Reconciliation

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Jens Lagergren - One of the best experts on this subject based on the ideXlab platform.

  • Bayesian gene/species tree Reconciliation and orthology analysis using MCMC.
    Bioinformatics (Oxford England), 2020
    Co-Authors: Lars Arvestad, Ann-charlotte Berglund, Jens Lagergren, Bengt Sennblad
    Abstract:

    Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and Reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious Reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available. We introduce a probabilistic gene evolution model based on a birth-death process in which a gene tree evolves 'inside' a species tree. Based on this model, we develop a tool with the capacity to perform practical orthology analysis, based on Fitch's original definition, and more generally for reconciling pairs of gene and species trees. Our gene evolution model is biologically sound (Nei et al., 1997) and intuitively attractive. We develop a Bayesian analysis based on MCMC which facilitates approximation of an a posteriori distribution for Reconciliations. That is, we can find the most probable Reconciliations and estimate the probability of any Reconciliation, given the observed gene tree. This also gives a way to estimate the probability that a pair of genes are orthologs. The main algorithmic contribution presented here consists of an algorithm for computing the likelihood of a given Reconciliation. To the best of our knowledge, this is the first successful introduction of this type of probabilistic methods, which flourish in phylogeny analysis, into Reconciliation and orthology analysis. The MCMC algorithm has been implemented and, although not yet being in its final form, tests show that it performs very well on synthetic as well as biological data. Using standard correspondences, our results carry over to allele trees as well as biogeography.

  • Genome-wide probabilistic Reconciliation analysis across vertebrates
    BMC Bioinformatics, 2013
    Co-Authors: Owais Mahmudi, Bengt Sennblad, Joel Sjöstrand, Jens Lagergren
    Abstract:

    Gene duplication is considered to be a major driving force in evolution that enables the genome of a species to acquire new functions. A Reconciliation - a mapping of gene tree vertices to the edges or vertices of a species tree - explains where gene duplications have occurred on the species tree. In this study, we sample Reconciliations from a posterior over Reconciliations, gene trees, edge lengths and other parameters, given a species tree and gene sequences. We employ a Bayesian analysis tool, based on the probabilistic model DLRS that integrates gene duplication, gene loss and sequence evolution under a relaxed molecular clock for substitution rates, to obtain this posterior. By applying these methods, we perform a genome-wide analysis of a nine species dataset, OPTIC, and conclude that for many gene families, the most parsimonious Reconciliation (MPR) - a Reconciliation that minimizes the number of duplications - is far from the correct explanation of the evolutionary history. For the given dataset, we observe that approximately 19% of the sampled Reconciliations are different from MPR. This is in clear contrast with previous estimates, based on simpler models and less realistic assumptions, according to which 98% of the Reconciliations can be expected to be identical to MPR. We also generate heatmaps showing where in the species trees duplications have been most frequent during the evolution of these species.

  • probabilistic orthology analysis
    Systematic Biology, 2009
    Co-Authors: Bengt Sennblad, Jens Lagergren
    Abstract:

    Orthology analysis aims at identifying orthologous genes and gene products from different organisms and, therefore, is a powerful tool in modern computational and experimental biology. Although Reconciliation-based orthology methods are generally considered more accurate than distance-based ones, the traditional parsimony-based implementation of Reconciliation-based orthology analysis (most parsimonious Reconciliation [MPR]) suffers from a number of shortcomings. For example, 1) it is limited to orthology predictions from the Reconciliation that minimizes the number of gene duplication and loss events, 2) it cannot evaluate the support of this Reconciliation in relation to the other Reconciliations, and 3) it cannot make use of prior knowledge (e.g., about species divergence times) that provides auxiliary information for orthology predictions. We present a probabilistic approach to Reconciliation-based orthology analysis that addresses all these issues by estimating orthology probabilities. The method is based on the gene evolution model, an explicit evolutionary model for gene duplication and gene loss inside a species tree, that generalizes the standard birth-death process. We describe the probabilistic approach to orthology analysis using 2 experimental data sets and show that the use of orthology probabilities allows a more informative analysis than MPR and, in particular, that it is less sensitive to taxon sampling problems. We generalize these anecdotal observations and show, using data generated under biologically realistic conditions, that MPR give false orthology predictions at a substantial frequency. Last, we provide a new orthology prediction method that allows an orthology and paralogy classification with any chosen sensitivity/specificity combination from the spectra of achievable combinations. We conclude that probabilistic orthology analysis is a strong and more advanced alternative to traditional orthology analysis and that it provides a framework for sophisticated comparative studies of processes in genome evolution.

