PhySIC_IST: A New Method for Inferring Informative Supertrees
Author Information
Author(s): Celine Scornavacca, Vincent Berry, Vincent Lefort, Emmanuel JP Douzery, Vincent Ranwez
Primary Institution: Institut des Sciences de l'Evolution (ISEM, UMR 5554 CNRS), Université Montpellier II
Hypothesis
Can non-plenary supertrees be inferred from source trees with topological conflicts using a new method called PhySIC_IST?
Conclusion
The study introduces PhySIC_IST and STC, which effectively infer non-plenary supertrees and preprocess source trees to improve phylogenetic resolution.
Supporting Evidence
- PhySIC_IST infers more informative supertrees than the original PhySIC method.
- STC preprocessing improves the resolution of supertrees without significantly increasing type I error.
- Case studies on placental mammals and a larger animal dataset validate the effectiveness of the proposed methods.
Takeaway
This study presents a new way to combine different trees into one big tree that makes more sense, especially when the smaller trees don't agree with each other.
Methodology
The study uses simulations and biological case studies to evaluate the effectiveness of the PhySIC_IST method and the STC preprocessing step.
Limitations
The method may struggle with source trees that have very low overlap or high contradictions.
Digital Object Identifier (DOI)
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