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Bootstrap-based support of HGT inferred by maximum parsimony
Hyun Jung Park1, Guohua Jin, Luay Nakhleh
1Department of Computer Science, Rice University, 6100 Main Street, MS 132, Houston, Texas 77005, USA.
BMC Evolutionary Biology
|May 7, 2010
Summary
This study introduces a novel bootstrap-based method to accurately quantify support for reticulation events in phylogenetic networks. This approach systematically determines the number and placement of reticulation events, improving phylogenetic network reconstruction.
Area of Science:
- Computational Biology
- Evolutionary Biology
- Bioinformatics
Background:
- Maximum parsimony is a common method for phylogenetic tree reconstruction.
- Extensions allow for phylogenetic network reconstruction and detection of reticulate evolution.
- A key challenge is the tendency to overestimate reticulation due to favoring complexity.
Purpose of the Study:
- To address the overestimation of reticulation in phylogenetic networks.
- To develop a systematic method for inferring reticulation events.
- To quantify the support for inferred reticulation events.
Main Methods:
- Proposed a nonparametric bootstrap-based measure for reticulation event support.
- Generated multiple samples from sequence alignments.
- Inferred reticulation events on each sample and quantified support across all samples.
Main Results:
- Developed a method to systematically determine the number and placement of reticulation events.
- Quantified the support for each inferred reticulation event.
- Implemented the method in the publicly available NEPAL software tool.
Conclusions:
- The NEPAL tool shows promising results on biological and simulated data.
- The bootstrap-based measure provides a systematic approach to inferring reticulation.
- Challenges remain in applying maximum parsimony to detect reticulate evolution.
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