Who is Who in Phylogenetic Networks

Publications of Yun S. Song     Order by:   Type | Year

Associated keywords

ARG branch-and-bound characterization coalescent explicit-network from-sequences galled-tree integer-linear-programming likelihood minimum-number phylogenetic-network phylogeny polynomial Program-Beagle Program-GalledTree Program-HapBound Program-SHRUB recombination reconstruction software statistical-model

Article (Journal)

1 Dan Gusfield, Vikas Bansal, Vineet Bafna and Yun S. Song. A Decomposition Theory for Phylogenetic Networks and Incompatible Characters. In JCB, Vol. 14(10):1247-1272, 2007. Keywords: explicit network, from sequences, galled tree, phylogenetic network, phylogeny, Program Beagle, Program GalledTree, recombination, reconstruction, software. Note: http://www.eecs.berkeley.edu/~yss/Pub/decomposition.pdf.         2 Yun S. Song, Zhihong Ding, Dan Gusfield, Charles Langley and Yufeng Wu. Algorithms to Distinguish the Role of Gene-Conversion from Single-Crossover Recombination in the Derivation of SNP Sequences in Populations. In JCB, Vol. 14(10):1273-1286, 2007. Keywords: ARG, from sequences, phylogenetic network, phylogeny, Program SHRUB, reconstruction. Note: http://dx.doi.org/10.1089/cmb.2007.0096.         Toggle abstract "Meiotic recombination is a fundamental biological event and one of the principal evolutionary forces responsible for shaping genetic variation within species. In addition to its fundamental role, recombination is central to several critical applied problems. The most important example is "association mapping" in populations, which is widely hoped to help find genes that influence genetic diseases (Carlson et al., 2004; Clark, 2003). Hence, a great deal of recent attention has focused on problems of inferring the historical derivation of sequences in populations when both mutations and recombinations have occurred. In the algorithms literature, most of that recent work has been directed to single-crossover recombination. However, gene-conversion is an important, and more common, form of (two-crossover) recombination which has been much less investigated in the algorithms literature. In this paper, we explicitly incorporate gene-conversion into discrete methods to study historical recombination. We are concerned with algorithms for identifying and locating the extent of historical crossing-over and gene-conversion (along with single-nucleotide mutation), and problems of constructing full putative histories of those events. The novel technical issues concern the incorporation of gene-conversion into recently developed discrete methods (Myers and Griffiths, 2003; Song et al., 2005) that compute lower and upper-bound information on the amount of needed recombination without gene-conversion. We first examine the most natural extension of the lower bound methods from Myers and Griffiths (2003), showing that the extension can be computed efficiently, but that this extension can only yield weak lower bounds. We then develop additional ideas that lead to higher lower bounds, and show how to solve, via integer-linear programming, a more biologically realistic version of the lower bound problem. We also show how to compute effective upper bounds on the number of needed single-crossovers and gene-conversions, along with explicit networks showing a putative history of mutations, single-crossovers and gene-conversions. Both lower and upper bound methods can handle data with missing entries, and the upper bound method can be used to infer missing entries with high accuracy. We validate the significance of these methods by showing that they can be effectively used to distinguish simulation-derived sequences generated without gene-conversion from sequences that were generated with gene-conversion. We apply the methods to recently studied sequences of Arabidopsis thaliana, identifying many more regions in the sequences than were previously identified (Plagnol et al., 2006), where gene-conversion may have played a significant role. Demonstration software is available at www.csif.cs.ucdavis.edu/∼gusfield. © 2007 Mary Ann Liebert, Inc." 3 Yun S. Song. A Concise Necessary and Sufficient Condition for the Existence of a Galled-Tree. In TCBB, Vol. 3(2):186-191, 2006. Keywords: characterization, from sequences, galled tree, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://www.eecs.berkeley.edu/~yss/Pub/nasc4gall.pdf.         4 Yun S. Song and Jotun Hein. Constructing Minimal Ancestral Recombination Graphs. In JCB, Vol. 12(2):147-169, 2005. Keywords: ARG, minimum number, recombination. Note: http://www.eecs.berkeley.edu/~yss/Pub/SH-JCB05.pdf.         5 Yun S. Song and Jotun Hein. On the Minimum Number of Recombination Events in the Evolutionary History of DNA Sequences. In JOMB, Vol. 48(2):160-186, 2004. Keywords: minimum number, recombination. Note: http://dx.doi.org/10.1007/s00285-003-0227-5.         Toggle abstract "In representing the evolutionary history of a set of binary DNA sequences by a connected graph, a set theoretical approach is introduced for studying recombination events. We show that set theoretical constraints have direct implications on the number of recombination events. We define a new lower bound on the number of recombination events and demonstrate the usefulness of our new approach through several explicit examples. © Springer-Verlag 2003."

InProceedings

6 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." 7 Rune Lyngsø, Yun S. Song and Jotun Hein. Minimum Recombination Histories by Branch and Bound. In WABI05, Vol. 3692:239-250 of LNCS, springer, 2005. Keywords: ARG, branch and bound, from sequences, minimum number, Program Beagle, recombination, reconstruction, software. Note: http://www.cs.ucdavis.edu/~yssong/Pub/WABI05-239.pdf.         8 Yun S. Song, Yufeng Wu and Dan Gusfield. Efficient computation of close lower and upper bounds on the minimum number of recombinations in biological sequence evolution. In ISMB05, Vol. 21:i413-i422 of BIO, 2005. Keywords: integer linear programming, minimum number, Program HapBound, Program SHRUB, recombination. Note: http://dx.doi.org/10.1093/bioinformatics/bti1033.         Toggle abstract "Motivation: We are interested in studying the evolution of DNA single nucleotide polymorphism sequences which have undergone (meiotic) recombination. For a given set of sequences, computing the minimum number of recombinations needed to explain the sequences (with one mutation per site) is a standard question of interest, but it has been shown to be NP-hard, and previous algorithms that compute it exactly work either only on very small datasets or on problems with special structure. Results: In this paper, we present efficient, practical methods for computing both upper and lower bounds on the minimum number of needed recombinations, and for constructing evolutionary histories that explain the input sequences. We study in detail the efficiency and accuracy of these algorithms on both simulated and real data sets. The algorithms produce very close upper and lower bounds, which match exactly in a surprisingly wide range of data. Thus, with the use of new, very effective lower bounding methods and an efficient algorithm for computing upper bounds, this approach allows the efficient, exact computation of the minimum number of needed recombinations, with high frequency in a large range of data. When upper and lower bounds match, evolutionary histories found by our algorithm correspond to the most parsimonious histories. © The Author 2005. Published by Oxford University Press. All rights reserved." 9 Yun S. Song and Jotun Hein. Parsimonious reconstruction of sequence evolution and haplotype blocks: Finding the minimum number of recombination events. In WABI03, Vol. 2812:287-302 of LNCS, springer, 2003. Keywords: minimum number, recombination. Note: http://www.cs.ucdavis.edu/~yssong/Pub/SH-WABI03.pdf.