Ranking top-<italic>k</italic> trees in tree-based phylogenetic networks

Momoko Hayamizu, Kazuhisa Makino

Research output: Contribution to journalArticlepeer-review

Abstract

Tree-based phylogenetic networks provide a powerful model for representing complex data or non-tree-like evolution. Such networks consist of an underlying evolutionary tree called a &#x201C;support tree&#x201D; (also known as a &#x201C;subdivision tree&#x201D;) together with extra arcs added between the edges of that tree. However, a tree-based network can have exponentially many support trees, and this leads to a variety of computational problems. Recently, Hayamizu established a theory called the structure theorem for rooted binary phylogenetic networks and provided linear-time and linear-delay algorithms for different problems, such as counting, optimization, and enumeration of support trees. However, in practice, it is often more useful to search for both optimal and near-optimal solutions than to calculate only an optimal solution. In the present paper, we thus consider the following problem: Given a tree-based phylogenetic network <italic>N</italic> where each arc is weighted by its probability, compute the ranking of top-<italic>k</italic> support trees of <italic>N</italic> according to their likelihood values. We provide a linear-delay (and hence optimal) algorithm for this problem.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • algorithm
  • enumeration
  • maximum likelihood estimation
  • Phylogenetic tree
  • spanning tree
  • subdivision tree
  • support tree
  • top-k ranking problem
  • tree-based phylogenetic network

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

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