  • The gene evolution model and computing its associated probabilities
    Journal of the ACM, 2009
    Co-Authors: Lars Arvestad, Jens Lagergren, Bengt Sennblad
    Abstract:

    Phylogeny is both a fundamental tool in biology and a rich source of fascinating modeling and algorithmic problems. Today's wealth of sequenced genomes makes it increasingly important to understand evolutionary events such as duplications, losses, transpositions, inversions, lateral transfers, and domain shuffling. We focus on the gene duplication event, that constitutes a major force in the creation of genes with new function [Ohno 1970; Lynch and Force 2000] and, thereby also, of biodiversity. We introduce the probabilistic gene evolution model, which describes how a gene tree evolves within a given species tree with respect to speciation, gene duplication, and gene loss. The actual relation between gene tree and species tree is captured by a Reconciliation, a concept which we generalize for more expressiveness. The model is a canonical generalization of the classical linear birth-death process, obtained by replacing the interval where the process takes place by a tree. For the gene evolution model, we derive efficient algorithms for some associated probability distributions: the probability of a reconciled tree, the probability of a gene tree, the maximum probability Reconciliation, the posterior probability of a Reconciliation, and sampling Reconciliations with respect to the posterior probability. These algorithms provides the basis for several applications, including species tree construction, Reconciliation analysis, orthology analysis, biogeography, and host-parasite co-evolution.

A. Prakash - One of the best experts on this subject based on the ideXlab platform.

  • methods and limitations of security policy Reconciliation
    ACM Transactions on Information and System Security, 2006
    Co-Authors: Patrick Mcdaniel, A. Prakash
    Abstract:

    A security policy specifies session participant requirements. However, existing frameworks provide limited facilities for the automated Reconciliation of participant policies. This paper considers the limits and methods of Reconciliation in a general-purpose policy model. We identify an algorithm for efficient two-policy Reconciliation and show that, in the worst-case, Reconciliation of three or more policies is intractable. Further, we suggest efficient heuristics for the detection and resolution of intractable Reconciliation. Based upon the policy model, we describe the design and implementation of the Ismene policy language. The expressiveness of Ismene, and indirectly of our model, is demonstrated through the representation and exposition of policies supported by existing policy languages. We conclude with brief notes on the integration and enforcement of Ismene policy within the Antigone communication system.

  • Methods and limitations of security policy Reconciliation
    Proceedings 2002 IEEE Symposium on Security and Privacy, 2002
    Co-Authors: P. Mdaniel, A. Prakash
    Abstract:

    A security policy is a means by which participant session requirements are specified. However, existing frameworks provide limited facilities for the automated Reconciliation of participant policies. This paper considers the limits and methods of Reconciliation in a general-purpose policy model. We identify an algorithm for efficient two-policy Reconciliation, and show that, in the worst-case, Reconciliation of three or more policies is intractable. Further, we suggest efficient heuristics for the detection and resolution of intractable Reconciliation. Based upon the policy model, we describe the design and implementation of the Ismene policy language. The expressiveness of Ismene, and indirectly of our model, is demonstrated through the representation and exposition of policies supported by existing policy languages. We conclude with brief notes on the integration and enforcement of Ismene policy within the Antigone communication system.

Bengt Sennblad - One of the best experts on this subject based on the ideXlab platform.

