Luay Nakhleh. Inferring Phylogenetic Networks Using PhyloNet. In SB, Vol. 67(4):735-740, 2018. Keywords: bayesian, likelihood, parsimony, phylogenetic network, phylogeny, Program PhyloNet, reconstruction, software.

2017

5 Christopher Bryant, Mareike Fischer, Simone Linz and Charles Semple. On the Quirks of Maximum Parsimony and Likelihood on Phylogenetic Networks. In JTB, Vol. 417:100-108, 2017. Keywords: explicit network, from sequences, likelihood, parsimony, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1505.06898.         6 Sha Zhu and James H. Degnan. Displayed Trees Do Not Determine Distinguishability Under the Network Multispecies Coalescent. In SB, Vol. 66(2):283-298, 2017. Keywords: branch length, coalescent, explicit network, from network, likelihood, phylogenetic network, phylogeny, Program Hybrid-coal, Program Hybrid-Lambda, Program PhyloNet, software, uniqueness. Note: presentation available at https://www.youtube.com/watch?v=JLYGTfEZG7g.         7 Claudia Solís-Lemus, Paul Bastide and Cécile Ané. PhyloNetworks: A Package for Phylogenetic Networks. In MBE, Vol. 34(12):3292-3298, 2017. Keywords: from sequences, from trees, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ, reconstruction, software. Note: https://doi.org/10.1093/molbev/msx235.         8 Cécile Ané. From reconstructing to using phylogenetic networks. Phyloseminar #72, 2017. Keywords: explicit network, from sequences, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ, reconstruction, semidirected network. Note: https://www.youtube.com/watch?v=PF4j_JOQP0c.

2016

9 Claudia Solís-Lemus and Cécile Ané. Inferring phylogenetic networks with maximum pseudolikelihood under incomplete lineage sorting. In PLOS Genetics, Vol. 12(3):e1005896, 2016. Keywords: explicit network, from quartets, from unrooted trees, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ. Note: http://arxiv.org/abs/1509.06075v1.

2015

10 Quan Nguyen. Likelihood-based Phylogenetic Network Inference by Approximate Structural Expectation Maximization. Master's thesis, University of Helsinki, 2015. Keywords: BIC, likelihood, phylogenetic network, phylogeny, Program PhyloDAG, reconstruction, software. Note: http://urn.fi/URN:NBN:fi-fe2015062910525.         11 Quan Nguyen and Teemu Roos. Likelihood-based inference of phylogenetic networks from sequence data by PhyloDAG. In AlCoB15, Vol. 9199:126-140 of LNCS, springer, 2015. Keywords: BIC, explicit network, from sequences, likelihood, phylogenetic network, phylogeny, Program PhyloDAG, reconstruction, software. Note: http://www.cs.helsinki.fi/u/ttonteri/pub/alcob2015.pdf.         12 Yun Yu and Luay Nakhleh. A maximum pseudo-likelihood approach for phylogenetic networks. In RECOMB-CG15, Vol. 16(Suppl 10)(S10):1-10 of BMC Genomics, BioMed Central, 2015. Keywords: explicit network, from rooted trees, hybridization, incomplete lineage sorting, likelihood, phylogenetic network, phylogeny, Program PhyloNet, reconstruction, tripartition distance. Note: http://dx.doi.org/10.1186/1471-2164-16-S10-S10.         13 Claudia Solís-Lemus. Statistical methods to infer population structure with coalescence and gene flow. PhD thesis, University of Wisconsin-Madison, 2015. Keywords: explicit network, from quartets, from unrooted trees, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ, semidirected network. Note: https://www.stat.wisc.edu/~claudia/thesis.pdf.

2014

14 Yun Yu, Jianrong Dong, Kevin J. Liu and Luay Nakhleh. Maximum likelihood inference of reticulate evolutionary histories. In PNAS, Vol. 111(46):16448-16453, 2014. Keywords: explicit network, likelihood, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1073/pnas.1407950111.

