skip to main content
research-article

Linear time 3-approximation for the MAST problem

Published:23 March 2009Publication History
Skip Abstract Section

Abstract

Given a set of leaf-labeled trees with identical leaf sets, the well-known Maximum Agreement SubTree (MAST) problem consists in finding a subtree homeomorphically included in all input trees and with the largest number of leaves. MAST and its variant called Maximum Compatible Tree (MCT) are of particular interest in computational biology. This article presents a linear-time approximation algorithm to solve the complement version of MAST, namely identifying the smallest set of leaves to remove from input trees to obtain isomorphic trees. We also present an O(n2 + kn) algorithm to solve the complement version of MCT. For both problems, we thus achieve significantly lower running times than previously known algorithms. Fast running times are especially important in phylogenetics where large collections of trees are routinely produced by resampling procedures, such as the nonparametric bootstrap or Bayesian MCMC methods.

References

  1. Amir, A., and Keselman, D. 1997. Maximum agreement subtree in a set of evolutionary trees: Metrics and efficient algorithm. SIAM J. Comput. 26, 6, 1656--1669. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Berger-Wolf, T. 2004. Consensus and agreement of phylogenetic trees. In Proceedings of the 4th Workshop on Algorithms in Bioinformatics (WABI). Lecture Notes in Computer Science. Springer, 350--361.Google ScholarGoogle Scholar
  3. Berry, V., and Nicolas, F. 2004. Maximum agreement and compatible supertrees. In Proceedings of the 15th Annual Symposium on Combinatorial Pattern Matching (CPM'04), S. C. Sahinalp et al., Eds. Lecture Notes in Computer Science, vol. 3109. Springer, 205--219.Google ScholarGoogle Scholar
  4. Berry, V., and Nicolas, F. to appear. Improved parametrized complexity and approximation of the maximum agreement subtree and maximum compatible tree problems. IEEE/ACM Trans. Comput. Biol. Bioinf. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Bryant, D. 1997. Building trees, hunting for trees and comparing trees: Theory and method in phylogenetic analysis. Ph.D. thesis, University of Canterbury, Department of Mathemathics.Google ScholarGoogle Scholar
  6. Bryant, D., Steel, M., and MacKenzie, A. 1983. The size of a maximum agreement subtree for random binary trees. In BioConsensus, M. Janowitz et al., Eds. DIMACS AMS, 55--66.Google ScholarGoogle Scholar
  7. Cole, R., Farach-Colton, M., Hariharan, R., Przytycka, T. M., and Thorup, M. 2001. An O(n log n) algorithm for the maximum agreement subtree problem for binary trees. SIAM J. Comput. 30, 5, 1385--1404. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Downey, R. G., Fellows, M. R., and Stege, U. 1999. Computational tractability: The view from Mars. Bull. Eur. Assoc. Theor. Comput. Sci. 69, 73--97.Google ScholarGoogle Scholar
  9. Farach, M., Przytycka, T. M., and Thorup, M. 1995. On the agreement of many trees. Inf. Process. Lett. 55, 6, 297--301. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Ganapathy, G., and Warnow, T. J. 2002. Approximating the complement of the maximum compatible subset of leaves of k trees. In Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization (APPROX'02). Lecture Notes in Computer Science, vol. 2462. Springer, 122--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Ganapathysaravanabavan, G., and Warnow, T. J. 2001. Finding a maximum compatible tree for a bounded number of trees with bounded degree is solvable in polynomial time. In Proceedings of the 1st International Workshop on Algorithms in Bioinformatics (WABI'01), O. Gascuel and B. M. E. Moret, Eds. Lecture Notes in Computer Science, vol. 2149. Springer, 156--163. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Guindon, S., and Gascuel, O. 2003. A simple, fast and accurate method to estimate large phylogenies by maximum-likelihood. Syst. Biol. 52, 5, 696--704.Google ScholarGoogle ScholarCross RefCross Ref
  13. Gupta, A., and Nishimura, N. 1998. Finding largest subtrees and smallest supertrees. Algorithmica 21, 2, 183--210.Google ScholarGoogle ScholarCross RefCross Ref
  14. Hamel, A. M., and Steel, M. A. 1996. Finding a maximum compatible tree is NP-hard for sequences and trees. Appl. Math. Lett. 9, 2, 55--59.Google ScholarGoogle ScholarCross RefCross Ref
  15. Harel, D., and Tarjan, R. E. 1984. Fast algorithms for finding nearest common ancestor. SIAM J. Comput. 13, 2, 338--355. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Hein, J., Jiang, T., Wang, L., and Zhang, K. 1996. On the complexity of comparing evolutionary trees. Discrete Appl. Math. 71, 1--3, 153--169. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Kao, M.-Y., Lam, T. W., Sung, W.-K., and Ting, H.-F. 1999. A decomposition theorem for maximum weight bipartite matchings with applications to evolutionary trees. In Proceedings of the 7th Annual European Symposium on Algorithms (ESA'99). Lecture Notes in Computer Science, vol. 1643. Springer, 438--449. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Kao, M.-Y., Lam, T. W., Sung, W.-K., and Ting, H.-F. 2001. An even faster and more unifying algorithm for comparing trees via unbalanced bipartite matchings. J. Algor. 40, 2, 212--233. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. McMorris, F., Meronik, D., and Neumann, D. 1983. A view of some consensus methods for trees. In Numerical Taxonomy, J. Felsenstein, Ed. Springer, 122--125.Google ScholarGoogle Scholar
  20. Nishimura, N., Ragde, P., and Thilikos, D. 2004. Smaller kernels for hitting set problems of constant arity. In International Workshop on Parameterized and Exact Computation (IWPEC). Lecture Notes in Computer Science, vol. 3162. 121--126.Google ScholarGoogle ScholarCross RefCross Ref
  21. Semple, C., and Steel, M. 2003. Phylogenetics. Oxford Lecture Series in Mathematics and its Applications, vol. 24. Oxford University Press.Google ScholarGoogle Scholar
  22. Steel, M. A., and Warnow, T. J. 1993. Kaikoura tree theorems: Computing the maximum agreement subtree. Inf. Process. Lett. 48, 2, 77--82. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Linear time 3-approximation for the MAST problem

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in

            Full Access

            • Published in

              cover image ACM Transactions on Algorithms
              ACM Transactions on Algorithms  Volume 5, Issue 2
              March 2009
              235 pages
              ISSN:1549-6325
              EISSN:1549-6333
              DOI:10.1145/1497290
              Issue’s Table of Contents

              Copyright © 2009 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 23 March 2009
              • Revised: 1 October 2008
              • Accepted: 1 October 2008
              • Received: 1 April 2006
              Published in talg Volume 5, Issue 2

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • research-article
              • Research
              • Refereed

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader