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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
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Distributions of 4-subtree patterns for uniform random unrooted phylogenetic trees
Kwok Pui Choi1, Gursharn Kaur2, Ariadne Thompson3
1Department of Statistics and Data Sciences, National University of Singapore, Singapore 117546, Singapore.
Journal of Theoretical Biology
|March 18, 2024
Summary
We present statistical models for tree shapes to understand evolutionary processes. Our findings confirm previous conjectures and offer new methods for detecting evolutionary forces like whole genome duplication.
Area of Science:
- Phylogenetics and Evolutionary Biology
- Computational Biology
- Statistical Genetics
Background:
- Tree shape statistics are crucial for understanding evolutionary mechanisms and developing inference methods.
- Previous work has explored modeling subgenome accumulation in polyploid evolution.
Purpose of the Study:
- To derive the distribution of subtree patterns for the unrooted Proportional to Distinguishable Arrangements (PDA) model.
- To confirm conjectures and provide theoretical insights related to polyploid evolution studies.
Main Methods:
- Derivation of a recursive formula for joint distributions of subtree patterns.
- Application of the Strong Law of Large Numbers and Central Limit Theorem to these distributions.
- Statistical testing using joint distributions on empirical datasets.
Main Results:
- The distribution of subtree patterns with four or fewer leaves for the PDA model was determined.
- Conjectures from Pouryahya and Sankoff were confirmed.
- A statistical test based on joint distributions demonstrated increased sensitivity in detecting evolutionary forces.
Conclusions:
- The derived statistical framework provides theoretical insights into polyploid evolution.
- Joint distribution-based statistical tests are more sensitive for detecting evolutionary forces like whole genome duplication compared to single subtree pattern tests.
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