2013

15 Gergely J. Szöllösi, Eric Tannier, Nicolas Lartillot and Vincent Daubin. Lateral Gene Transfer from the Dead. In Systematic Biology, Vol. 62(3):386-397, 2013. Keywords: duplication, lateral gene transfer, likelihood, loss, phylogeny, Program TERA, reconstruction. Note: http://dx.doi.org/10.1093/sysbio/syt003.         Toggle abstract "In phylogenetic studies, the evolution of molecular sequences is assumed to have taken place along the phylogeny traced by the ancestors of extant species. In the presence of lateral gene transfer, however, this may not be the case, because the species lineage from which a gene was transferred may have gone extinct or not have been sampled. Because it is not feasible to specify or reconstruct the complete phylogeny of all species, we must describe the evolution of genes outside the represented phylogeny by modeling the speciation dynamics that gave rise to the complete phylogeny. We demonstrate that if the number of sampled species is small compared with the total number of existing species, the overwhelming majority of gene transfers involve speciation to and evolution along extinct or unsampled lineages. We show that the evolution of genes along extinct or unsampled lineages can to good approximation be treated as those of independently evolving lineages described by a few global parameters. Using this result, we derive an algorithm to calculate the probability of a gene tree and recover the maximum-likelihood reconciliation given the phylogeny of the sampled species. Examining 473 near-universal gene families from 36 cyanobacteria, we find that nearly a third of transfer events (28%) appear to have topological signatures of evolution along extinct species, but only approximately 6% of transfers trace their ancestry to before the common ancestor of the sampled cyanobacteria. © 2013 The Author(s)." 16 Gergely J. Szöllösi, Wojciech Rosikiewicz, Bastien Boussau, Eric Tannier and Vincent Daubin. Efficient Exploration of the Space of Reconciled Gene Trees. In Systematic Biology, Vol. 62(6):901-912, 2013. Keywords: duplication, explicit network, lateral gene transfer, likelihood, loss, phylogeny, Program ALE, reconstruction. Note: http://arxiv.org/abs/1306.2167.         Toggle abstract "Gene trees record the combination of gene-level events, such as duplication, transfer and loss (DTL), and species-level events, such as speciation and extinction. Gene tree-species tree reconciliation methods model these processes by drawing gene trees into the species tree using a series of gene and species-level events. The reconstruction of gene trees based on sequence alone almost always involves choosing between statistically equivalent or weakly distinguishable relationships that could be much better resolved based on a putative species tree. To exploit this potential for accurate reconstruction of gene trees, the space of reconciled gene trees must be explored according to a joint model of sequence evolution and gene tree-species tree reconciliation. Here we present amalgamated likelihood estimation (ALE), a probabilistic approach to exhaustively explore all reconciled gene trees that can be amalgamated as a combination of clades observed in a sample of gene trees. We implement the ALE approach in the context of a reconciliation model (Szöllo{double acute}si et al. 2013), which allows for the DTL of genes. We use ALE to efficiently approximate the sum of the joint likelihood over amalgamations and to find the reconciled gene tree that maximizes the joint likelihood among all such trees. We demonstrate using simulations that gene trees reconstructed using the joint likelihood are substantially more accurate than those reconstructed using sequence alone. Using realistic gene tree topologies, branch lengths, and alignment sizes, we demonstrate that ALE produces more accurate gene trees even if the model of sequence evolution is greatly simplified. Finally, examining 1099 gene families from 36 cyanobacterial genomes we find that joint likelihood-based inference results in a striking reduction in apparent phylogenetic discord, with respectively. 24%, 59%, and 46% reductions in the mean numbers of duplications, transfers, and losses per gene family. The open source implementation of ALE is available from https://github.com/ssolo/ALE.git. © The Author(s) 2013."