  • Bayesian gene/species tree Reconciliation and orthology analysis using MCMC.
    Bioinformatics (Oxford England), 2020
    Co-Authors: Lars Arvestad, Ann-charlotte Berglund, Jens Lagergren, Bengt Sennblad
    Abstract:

    Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and Reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious Reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available. We introduce a probabilistic gene evolution model based on a birth-death process in which a gene tree evolves 'inside' a species tree. Based on this model, we develop a tool with the capacity to perform practical orthology analysis, based on Fitch's original definition, and more generally for reconciling pairs of gene and species trees. Our gene evolution model is biologically sound (Nei et al., 1997) and intuitively attractive. We develop a Bayesian analysis based on MCMC which facilitates approximation of an a posteriori distribution for Reconciliations. That is, we can find the most probable Reconciliations and estimate the probability of any Reconciliation, given the observed gene tree. This also gives a way to estimate the probability that a pair of genes are orthologs. The main algorithmic contribution presented here consists of an algorithm for computing the likelihood of a given Reconciliation. To the best of our knowledge, this is the first successful introduction of this type of probabilistic methods, which flourish in phylogeny analysis, into Reconciliation and orthology analysis. The MCMC algorithm has been implemented and, although not yet being in its final form, tests show that it performs very well on synthetic as well as biological data. Using standard correspondences, our results carry over to allele trees as well as biogeography.

  • Genome-wide probabilistic Reconciliation analysis across vertebrates
    BMC Bioinformatics, 2013
    Co-Authors: Owais Mahmudi, Bengt Sennblad, Joel Sjöstrand, Jens Lagergren
    Abstract:

    Gene duplication is considered to be a major driving force in evolution that enables the genome of a species to acquire new functions. A Reconciliation - a mapping of gene tree vertices to the edges or vertices of a species tree - explains where gene duplications have occurred on the species tree. In this study, we sample Reconciliations from a posterior over Reconciliations, gene trees, edge lengths and other parameters, given a species tree and gene sequences. We employ a Bayesian analysis tool, based on the probabilistic model DLRS that integrates gene duplication, gene loss and sequence evolution under a relaxed molecular clock for substitution rates, to obtain this posterior. By applying these methods, we perform a genome-wide analysis of a nine species dataset, OPTIC, and conclude that for many gene families, the most parsimonious Reconciliation (MPR) - a Reconciliation that minimizes the number of duplications - is far from the correct explanation of the evolutionary history. For the given dataset, we observe that approximately 19% of the sampled Reconciliations are different from MPR. This is in clear contrast with previous estimates, based on simpler models and less realistic assumptions, according to which 98% of the Reconciliations can be expected to be identical to MPR. We also generate heatmaps showing where in the species trees duplications have been most frequent during the evolution of these species.

  • probabilistic orthology analysis
    Systematic Biology, 2009
    Co-Authors: Bengt Sennblad, Jens Lagergren
    Abstract:

    Orthology analysis aims at identifying orthologous genes and gene products from different organisms and, therefore, is a powerful tool in modern computational and experimental biology. Although Reconciliation-based orthology methods are generally considered more accurate than distance-based ones, the traditional parsimony-based implementation of Reconciliation-based orthology analysis (most parsimonious Reconciliation [MPR]) suffers from a number of shortcomings. For example, 1) it is limited to orthology predictions from the Reconciliation that minimizes the number of gene duplication and loss events, 2) it cannot evaluate the support of this Reconciliation in relation to the other Reconciliations, and 3) it cannot make use of prior knowledge (e.g., about species divergence times) that provides auxiliary information for orthology predictions. We present a probabilistic approach to Reconciliation-based orthology analysis that addresses all these issues by estimating orthology probabilities. The method is based on the gene evolution model, an explicit evolutionary model for gene duplication and gene loss inside a species tree, that generalizes the standard birth-death process. We describe the probabilistic approach to orthology analysis using 2 experimental data sets and show that the use of orthology probabilities allows a more informative analysis than MPR and, in particular, that it is less sensitive to taxon sampling problems. We generalize these anecdotal observations and show, using data generated under biologically realistic conditions, that MPR give false orthology predictions at a substantial frequency. Last, we provide a new orthology prediction method that allows an orthology and paralogy classification with any chosen sensitivity/specificity combination from the spectra of achievable combinations. We conclude that probabilistic orthology analysis is a strong and more advanced alternative to traditional orthology analysis and that it provides a framework for sophisticated comparative studies of processes in genome evolution.

