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Accuracy in Near-Perfect Virus Phylogenies
Joel O Wertheim1, Mike Steel2, Michael J Sanderson3
1Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA.
Systematic Biology
|August 16, 2021
Summary
Phylogenetic tree accuracy can be high even with short edges. In near-perfect conditions, the false positive rate for discovering clades is low, especially for viruses like SARS-CoV-2.
Area of Science:
- Phylogenetics
- Computational Biology
- Evolutionary Biology
Background:
- Real-world phylogenetic trees often have short edges, leading to incomplete resolution and reduced accuracy.
- Theoretical models suggest that accurately reconstructing trees requires a number of sites inversely proportional to the square of the shortest edge length.
Purpose of the Study:
- To redefine and assess "accuracy" in phylogenetic inference when short edges are present.
- To analyze the false positive rate of clade discovery in "near-perfect" phylogenetic parameter spaces.
- To compare bootstrap support measures with actual false positive rates.
Main Methods:
- Analytical derivation for maximum parsimony.
- Theoretical analysis and simulations for maximum likelihood.
- Comparison of bootstrap resampling support with false positive rates.
Main Results:
- Accuracy can remain high even with short edges if defined by false split discovery rate.
- In near-perfect parameter spaces, the expected false positive rate is low (less than ξ/3), often below 5%.
- Bootstrap support measures tend to underestimate clade reliability compared to actual false positive rates in near-perfect trees.
Conclusions:
- The "near-perfect" model accurately reflects empirical data from human virus outbreaks (e.g., Ebolavirus, Zika virus, SARS-CoV-2).
- Phylogenetic inference can be reliable in scenarios with low substitution rates relative to high transmission/sampling rates.
- This work provides a more nuanced understanding of phylogenetic accuracy and support measures.
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