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The accuracy of fast phylogenetic methods for large datasets.
Luay Nakhleh1, Bernard M E Moret, Usman Roshan
1Dept. of Computer Sciences, University of Texas, Austin, TX 78712, USA.
Summary
Accurate whole-genome phylogenetic reconstruction requires fast and robust methods. Weighbor excels with short sequences, while a new disk-covering method is best for longer sequences, with neighbor-joining and greedy parsimony being fastest for very large datasets.
Area of Science:
- Genomics
- Computational Biology
- Evolutionary Biology
Background:
- Whole-genome phylogenetic studies necessitate diverse signals for accurate evolutionary history reconstruction.
- Sequence-based methods are crucial for resolving recent evolutionary events.
- Large genomic datasets and distances demand fast, robust, and accurate reconstruction techniques.
Purpose of the Study:
- To evaluate the accuracy, convergence rate, and speed of various fast phylogenetic reconstruction methods.
- To identify optimal methods for different sequence lengths in whole-genome phylogenetics.
Main Methods:
- Comparative analysis of Neighbor-Joining, Weighbor, greedy parsimony, and a novel DCM-NJ + MP method.
- Extensive simulations using random birth-death trees with controlled deviations from ultrametricity.
Main Results:
- Weighbor demonstrates superior performance for short sequences due to advanced probability handling.
- The new DCM-NJ + MP method is most accurate for sequence lengths exceeding 100.
- For very large sequence lengths, Neighbor-Joining and greedy parsimony offer comparable accuracy and superior speed.
Conclusions:
- Method selection in whole-genome phylogenetics depends on sequence length and desired balance between accuracy and speed.
- Weighbor and DCM-NJ + MP offer distinct advantages for shorter and intermediate sequence lengths, respectively.
- Neighbor-Joining and greedy parsimony remain practical choices for very large datasets where speed is paramount.