SuperFine: fast and accurate supertree estimation

Many research groups are estimating trees containing anywhere from a few thousands to hundreds of thousands of species, toward the eventual goal of the estimation of a Tree of Life, containing perhaps as many as several million leaves. These phylogenetic estimations present enormous computational challenges, and current computational methods are likely to fail to run even on data sets in the low end of this range. One approach to estimate a large species tree is to use phylogenetic estimation methods (such as maximum likelihood) on a supermatrix produced by concatenating multiple sequence alignments for a collection of markers; however, the most accurate of these phylogenetic estimation methods are extremely computationally intensive for data sets with more than a few thousand sequences. Supertree methods, which assemble phylogenetic trees from a collection of trees on subsets of the taxa, are important tools for phylogeny estimation where phylogenetic analyses based upon maximum likelihood (ML) are infeasible. In this paper, we introduce SuperFine, a meta-method that utilizes a novel two-step procedure in order to improve the accuracy and scalability of supertree methods. Our study, using both simulated and empirical data, shows that SuperFine-boosted supertree methods produce more accurate trees than standard supertree methods, and run quickly on very large data sets with thousands of sequences. Furthermore, SuperFine-boosted matrix representation with parsimony (MRP, the most well-known supertree method) approaches the accuracy of ML methods on supermatrix data sets under realistic conditions.     

On the Ancestral Compatibility of Two Phylogenetic Trees with Nested Taxa

Compatibility of phylogenetic trees is the most important concept underlying widely-used methods for assessing the agreement of different phylogenetic trees with overlapping taxa and combining them into common supertrees to reveal the tree of life. The notion of ancestral compatibility of phylogenetic trees with nested taxa was recently introduced. In this paper we analyze in detail the meaning of this compatibility from the points of view of the local structure of the trees, of the existence of embeddings into a common supertree, and of the joint properties of their cluster representations. Our analysis leads to a very simple polynomial-time algorithm for testing this compatibility, which we have implemented and is freely available for download from the BioPerl collection of Perl modules for computational biology.     

PhySIC: a veto supertree method with desirable properties

This paper focuses on veto supertree methods; i.e., methods that aim at producing a conservative synthesis of the relationships agreed upon by all source trees. We propose desirable properties that a supertree should satisfy in this framework, namely the non-contradiction property (PC) and the induction property (PI). The former requires that the supertree does not contain relationships that contradict one or a combination of the source topologies, whereas the latter requires that all topological information contained in the supertree is present in a source tree or collectively induced by several source trees. We provide simple examples to illustrate their relevance and that allow a comparison with previously advocated properties. We show that these properties can be checked in polynomial time for any given rooted supertree. Moreover, we introduce the PhySIC method (PHYlogenetic Signal with Induction and non-Contradiction). For k input trees spanning a set of n taxa, this method produces a supertree that satisfies the above-mentioned properties in O(kn(3) + n(4)) computing time. The polytomies of the produced supertree are also tagged by labels indicating areas of conflict as well as those with insufficient overlap. As a whole, PhySIC enables the user to quickly summarize consensual information of a set of trees and localize groups of taxa for which the data require consolidation. Lastly, we illustrate the behaviour of PhySIC on primate data sets of various sizes, and propose a supertree covering 95% of all primate extant genera. The PhySIC algorithm is available at http://atgc.lirmm.fr/cgi-bin/PhySIC.     

Assessment of the accuracy of matrix representation with parsimony analysis supertree construction

