The binary perfect phylogeny with persistent characters

  title={The binary perfect phylogeny with persistent characters},
  author={Paola Bonizzoni and Chiara Braghin and Riccardo Dondi and Gabriella Trucco},
  journal={Theor. Comput. Sci.},

Tables from this paper

Algorithms for the Constrained Perfect Phylogeny with Persistent Characters

This paper develops a parameterized algorithm for solving the Persistent Perfect Phylogeny problem where the parameter is the number of characters and provides a polynomial time solution for the CP-PP problem for matrices having an empty conflict-graph.

Incomplete Directed Perfect Phylogeny in Linear Time

Insight into the specific structure of the IDPP problem leads to an asymptotically faster algorithm, that runs in optimal $O(nm)$ time, and is successful in giving a much simpler $\tilde{O}( nm)$-time algorithm.

Beyond Perfect Phylogeny: Multisample Phylogeny Reconstruction via ILP

An experimental analysis shows that the ILP approach is able to explain data that do not fit the perfect phylogeny assumption, thereby allowing multiple losses and gains of mutations, and a number of subpopulations that is smaller than the number of input mutations.

PE ] 1 1 O ct 2 01 8 Combinatorial views on persistent characters in phylogenetics

The question of how many binary characters together with their persistence status are needed to uniquely determine a phylogenetic tree is considered and an upper bound for the number of characters needed is provided.

Persistent phylogeny: a galled-tree and integer linear programming approach

An integer programming solution to the Persistent-Phylogeny Problem is developed; empirically explore its efficiency; and the utility of using fast algorithms that recognize galled trees, to recognize persistent phylogeny is explored.

Combinatorial perspectives on Dollo-k characters in phylogenetics

Does relaxing the infinite sites assumption give better tumor phylogenies? An ILP-based comparative approach

This work proposes a new approach that incorporates the possibility of losing a previously acquired mutation, extending the Persistent Phylogeny model, and exploits the model to provide an ILP formulation of the problem of reconstructing trees on mixed populations, where the input data consists of the fraction of cells in a set of samples that have a certain mutation.

A Generalized Robinson-Foulds Distance for Clonal Trees, Mutation Trees, and Phylogenetic Trees and Networks

A distance metric for multi-labeled trees is presented that generalizes the Robinson-Foulds distance for phylogenetic trees, allows for a similarity assessment at much higher resolution, and can be applied to trees and networks with different sets of node labels.



Incomplete Directed Perfect Phylogeny

This work provides a near optimal O(nm)-time algorithm for the problem of perfect phylogeny, which arises in classical phylogenetic studies, when some states are missing or undetermined.

Reducing Multi-state to Binary Perfect Phylogeny with Applications to Missing, Removable, Inserted, and Deleted Data

A new general conceptual solution to the multistate Perfect Phylogeny problem is introduced, and conceptual solutions to the MD, CR, MDCR and ID problems for any k significantly improving previous work are introduced.

Algorithms for Efficient Near-Perfect Phylogenetic Tree Reconstruction in Theory and Practice

This work proves that the BNPP problem is fixed-parameter tractable and provides the first practical phylogenetic tree reconstruction algorithms that find guaranteed optimal solutions while being easily implemented and computationally feasible for data sets of biologically meaningful size and complexity.

The Perfect Phylogeny Problem

This work is concerned here with taxa described by the states they exhibit on a set of characters, and assumes that the taxa descend from a common ancestor where all characters are absent.

Constructing Near-Perfect Phylogenies with multiple homoplasy events

A near-optimal algorithm is presented for the H1-NPPH problem, which is to determine if a given set of genotypes admit a phylogeny with a single homoplasy event, and the accuracy of this algorithm is comparable to that of the existing methods, while being orders of magnitude faster.

An Optimal Algorithm for Perfect Phylogeny Haplotyping

The OPPH algorithm is one of the first O(nm) algorithms presented for the PPH problem and the FlexTree (flexible tree) data structure provides a compact representation of all the perfect phylogenies for the given set of genotypes.

A Linear-Time Algorithm for the Perfect Phylogeny Haplotype Problem

The Perfect Phylogeny Haplotype problem is solved and an O(nm)-time algorithm to complete matrices of n rows and m columns to represent PPH solutions is given: it is shown that solving the problem requires recognizing special posets of width 2.

Extensions and Improvements to the Chordal Graph Approach to the Multistate Perfect Phylogeny Problem

  • Rob GyselD. Gusfield
  • Mathematics
    IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • 2011
This work shows how to use chordal graphs and triangulations to solve the character removal problem for an arbitrary number of states, which was previously unsolved, and outlines a preprocessing technique that speeds up the computation of the minimal separators of a graph.

Haplotyping as perfect phylogeny: conceptual framework and efficient solutions

This paper explores the algorithmic implications of the key "no-recombination in long blocks" observation, for the problem of inferring haplotypes in populations, and observes that the no-re Combination assumption is very powerful.

Efficient reconstruction of haplotype structure via perfect phylogeny.

A simple and efficient polynomial-time algorithm for inferring haplotypes from the genotypes of a set of individuals assuming a perfect phylogeny is presented and a hardness result for the problem of removing the minimum number of individuals from a population is presented to ensure that the genotype of the remaining individuals are consistent with aperfect phylogeny.