2012

17 Hyun Jung Park and Luay Nakhleh. Inference of reticulate evolutionary histories by maximum likelihood: The performance of information criteria. In RECOMB-CG'12, Vol. 13(suppl 19):S12 of BMCB, 2012. Keywords: AIC, BIC, explicit network, heuristic, likelihood, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://www.biomedcentral.com/1471-2105/13/S19/S12.         18 Hyun Jung Park. Towards Accurate Reconstruction of Phylogenetic Networks. PhD thesis, Rice University, U.S.A., 2012. Keywords: explicit network, likelihood, parsimony, phylogenetic network, phylogeny, reconstruction. Note: http://scholarship.rice.edu/handle/1911/64705.         19 Joseph K. Pickrell and Jonathan K. Pritchard. Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data. In PLoS Genetics, Vol. 8(11):e1002967, 2012. Keywords: explicit network, heuristic, likelihood, phylogenetic network, phylogeny, population genetics, Program TreeMix. Note: http://dx.doi.org/10.1371/journal.pgen.1002967.         Toggle abstract "Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com. © 2012 Pickrell, Pritchard."

2011

20 Gergely J. Szöllösi and Vincent Daubin. Modeling Gene Family Evolution and Reconciling Phylogenetic Discord. In Evolutionary Genomics, Statistical and Computational Methods, Volume 2, Methods in Molecular Biology, Vol. 856:29-51, Chapter 2, springer, 2011. Keywords: duplication, from multilabeled tree, lateral gene transfer, likelihood, phylogeny, reconstruction, statistical model. Note: ArXiv version entitled The pattern and process of gene family evolution.         Toggle abstract "Large-scale databases are available that contain homologous gene families constructed from hundreds of complete genome sequences from across the three domains of life. Here, we discuss the approaches of increasing complexity aimed at extracting information on the pattern and process of gene family evolution from such datasets. In particular, we consider the models that invoke processes of gene birth (duplication and transfer) and death (loss) to explain the evolution of gene families. First, we review birth-and-death models of family size evolution and their implications in light of the universal features of family size distribution observed across different species and the three domains of life. Subsequently, we proceed to recent developments on models capable of more completely considering information in the sequences of homologous gene families through the probabilistic reconciliation of the phylogenetic histories of individual genes with the phylogenetic history of the genomes in which they have resided. To illustrate the methods and results presented, we use data from the HOGENOM database, demonstrating that the distribution of homologous gene family sizes in the genomes of the eukaryota, archaea, and bacteria exhibits remarkably similar shapes. We show that these distributions are best described by models of gene family size evolution, where for individual genes the death (loss) rate is larger than the birth (duplication and transfer) rate but new families are continually supplied to the genome by a process of origination. Finally, we use probabilistic reconciliation methods to take into consideration additional information from gene phylogenies, and find that, for prokaryotes, the majority of birth events are the result of transfer. © 2012 Springer Science+Business Media, LLC."