Despite the growing popularity of supertree construction for combining phylogenetic information to produce more inclusive phylogenies, large-scale performance testing of this method has not been done. Through simulation, we tested the accuracy of the most widely used supertree method, matrix representation with parsimony analysis (MRP), with respect to a (maximum parsimony) total evidence solution and a known model tree. When source trees overlap completely, MRP provided a reasonable approximation of the total evidence tree; agreement was usually > 85%. Performance improved slightly when using smaller, more numerous, or more congruent source trees, and especially when elements were weighted in proportion to the bootstrap frequencies of the nodes they represented on each source tree ("weighted MRP"). Although total evidence always estimated the model tree slightly better than nonweighted MRP methods, weighted MRP in turn usually out-performed total evidence slightly. When source studies were even moderately nonoverlapping (i.e., sharing only three-quarters of the taxa), the high proportion of missing data caused a loss in resolution that severely degraded the performance for all methods, including total evidence. In such cases, even combining more trees, which had positive effects elsewhere, did not improve accuracy. Instead, "seeding" the supertree or total evidence analyses with a single largely complete study improved performance substantially. This finding could be an important strategy for any studies that seek to combine phylogenetic information. Overall, our results suggest that MRP supertree construction provides a reasonable approximation of a total evidence solution and that weighted MRP should be used whenever possible.     

Robustness of Topological Supertree Methods for Reconciling Dense Incompatible Data

Given a collection of rooted phylogenetic trees with overlapping sets of leaves, a compatible supertree $S$ is a single tree whose set of leaves is the union of the input sets of leaves and such that $S$ agrees with each input tree when restricted to the leaves of the input tree. Typically with trees from real data, no compatible supertree exists, and various methods may be utilized to reconcile the incompatibilities in the input trees. This paper focuses on a measure of robustness of a supertree method called its ``radius" $R$. The larger the value of $R$ is, the further the data set can be from a natural correct tree $T$ and yet the method will still output $T$. It is shown that the maximal possible radius for a method is $R = 1/2$. Many familiar methods, both for supertrees and consensus trees, are shown to have $R = 0$, indicating that they need not output a tree $T$ that would seem to be the natural correct answer. A polynomial-time method Normalized Triplet Supertree (NTS) with the maximal possible $R = 1/2$ is defined. A geometric interpretion is given, and NTS is shown to solve an optimization problem. Additional properties of NTS are described.     

Efficient FPT Algorithms for (Strict) Compatibility of Unrooted Phylogenetic Trees

In phylogenetics, a central problem is to infer the evolutionary relationships between a set of species X; these relationships are often depicted via a phylogenetic tree—a tree having its leaves labeled bijectively by elements of X and without degree-2 nodes—called the “species tree.” One common approach for reconstructing a species tree consists in first constructing several phylogenetic trees from primary data (e.g., DNA sequences originating from some species in X), and then constructing a single phylogenetic tree maximizing the “concordance” with the input trees. The obtained tree is our estimation of the species tree and, when the input trees are defined on overlapping—but not identical—sets of labels, is called “supertree.” In this paper, we focus on two problems that are central when combining phylogenetic trees into a supertree: the compatibility and the strict compatibility problems for unrooted phylogenetic trees. These problems are strongly related, respectively, to the notions of “containing as a minor” and “containing as a topological minor” in the graph community. Both problems are known to be fixed parameter tractable in the number of input trees k, by using their expressibility in monadic second-order logic and a reduction to graphs of bounded treewidth. Motivated by the fact that the dependency on k of these algorithms is prohibitively large, we give the first explicit dynamic programming algorithms for solving these problems, both running in time \(2^{O(k^2)} \cdot n\), where n is the total size of the input.     

Novel versus unsupported clades: assessing the qualitative support for clades in MRP supertrees

Matrix representation with parsimony (MRP) supertree construction has been criticized because the supertree may specify clades that are contradicted by every source tree contributing to it. Such unsupported clades may also occur using other supertree methods; however, their incidence is largely unknown. In this study, I investigated the frequency of unsupported clades in both simulated and empirical MRP supertrees. Here, I propose a new index, QS, to quantify the qualitative support for a supertree and its clades among the set of source trees. Results show that unsupported clades are very rare in MRP supertrees, occurring most often when there are few source trees that all possess the same set of taxa. However, even under these conditions the frequency of unsupported clades was <0.2%. Unsupported clades were absent from both the Carnivora and Lagomorpha supertrees, reflecting the use of large numbers of source trees for both. The proposed QS indices are correlated broadly with another measure of quantitative clade support (bootstrap frequencies, as derived from resampling of the MRP matrix) but appear to be more sensitive. More importantly, they sample at the level of the source trees and thus, unlike the bootstrap, are suitable for summarizing the support of MRP supertree clades.     