  • The gene evolution model and computing its associated probabilities
    Journal of the ACM, 2009
    Co-Authors: Lars Arvestad, Jens Lagergren, Bengt Sennblad
    Abstract:

    Phylogeny is both a fundamental tool in biology and a rich source of fascinating modeling and algorithmic problems. Today's wealth of sequenced genomes makes it increasingly important to understand evolutionary events such as duplications, losses, transpositions, inversions, lateral transfers, and domain shuffling. We focus on the gene duplication event, that constitutes a major force in the creation of genes with new function [Ohno 1970; Lynch and Force 2000] and, thereby also, of biodiversity. We introduce the probabilistic gene evolution model, which describes how a gene tree evolves within a given species tree with respect to speciation, gene duplication, and gene loss. The actual relation between gene tree and species tree is captured by a Reconciliation, a concept which we generalize for more expressiveness. The model is a canonical generalization of the classical linear birth-death process, obtained by replacing the interval where the process takes place by a tree. For the gene evolution model, we derive efficient algorithms for some associated probability distributions: the probability of a reconciled tree, the probability of a gene tree, the maximum probability Reconciliation, the posterior probability of a Reconciliation, and sampling Reconciliations with respect to the posterior probability. These algorithms provides the basis for several applications, including species tree construction, Reconciliation analysis, orthology analysis, biogeography, and host-parasite co-evolution.

Patrick Drew Mcdaniel - One of the best experts on this subject based on the ideXlab platform.

  • Security policy Reconciliation in distributed computing environments
    Proceedings. Fifth IEEE International Workshop on Policies for Distributed Systems and Networks 2004. POLICY 2004., 2004
    Co-Authors: Hao Wang, Miron Livny, S. Jhat, Patrick Drew Mcdaniel
    Abstract:

    A major hurdle in sharing resources between organizations is heterogeneity. Therefore, in order for two organizations to collaborate their policies have to be resolved. The process of resolving different policies is known as policy Reconciliation, which in general is an intractable problem. This paper addresses policy Reconciliation in the context of security. We present a formal framework and hierarchical representation for security policies. Our hierarchical representation exposes the structure of the policies and leads to an efficient Reconciliation algorithm. We also demonstrate that agent preferences for security mechanisms can be readily incorporated into our framework. We have implemented our Reconciliation algorithm in a library called the policy Reconciliation engine or PRE. In order to test the implementation and measure the overhead of our Reconciliation algorithm, we have integrated PRE into a distributed high-throughput system called Condor.

  • Security Policy Reconciliation in Distributed Computing Environments.
    POLICY, 2004
    Co-Authors: Hao Wang, Miron Livny, Somesh Jha, Patrick Drew Mcdaniel
    Abstract:

    A major hurdle in sharing resources between organizations is heterogeneity. Therefore, in order for two organizations to collaborate their policies have to be resolved. The process of resolving different policies is known as policy Reconciliation, which in general is an intractable problem. This paper addresses policy Reconciliation in the context of security. We present a formal framework and hierarchical representation for security policies. Our hierarchical representation exposes the structure of the policies and leads to an efficient Reconciliation algorithm. We also demonstrate that agent preferences for security mechanisms can be readily incorporated into our framework. We have implemented our Reconciliation algorithm in a library called the Policy Reconciliation Engine or PRE. In order to test the implementation and measure the overhead of our Reconciliation algorithm, we have integrated PRE into a distributed high-throughput system called Condor.

Manolis Kellis - One of the best experts on this subject based on the ideXlab platform.

  • pareto optimal phylogenetic tree Reconciliation
    Bioinformatics, 2014
    Co-Authors: Ran Libeskindhadas, Yichieh Wu, Mukul S Bansal, Manolis Kellis
    Abstract:

    MOTIVATION: Phylogenetic tree Reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a Reconciliation of minimum total cost. It is generally understood that Reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem. RESULTS: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of Reconciliations, thus providing the first systematic method for understanding the relationship between event costs and Reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies. AVAILABILITY AND IMPLEMENTATION: Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape. .