2009

21 Sagi Snir and Tamir Tuller. The NET-HMM approach: Phylogenetic Network Inference by Combining Maximum Likelihood and Hidden Markov Models. In JBCB, Vol. 7(4):625-644, 2009. Keywords: explicit network, from sequences, HMM, lateral gene transfer, likelihood, phylogenetic network, phylogeny, statistical model. Note: http://research.haifa.ac.il/~ssagi/published%20papers/Snir-NET-HMM-JBCB-2009.pdf.         Toggle abstract "Horizontal gene transfer (HGT) is the event of transferring genetic material from one lineage in the evolutionary tree to a different lineage. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Although the prevailing assumption is of complete HGT, cases of partial HGT (which are also named chimeric HGT) where only part of a gene is horizontally transferred, have also been reported, albeit less frequently. In this work we suggest a new probabilistic model, the NET-HMM, for analyzing and modeling phylogenetic networks. This new model captures the biologically realistic assumption that neighboring sites of DNA or amino acid sequences are not independent, which increases the accuracy of the inference. The model describes the phylogenetic network as a Hidden Markov Model (HMM), where each hidden state is related to one of the network's trees. One of the advantages of the NET-HMM is its ability to infer partial HGT as well as complete HGT. We describe the properties of the NET-HMM, devise efficient algorithms for solving a set of problems related to it, and implement them in software. We also provide a novel complementary significance test for evaluating the fitness of a model (NET-HMM) to a given dataset. Using NET-HMM, we are able to answer interesting biological questions, such as inferring the length of partial HGT's and the affected nucleotides in the genomic sequences, as well as inferring the exact location of HGT events along the tree branches. These advantages are demonstrated through the analysis of synthetical inputs and three different biological inputs. © 2009 Imperial College Press." 22 Chen Meng and Laura S. Kubatko. Detecting hybrid speciation in the presence of incomplete lineage sorting using gene tree incongruence: A model. In Theoretical Population Biology, Vol. 75(1):35-45, 2009. Keywords: bayesian, coalescent, from network, from rooted trees, hybridization, likelihood, lineage sorting, phylogenetic network, phylogeny, statistical model. Note: http://dx.doi.org/10.1016/j.tpb.2008.10.004.         Toggle abstract "The application of phylogenetic inference methods, to data for a set of independent genes sampled randomly throughout the genome, often results in substantial incongruence in the single-gene phylogenetic estimates. Among the processes known to produce discord between single-gene phylogenies, two of the best studied in a phylogenetic context are hybridization and incomplete lineage sorting. Much recent attention has focused on the development of methods for estimating species phylogenies in the presence of incomplete lineage sorting, but phylogenetic models that allow for hybridization have been more limited. Here we propose a model that allows incongruence in single-gene phylogenies to be due to both hybridization and incomplete lineage sorting, with the goal of determining the contribution of hybridization to observed gene tree incongruence in the presence of incomplete lineage sorting. Using our model, we propose methods for estimating the extent of the role of hybridization in both a likelihood and a Bayesian framework. The performance of our methods is examined using both simulated and empirical data. © 2008 Elsevier Inc. All rights reserved."

2008

23 Rune Lyngsø, Yun S. Song and Jotun Hein. Accurate Computation of Likelihoods in the Coalescent with Recombination via Parsimony. In RECOMB08, Vol. 4955:463-477 of LNCS, springer, 2008. Keywords: coalescent, likelihood, phylogenetic network, phylogeny, recombination, statistical model. Note: http://dx.doi.org/10.1007/978-3-540-78839-3_41.         Toggle abstract "Understanding the variation of recombination rates across a given genome is crucial for disease gene mapping and for detecting signatures of selection, to name just a couple of applications. A widely-used method of estimating recombination rates is the maximum likelihood approach, and the problem of accurately computing likelihoods in the coalescent with recombination has received much attention in the past. A variety of sampling and approximation methods have been proposed, but no single method seems to perform consistently better than the rest, and there still is great value in developing better statistical methods for accurately computing likelihoods. So far, with the exception of some two-locus models, it has remained unknown how the true likelihood exactly behaves as a function of model parameters, or how close estimated likelihoods are to the true likelihood. In this paper, we develop a deterministic, parsimony-based method of accurately computing the likelihood for multi-locus input data of moderate size. We first find the set of all ancestral configurations (ACs) that occur in evolutionary histories with at most k crossover recombinations. Then, we compute the likelihood by summing over all evolutionary histories that can be constructed only using the ACs in that set. We allow for an arbitrary number of crossing over, coalescent and mutation events in a history, as long as the transitions stay within that restricted set of ACs. For given parameter values, by gradually increasing the bound k until the likelihood stabilizes, we can obtain an accurate estimate of the likelihood. At least for moderate crossover rates, the algorithm-based method described here opens up a new window of opportunities for testing and fine-tuning statistical methods for computing likelihoods. © 2008 Springer-Verlag Berlin Heidelberg." 24 Sagi Snir and Tamir Tuller. Novel Phylogenetic Network Inference by Combining Maximum Likelihood and Hidden Markov Models. In WABI08, Vol. 5251:354-368 of LNCS, springer, 2008. Keywords: explicit network, from sequences, HMM, lateral gene transfer, likelihood, phylogenetic network, phylogeny, statistical model. Note: http://dx.doi.org/10.1007/978-3-540-87361-7_30.         Toggle abstract "Horizontal Gene Transfer (HGT) is the event of transferring genetic material from one lineage in the evolutionary tree to a different lineage. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Although the prevailing assumption is of complete HGT, cases of partial HGT (which are also named chimeric HGT) where only part of a gene is horizontally transferred, have also been reported, albeit less frequently. In this work we suggest a new probabilistic model for analyzing and modeling phylogenetic networks, the NET-HMM. This new model captures the biologically realistic assumption that neighboring sites of DNA or amino acid sequences are not independent, which increases the accuracy of the inference. The model describes the phylogenetic network as a Hidden Markov Model (HMM), where each hidden state is related to one of the network's trees. One of the advantages of the NET-HMM is its ability to infer partial HGT as well as complete HGT. We describe the properties of the NET-HMM, devise efficient algorithms for solving a set of problems related to it, and implement them in software. We also provide a novel complementary significance test for evaluating the fitness of a model (NET-HMM) to a given data set. Using NET-HMM we are able to answer interesting biological questions, such as inferring the length of partial HGT's and the affected nucleotides in the genomic sequences, as well as inferring the exact location of HGT events along the tree branches. These advantages are demonstrated through the analysis of synthetical inputs and two different biological inputs. © 2008 Springer-Verlag Berlin Heidelberg."