Performance of flip supertree construction with a heuristic algorithm

Supertree methods are used to assemble separate phylogenetic trees with shared taxa into larger trees (supertrees) in an effort to construct more comprehensive phylogenetic hypotheses. In spite of much recent interest in supertrees, there are still few methods for supertree construction. The flip supertree problem is an error correction approach that seeks to find a minimum number of changes (flips) to the matrix representation of the set of input trees to resolve their incompatibilities. A previous flip supertree algorithm was limited to finding exact solutions and was only feasible for small input trees. We developed a heuristic algorithm for the flip supertree problem suitable for much larger input trees. We used a series of 48- and 96-taxon simulations to compare supertrees constructed with the flip supertree heuristic algorithm with supertrees constructed using other approaches, including MinCut (MC), modified MC (MMC), and matrix representation with parsimony (MRP). Flip supertrees are generally far more accurate than supertrees constructed using MC or MMC algorithms and are at least as accurate as supertrees built with MRP. The flip supertree method is therefore a viable alternative to other supertree methods when the number of taxa is large.     

MRL and SuperFine+MRL: new supertree methods

Background

Supertree methods combine trees on subsets of the full taxon set together to produce a tree on the entire set of taxa. Of the many supertree methods, the most popular is MRP (Matrix Representation with Parsimony), a method that operates by first encoding the input set of source trees by a large matrix (the "MRP matrix") over {0,1, ?}, and then running maximum parsimony heuristics on the MRP matrix. Experimental studies evaluating MRP in comparison to other supertree methods have established that for large datasets, MRP generally produces trees of equal or greater accuracy than other methods, and can run on larger datasets. A recent development in supertree methods is SuperFine+MRP, a method that combines MRP with a divide-and-conquer approach, and produces more accurate trees in less time than MRP. In this paper we consider a new approach for supertree estimation, called MRL (Matrix Representation with Likelihood). MRL begins with the same MRP matrix, but then analyzes the MRP matrix using heuristics (such as RAxML) for 2-state Maximum Likelihood.

Results

We compared MRP and SuperFine+MRP with MRL and SuperFine+MRL on simulated and biological datasets. We examined the MRP and MRL scores of each method on a wide range of datasets, as well as the resulting topological accuracy of the trees. Our experimental results show that MRL, coupled with a very good ML heuristic such as RAxML, produced more accurate trees than MRP, and MRL scores were more strongly correlated with topological accuracy than MRP scores.

Conclusions

SuperFine+MRP, when based upon a good MP heuristic, such as TNT, produces among the best scores for both MRP and MRL, and is generally faster and more topologically accurate than other supertree methods we tested.     

Robinson-Foulds Supertrees

Background  

Supertree methods synthesize collections of small phylogenetic trees with incomplete taxon overlap into comprehensive trees, or supertrees, that include all taxa found in the input trees. Supertree methods based on the well established Robinson-Foulds (RF) distance have the potential to build supertrees that retain much information from the input trees. Specifically, the RF supertree problem seeks a binary supertree that minimizes the sum of the RF distances from the supertree to the input trees. Thus, an RF supertree is a supertree that is consistent with the largest number of clusters (or clades) from the input trees.     