  • Reconciliation revisited handling multiple optima when reconciling with duplication transfer and loss
    Journal of Computational Biology, 2013
    Co-Authors: Mukul S Bansal, Manolis Kellis
    Abstract:

    : Phylogenetic tree Reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While duplication-loss (DL) Reconciliation leads to a unique maximum-parsimony solution, duplication-transfer-loss (DTL) Reconciliation yields a multitude of optimal solutions, making it difficult to infer the true evolutionary history of the gene family. This problem is further exacerbated by the fact that different event cost assignments yield different sets of optimal Reconciliations. Here, we present an effective, efficient, and scalable method for dealing with these fundamental problems in DTL Reconciliation. Our approach works by sampling the space of optimal Reconciliations uniformly at random and aggregating the results. We show that even gene trees with only a few dozen genes often have millions of optimal Reconciliations and present an algorithm to efficiently sample the space of optimal Reconciliations uniformly at random in O(mn(2)) time per sample, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal Reconciliations vary in their node mappings and event assignments and to investigate the impact of varying event costs. We apply our method to a biological dataset of approximately 4700 gene trees from 100 taxa and observe that 93% of event assignments and 73% of mappings remain consistent across different multiple optima. Our analysis represents the first systematic investigation of the space of optimal DTL Reconciliations and has many important implications for the study of gene family evolution.

  • Reconciliation revisited handling multiple optima when reconciling with duplication transfer and loss
    Research in Computational Molecular Biology, 2013
    Co-Authors: Mukul S Bansal, Manolis Kellis
    Abstract:

    Phylogenetic tree Reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While Duplication-Loss (DL) Reconciliation leads to a unique maximum-parsimony solution, Duplication-Transfer-Loss (DTL) Reconciliation yields a multitude of optimal solutions, making it difficult the infer the true evolutionary history of the gene family. Here, we present an effective, efficient, and scalable method for dealing with this fundamental problem in DTL Reconciliation. Our approach works by sampling the space of optimal Reconciliations uniformly at random and aggregating the results. We present an algorithm to efficiently sample the space of optimal Reconciliations uniformly at random in O(mn2) time, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal Reconciliations vary in their node mapping and event assignments, and to investigate the impact of varying event costs.

  • efficient algorithms for the Reconciliation problem with gene duplication horizontal transfer and loss
    Bioinformatics, 2012
    Co-Authors: Mukul S Bansal, Manolis Kellis
    Abstract:

    Motivation: Gene family evolution is driven by evolutionary events such as speciation, gene duplication, horizontal gene transfer and gene loss, and inferring these events in the evolutionary history of a given gene family is a fundamental problem in comparative and evolutionary genomics with numerous important applications. Solving this problem requires the use of a Reconciliation framework, where the input consists of a gene family phylogeny and the corresponding species phylogeny, and the goal is to reconcile the two by postulating speciation, gene duplication, horizontal gene transfer and gene loss events. This Reconciliation problem is referred to as duplication-transfer-loss (DTL) Reconciliation and has been extensively studied in the literature. Yet, even the fastest existing algorithms for DTL Reconciliation are too slow for reconciling large gene families and for use in more sophisticated applications such as gene tree or species tree reconstruction. Results: We present two new algorithms for the DTL Reconciliation problem that are dramatically faster than existing algorithms, both asymptotically and in practice. We also extend the standard DTL Reconciliation model by considering distance-dependent transfer costs, which allow for more accurate Reconciliation and give an efficient algorithm for DTL Reconciliation under this extended model. We implemented our new algorithms and demonstrated up to 100 000-fold speed-up over existing methods, using both simulated and biological datasets. This dramatic improvement makes it possible to use DTL Reconciliation for performing rigorous evolutionary analyses of large gene families and enables its use in advanced Reconciliation-based gene and species tree reconstruction methods. Availability: Our programs can be freely downloaded from http://compbio.mit.edu/ranger-dtl/. Contact:[email protected]; [email protected] Supplementary information:Supplementary data are available at Bioinformatics online.