2007

25 Tamir Tuller and Sagi Snir. The NET-HMM: a HMM Based Likelihood Model for Evolutionary Networks. 2007. Keywords: lateral gene transfer, likelihood, phylogenetic network, phylogeny, reconstruction, statistical model. Note: Poster presented at the eleventh Annual International Conference on Research in Computational Molecular Biology (RECOMB'07), http://www.qb3.org/recomb07/posters/Tuller013043013RECOMB_HMM1.pdf.

2006

26 Guohua Jin, Luay Nakhleh, Sagi Snir and Tamir Tuller. Maximum Likelihood of Phylogenetic Networks. In BIO, Vol. 22(21):2604-2611, 2006. Keywords: explicit network, likelihood, phylogenetic network, phylogeny, Program Nepal, reconstruction. Note: http://www.cs.rice.edu/~nakhleh/Papers/NetworksML06.pdf, supplementary material: http://www.cs.rice.edu/~nakhleh/Papers/Supp-ML.pdf.

2005

27 David Bryant. Extending tree models to splits networks. In Lior Pachter and Bernd Sturmfels editors, Algebraic Statistics for Computational Biology, Pages 322-334, Cambridge University Press, 2005. Keywords: abstract network, from splits, likelihood, phylogenetic network, phylogeny, split, split network, statistical model. Note: http://www.math.auckland.ac.nz/~bryant/Papers/05ascbChapter.pdf.

2001

28 David Posada and Keith A. Crandall. Intraspecific gene genealogies: trees grafting into networks. In TEE, Vol. 16(1):37-45, 2001. Keywords: likelihood, median network, netting, parsimony, phylogenetic network, phylogeny, Program Arlequin, Program SplitsTree, Program T REX, Program TCS, pyramid, reticulogram, split decomposition, statistical parsimony, survey. Note: http://darwin.uvigo.es/download/papers/09.networks01.pdf.

2000

29 Korbinian Strimmer and Vincent Moulton. Likelihood Analysis of Phylogenetic Networks Using Directed Graphical Models. In MBE, Vol. 17(6):875-881, 2000. Keywords: bayesian, likelihood, median network, split network, statistical model. Note: http://mbe.oxfordjournals.org/cgi/content/abstract/17/6/875.

1993

30 Arndt von Haeseler and Gary A. Churchill. Network models for sequence evolution. In JME, Vol. 37(1):77-85, 1993. Keywords: explicit network, likelihood, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://dx.doi.org/10.1007/BF00170465.