Quarnet Inference Rules for Level-1 Networks

An important problem in phylogenetics is the construction of phylogenetic trees. One way to approach this problem, known as the supertree method, involves inferring a phylogenetic tree with leaves consisting of a set X of species from a collection of trees, each having leaf-set some subset of X. In the 1980s, Colonius and Schulze gave certain inference rules for deciding when a collection of 4-leaved trees, one for each 4-element subset of X, can be simultaneously displayed by a single supertree with leaf-set X. Recently, it has become of interest to extend this and related results to phylogenetic networks. These are a generalization of phylogenetic trees which can be used to represent reticulate evolution (where species can come together to form a new species). It has recently been shown that a certain type of phylogenetic network, called a (unrooted) level-1 network, can essentially be constructed from 4-leaved trees. However, the problem of providing appropriate inference rules for such networks remains unresolved. Here, we show that by considering 4-leaved networks, called quarnets, as opposed to 4-leaved trees, it is possible to provide such rules. In particular, we show that these rules can be used to characterize when a collection of quarnets, one for each 4-element subset of X, can all be simultaneously displayed by a level-1 network with leaf-set X. The rules are an intriguing mixture of tree inference rules, and an inference rule for building up a cyclic ordering of X from orderings on subsets of X of size 4. This opens up several new directions of research for inferring phylogenetic networks from smaller ones, which could yield new algorithms for solving the supernetwork problem in phylogenetics.     

Minority rule supertrees? MRP,Compatibility, and Minimum Flip may display the least frequent groups

New examples are presented, showing that supertree methods such as matrix representation with parsimony, minimum flip trees, and compatibility analysis of the matrix representing the input trees, produce supertrees that cannot be interpreted as displaying the groups present in the majority of the input trees. These methods may produce a supertree displaying some groups present in the minority of the trees, and contradicted by the majority. Of the three methods, compatibility analysis is the least used, but it seems to be the one that differs the least from majority rule consensus. The three methods are similar in that they choose the supertree(s) that best fit the set of input trees (quantified as some measure of the fit to the matrix representation of the input trees); in the case of complete trees, it is argued that, for a supertree method to be equivalent to majority rule or frequency difference consensus, two necessary (but not sufficient) conditions must be met. First, the measure of fit between a supertree and an input tree must be symmetrical. Second, the fit for a character representing a group must be measured as absolute: either it fits or it does not fit. In the restricted case of complete and equally resolved input trees, compatibility analysis (unlike MRP and minimum flipping) fulfils these two conditions: it is symmetrical (i.e., as long as the trees have the same taxon sets and are equally resolved, the number of characters in the matrix representation of tree A that require homoplasy in tree B is always the same as the number of characters in the matrix representation of tree B that require homoplasy in tree A) and it measures fit as all‐or‐none. In the case of just two complete and equally resolved input trees, the two conditions (symmetry and absolute fit) are necessary and sufficient, which explains why the compatibility analysis of such trees behaves as majority consensus. With more than two such trees, these conditions are still necessary but no longer sufficient for the equivalence; in such cases, the compatibility supertree may differ significantly from the majority rule consensus, even when these conditions apply (as shown by example). MRP and minimum flipping are asymmetric and measure various degrees of fit for each character, which explains why they often behave very differently from majority rule procedures, and why they are very likely to have groups contradicted by each of the input trees, or groups supported by a minority of the input trees. © The Willi Hennig Society 2005.     

Majority-rule supertrees

Most supertree methods proposed to date are essentially ad hoc, rather than designed with particular properties in mind. Although the supertree problem remains difficult, one promising avenue is to develop from better understood consensus methods to the more general supertree setting. Here, we generalize the widely used majority-rule consensus method to the supertree setting. The majority-rule consensus tree is the strict consensus of the median trees under the symmetric-difference metric, so we can generalize the consensus method by generalizing this metric to trees with differing leaf sets. There are two different natural generalizations, based on pruning or grafting leaves to produce comparable trees, and these two generalizations produce two different, but related, majority-rule supertree methods.     

