Reconciliation with Non-binary Gene Trees Revisited

Zheng, Yu; Zhang, Louxin

doi:10.1007/978-3-319-05269-4_33

Cited by 17 publications

(9 citation statements)

References 29 publications

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“…Integrative methods are generally expected to be more accurate than gene tree correction methods when gene tree heterogeneity is due to GDL, but as a result of using likelihood calculations they are also more computationally intensive. See [10][11][12][13][14][15][16] for an entry into the vast literature on this subject.…”

Section: Introductionmentioning

confidence: 99%

Non-parametric correction of estimated gene trees using TRACTION

Christensen

Molloy

Vachaspati

et al. 2020

Algorithms Mol Biol

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Motivation: Estimated gene trees are often inaccurate, due to insufficient phylogenetic signal in the single gene alignment, among other causes. Gene tree correction aims to improve the accuracy of an estimated gene tree by using computational techniques along with auxiliary information, such as a reference species tree or sequencing data. However, gene trees and species trees can differ as a result of gene duplication and loss (GDL), incomplete lineage sorting (ILS), and other biological processes. Thus gene tree correction methods need to take estimation error as well as gene tree heterogeneity into account. Many prior gene tree correction methods have been developed for the case where GDL is present. Results: Here, we study the problem of gene tree correction where gene tree heterogeneity is instead due to ILS and/or HGT. We introduce TRACTION, a simple polynomial time method that provably finds an optimal solution to the RF-optimal tree refinement and completion (RF-OTRC) Problem, which seeks a refinement and completion of a singlylabeled gene tree with respect to a given singly-labeled species tree so as to minimize the Robinson−Foulds (RF) distance. Our extensive simulation study on 68,000 estimated gene trees shows that TRACTION matches or improves on the accuracy of well-established methods from the GDL literature when HGT and ILS are both present, and ties for best under the ILS-only conditions. Furthermore, TRACTION ties for fastest on these datasets. We also show that a naive generalization of the RF-OTRC problem to multi-labeled trees is possible, but can produce misleading results where gene tree heterogeneity is due to GDL.

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Section: Introductionmentioning

confidence: 99%

Non-parametric correction of estimated gene trees using TRACTION

Christensen

Molloy

Vachaspati

et al. 2020

Algorithms Mol Biol

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show abstract

“…(1) Use AllMinTrees to output all minimally resolved supertrees, and for each one which is non-binary in general, find in linear time a resolution minimizing the reconciliation [ 16 , 32 ] or duplication [ 31 ] cost. Among all optimally resolved trees, select one of minimum cost.…”

Section: From the Supertree To The Supergenetree Problemmentioning

confidence: 99%

Reconstructing a SuperGeneTree minimizing reconciliation

2015

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Combining a set of trees on partial datasets into a single tree is a classical method for inferring large phylogenetic trees. Ideally, the combined tree should display each input partial tree, which is only possible if input trees do not contain contradictory phylogenetic information. The simplest version of the supertree problem is thus to state whether a set of trees is compatible, and if so, construct a tree displaying them all. Classically, supertree methods have been applied to the reconstruction of species trees. Here we rather consider reconstructing a super gene tree in light of a known species tree S. We define the supergenetree problem as finding, among all supertrees displaying a set of input gene trees, one supertree minimizing a reconciliation distance with S. We first show how classical exact methods to the supertree problem can be extended to the supergenetree problem. As all these methods are highly exponential, we also exhibit a natural greedy heuristic for the duplication cost, based on minimizing the set of duplications preceding the first speciation event. We then show that both the supergenetree problem and its restriction to minimizing duplications preceding the first speciation are NP-hard to approximate within a n1-ϵ factor, for any 0 < ϵ < 1. Finally, we show that a restriction of this problem to uniquely labeled speciation gene trees, which is relevant to many biological applications, is also NP-hard. Therefore, we introduce new avenues in the field of supertrees, and set the theoretical basis for the exploration of various algorithmic aspects of the problems.

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“…When the input consists of a non-binary gene tree, the reconciliation problem seeks to find a binary resolution of the gene tree that minimizes the reconciliation cost. Given the prevalence of non-binary gene trees, many efficient algorithms have been developed for this problem in the context of the simpler Duplication-Loss (DL) reconciliation model [5,[18][19][20], with the most efficient of these algorithms having an optimal O(m + n) time complexity [20]. However, the DTL reconciliation model is more general and significantly more complex than the DL reconciliation model.…”

Section: Introductionmentioning

confidence: 99%

On the Complexity of Duplication-Transfer-Loss Reconciliation with Non-binary Gene Trees

Kordi

Bansal

2015

Lecture Notes in Computer Science

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Abstract. Duplication-Transfer-Loss (DTL) reconciliation has emerged as a powerful technique for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation takes as input a gene family phylogeny and the corresponding species phylogeny, and reconciles the two by postulating speciation, gene duplication, horizontal gene transfer, and gene loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. However, gene trees are frequently non-binary. With such non-binary gene trees, the reconciliation problem seeks to find a binary resolution of the gene tree that minimizes the reconciliation cost. Given the prevalence of non-binary gene trees, many efficient algorithms have been developed for this problem in the context of the simpler Duplication-Loss (DL) reconciliation model. Yet, no efficient algorithms exist for DTL reconciliation with non-binary gene trees and the complexity of the problem remains unknown. In this work, we resolve this open question by showing that the problem is, in fact, NP-hard. Our reduction applies to both the dated and undated formulations of DTL reconciliation. By resolving this long-standing open problem, this work will spur the development of both exact and heuristic algorithms for this important problem.

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Reconciliation with Non-binary Gene Trees Revisited

Cited by 17 publications

References 29 publications

Non-parametric correction of estimated gene trees using TRACTION

Non-parametric correction of estimated gene trees using TRACTION

Reconstructing a SuperGeneTree minimizing reconciliation

On the Complexity of Duplication-Transfer-Loss Reconciliation with Non-binary Gene Trees

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