Orientability of Undirected Phylogenetic Networks to a Desired Class: Practical Algorithms and Application to Tree-Child Orientation

Authors Tsuyoshi Urata , Manato Yokoyama , Momoko Hayamizu



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Author Details

Tsuyoshi Urata
  • Department of Pure and Applied Mathematics, Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan
Manato Yokoyama
  • Department of Pure and Applied Mathematics, Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan
Momoko Hayamizu
  • Department of Applied Mathematics, Faculty of Science and Engineering, Waseda University, Tokyo, Japan

Acknowledgements

We thank Yufeng Wu and Louxin Zhang for sharing code for randomly generating graphs, which we adapted for our experiments. We also appreciate Haruki Miyaji’s helpful discussions and the anonymous reviewers' careful reading of our manuscript and useful comments.

Cite AsGet BibTex

Tsuyoshi Urata, Manato Yokoyama, and Momoko Hayamizu. Orientability of Undirected Phylogenetic Networks to a Desired Class: Practical Algorithms and Application to Tree-Child Orientation. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 9:1-9:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.WABI.2024.9

Abstract

The 𝒞-Orientation problem asks whether it is possible to orient an undirected graph to a directed phylogenetic network of a desired class 𝒞, and to find such an orientation if one exists. The problem can arise when visualising evolutionary data, for example, because popular phylogenetic network reconstruction methods such as Neighbor-Net are distance-based and thus inevitably produce undirected graphs. The complexity of 𝒞-Orientation remains open for many classes 𝒞, including binary tree-child networks, and practical methods are still lacking. In this paper, we propose an exponential but practically efficient FPT algorithm for 𝒞-Orientation, which is parameterised by the reticulation number and the maximum size of minimal basic cycles used in the computation. We also present a very fast heuristic for Tree-Child Orientation. To evaluate the empirical performance of the proposed methods, we compared their accuracy and execution time for Tree-Child Orientation with those of an exponential time 𝒞-orientation algorithm from the literature. Our experiments show that the proposed exact algorithm is significantly faster than the state-of-the-art exponential time algorithm. The proposed heuristic runs even faster but the accuracy decreases as the reticulation number increases.

Subject Classification

ACM Subject Classification
  • Applied computing → Biological networks
Keywords
  • Phylogenetic Networks
  • Tree-Child Networks
  • Graph Orientation Algorithms

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References

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