Genus-level supertree of Cyprinidae (Actinopterygii: Cypriniformes), partitioned qualitative clade support and test of macro-evolutionary scenarios

We used the supertree approach of matrix representation with parsimony to reconstruct to date the most exhaustive (genus‐level) phylogeny of Cyprinidae. The supertree of Cyprinidae, representing 397 taxa (237 nominal genera) and 990 pseudocharacters, was well resolved (96%) through extended consensus majority rule, although 36 nodes (9.4%) were unsupported. The proportion of shared taxa among source trees was very low after calculation of the taxonomic coverage index (TCI = 0.059), which is proposed here as a more accurate alternative to the usual ratios calculated from the number of pseudo‐characters or source trees per taxon. We define a new index for the calculation of partitioned qualitative clade support, the partitioned rQS (_prQS), which offers a straightforward visualization of the relative supports of source tree partitions at supertree nodes.The use of _prQS showed that the molecular source tree partition contributed to most node supports within the supertree of Cyprinidae (73%, contra 21% for the morphological partition) and evidenced a fair proportion of conflict at nodes between the two partitions (21%), notably reflecting (i) the greater number and resolution of molecular source trees, and (ii) potential morphological convergences. Most of the higher‐level relationships within Cyprinidae were supported by both morphological and molecular source tree partitions. Our supertree showed a well‐supported dichotomy between a clade consisting of a ‘barbine’ + ‘rasborine’ lineage, sister group to (Barbinae [paraphyletic], (Cyprininae, Labeoninae)), and a clade consisting of other rasborines (large polytomy) and the two monophyletic groups ((Tincinae, Tanichthys), (Ecocarpia, (Acheilognathinae, (Gobioninae, Leuciscinae)))) and (Squaliobarbinae, (Xenocyprinae, Cultrinae)). Through the non‐monophyly of almost all the traditional subfamilies of Cyprinidae and 34 genera, our supertree exemplified the taxonomic chaos that reigns in the classification of the family. It also highlighted that further efforts should aim at increasing taxonomic sampling and generating alternative phylogenetic signals, notably for the still poorly apprehended Tincinae, Squaliobarbinae, Acheilognathinae, Gobioninae, and Rasborinae, the latter representing a key taxon for the understanding of early cyprinid evolution. Our supertree also proved useful for testing macro‐evolutionary scenarios at a wide taxonomic scale. Ancestral reconstructions using linear parsimony confirmed that the Oriental tropical region was the centre of origin of Cyprinidae, and identified three Oriental‐to‐Palaearctic, two Palaearctic‐to‐Nearctic, and one Oriental‐to‐Afrotropical major migration events. On the other hand, we almost completely rejected the hypothesis of presence of barbels as a plesiomorphic condition within Cyprinidae (although ambiguous for maxillary barbels of the Barbinae‐Cyprininae type). The supertree of Cyprinidae serves as a basis to discuss the applications and bias of the newly proposed _prQS, to provide future guidelines for a better achievement of cyprinid phylogeny, and to elaborate further on inter‐continental migrations and the adaptive value of barbels.     

Imputing supertrees and supernetworks from quartets

Inferring species phylogenies is an important part of understanding molecular evolution. Even so, it is well known that an accurate phylogenetic tree reconstruction for a single gene does not always necessarily correspond to the species phylogeny. One commonly accepted strategy to cope with this problem is to sequence many genes; the way in which to analyze the resulting collection of genes is somewhat more contentious. Supermatrix and supertree methods can be used, although these can suppress conflicts arising from true differences in the gene trees caused by processes such as lineage sorting, horizontal gene transfer, or gene duplication and loss. In 2004, Huson et al. (IEEE/ACM Trans. Comput. Biol. Bioinformatics 1:151-158) presented the Z-closure method that can circumvent this problem by generating a supernetwork as opposed to a supertree. Here we present an alternative way for generating supernetworks called Q-imputation. In particular, we describe a method that uses quartet information to add missing taxa into gene trees. The resulting trees are subsequently used to generate consensus networks, networks that generalize strict and majority-rule consensus trees. Through simulations and application to real data sets, we compare Q-imputation to the matrix representation with parsimony (MRP) supertree method and Z-closure, and demonstrate that it provides a useful complementary tool.     

