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Consider the Aldous Markov chain on the space of rooted binary trees withnlabeled leaves in which at each transition a uniform random leaf is deleted and reattached to a uniform random edge. Now, fix 1 ≤ k<nand project the leaf mass onto the subtree spanned by the firstkleaves. This yields a binary tree with edge weights that we call a “decoratedk‐tree with total massn.” We introduce label swapping dynamics for the Aldous chain so that, when it runs in stationarity, the decoratedk‐trees evolve as Markov chains themselves, and are projectively consistent overk. The construction of projectively consistent chains is a crucial step in the construction of the Aldous diffusion on continuum trees by the present authors, which is then→∞continuum analog of the Aldous chain and will be taken up elsewhere.
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This content will become publicly available on December 1, 2025
Median quartet tree search algorithms using optimal subtree prune and regraft
Abstract Gene trees can be different from the species tree due to biological processes and inference errors. One way to obtain a species tree is to find one that maximizes some measure of similarity to a set of gene trees. The number of shared quartets between a potential species tree and gene trees provides a statistically justifiable score; if maximized properly, it could result in a statistically consistent estimator of the species tree under several statistical models of discordance. However, finding the median quartet score tree, one that maximizes this score, is NP-Hard, motivating several existing heuristic algorithms. These heuristics do not follow the hill-climbing paradigm used extensively in phylogenetics. In this paper, we make theoretical contributions that enable an efficient hill-climbing approach. Specifically, we show that a subtree of sizemcan be placed optimally on a tree of sizenin quasi-linear time with respect tonand (almost) independently ofm. This result enables us to perform subtree prune and regraft (SPR) rearrangements as part of a hill-climbing search. We show that this approach can slightly improve upon the results of widely-used methods such as ASTRAL in terms of the optimization score but not necessarily accuracy.
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- Award ID(s):
- 1845967
- PAR ID:
- 10510814
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- Algorithms for Molecular Biology
- Volume:
- 19
- Issue:
- 1
- ISSN:
- 1748-7188
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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