Maximal Accurate Forests from Distance Matrices

  • Constantinos Daskalakis
  • Cameron Hill
  • Alexandar Jaffe
  • Radu Mihaescu
  • Elehanan Mossel
  • Satish Rao
Conference paper

DOI: 10.1007/11732990_24

Volume 3909 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Daskalakis C., Hill C., Jaffe A., Mihaescu R., Mossel E., Rao S. (2006) Maximal Accurate Forests from Distance Matrices. In: Apostolico A., Guerra C., Istrail S., Pevzner P.A., Waterman M. (eds) Research in Computational Molecular Biology. RECOMB 2006. Lecture Notes in Computer Science, vol 3909. Springer, Berlin, Heidelberg

Abstract

We present a fast converging method for distance-based phylogenetic inference, which is novel in two respects. First, it is the only method (to our knowledge) to guarantee accuracy when knowledge about the model tree, i.e bounds on the edge lengths, is not assumed. Second, our algorithm guarantees that, with high probability, no false assertions are made. The algorithm produces a maximal forest of the model tree, in time Õ(n3) in the typical case. Empirical testing has been promising, comparing favorably to Neighbor Joining, with the advantage of making few or no false assertions about the topology of the model tree; guarantees against false positives can be controlled as a parameter by the user.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Constantinos Daskalakis
    • 1
  • Cameron Hill
    • 1
  • Alexandar Jaffe
    • 1
  • Radu Mihaescu
    • 1
  • Elehanan Mossel
    • 1
  • Satish Rao
    • 1
  1. 1.University of CaliforniaBerkeley