Trees of trees: an approach to comparing multiple alternative phylogenies

Phylogenetic analysis very commonly produces several alternative trees for a given fixed set of taxa. For example, different sets of orthologous genes may be analyzed, or the analysis may sample from a distribution of probable trees. This article describes an approach to comparing and visualizing multiple alternative phylogenies via the idea of a "tree of trees" or "meta-tree." A meta-tree clusters phylogenies with similar topologies together in the same way that a phylogeny clusters species with similar DNA sequences. Leaf nodes on a meta-tree correspond to the original set of phylogenies given by some analysis, whereas interior nodes correspond to certain consensus topologies. The construction of meta-trees is motivated by analogy with construction of a most parsimonious tree for DNA data, but instead of using DNA letters, in a meta-tree the characters are partitions or splits of the set of taxa. An efficient algorithm for meta-tree construction is described that makes use of a known relationship between the majority consensus and parsimony in terms of gain and loss of splits. To illustrate these ideas meta-trees are constructed for two datasets: a set of gene trees for species of yeast and trees from a bootstrap analysis of a set of gene trees in ray-finned fish. A software tool for constructing meta-trees and comparing alternative phylogenies is available online, and the source code can be obtained from the author.     

Building supertrees: an empirical assessment using the grass family (Poaceae)

Large and comprehensive phylogenetic trees are desirable for studying macroevolutionary processes and for classification purposes. Such trees can be obtained in two different ways. Either the widest possible range of taxa can be sampled and used in a phylogenetic analysis to produce a "big tree," or preexisting topologies can be used to create a supertree. Although large multigene analyses are often favored, combinable data are not always available, and supertrees offer a suitable solution. The most commonly used method of supertree reconstruction, matrix representation with parsimony (MRP), is presented here. We used a combined data set for the Poaceae to (1) assess the differences between an approach that uses combined data and one that uses different MRP modifications based on the character partitions and (2) investigate the advantages and disadvantages of these modifications. Baum and Ragan and Purvis modifications gave similar results. Incorporating bootstrap support associated with pre-existing topologies improved Baum and Ragan modification and its similarity with a combined analysis. Finally, we used the supertree reconstruction approach on 55 published phylogenies to build one of most comprehensive phylogenetic trees published for the grass family including 403 taxa and discuss its strengths and weaknesses in relation to other published hypotheses.     

A simulation study comparing supertree and combined analysis methods using SMIDGen

Background  

Supertree methods comprise one approach to reconstructing large molecular phylogenies given multi-marker datasets: trees are estimated on each marker and then combined into a tree (the "supertree") on the entire set of taxa. Supertrees can be constructed using various algorithmic techniques, with the most common being matrix representation with parsimony (MRP). When the data allow, the competing approach is a combined analysis (also known as a "supermatrix" or "total evidence" approach) whereby the different sequence data matrices for each of the different subsets of taxa are concatenated into a single supermatrix, and a tree is estimated on that supermatrix.     

PhySIC_IST: cleaning source trees to infer more informative supertrees

Background  

Supertree methods combine phylogenies with overlapping sets of taxa into a larger one. Topological conflicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conflicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conflicting resolutions. When the source trees host a significant number of topological conflicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees.     

Quartet MaxCut: A fast algorithm for amalgamating quartet trees

Accurate phylogenetic reconstruction methods are inherently computationally heavy and therefore are limited to relatively small numbers of taxa. Supertree construction is the task of amalgamating small trees over partial sets into a big tree over the complete taxa set. The need for fast and accurate supertree methods has become crucial due to the enormous number of new genomic sequences generated by modern technology and the desire to use them for classification purposes. In particular, the Assembling the Tree of Life (ATOL) program aims at constructing the evolutionary history of all living organisms on Earth. When dealing with unrooted trees, a quartet - an unrooted tree over four taxa - is the most basic piece of phylogenetic information. Therefore, quartet amalgamation stands at the heart of any supertree problem as it concerns combining many minimal pieces of information into a single, coherent, and more comprehensive piece of information.We have devised an extremely fast algorithm for quartet amalgamation and implemented it in a very efficient code. The new code can handle over a hundred millions of quartet trees over several hundreds of taxa with very high accuracy.