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Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

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Looking for trees in the forest: summary tree from posterior samples.

Joseph Heled¹, Remco R Bouckaert

¹Department of Computer Science, University of Auckland, Auckland New Zealand. jheled@gmail.com.

BMC Evolutionary Biology

|October 8, 2013

Summary

This summary is machine-generated.

Choosing the best summary tree method depends on your goals. Our research compares methods for rooted time trees, finding no single best approach for all phylogenetic analysis needs.

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Area of Science:

Computational Biology
Phylogenetics
Evolutionary Biology

Background:

Bayesian phylogenetic analysis yields multiple trees, necessitating representative summary trees.
Existing methods for unrooted trees are more developed than those for rooted time trees from BEAST analyses.
Limited research exists on simultaneously optimizing topology and branch lengths for summary trees.

Purpose of the Study:

To evaluate and compare existing and novel methods for generating summary trees from Bayesian phylogenetic analyses.
To assess the performance of summary tree methods for rooted time trees, specifically those from BEAST.
To provide guidance on selecting appropriate summary tree methods based on user objectives.

Main Methods:

Empirical comparison of new and established summary tree generation techniques.
Development of methods based on tree metrics and practical tree concepts.
Extensive simulations to assess summary tree quality using model fit and accuracy to true trees.

Main Results:

No single summary tree method excels in all aspects; trade-offs exist between divergence time accuracy and branch length precision.
New methods utilize more posterior information compared to existing approaches that discard data.
Performance was evaluated based on explanatory power for sequence data and proximity to simulated true trees.

Conclusions:

The choice of summary tree method is contingent on the specific research question and desired outcome.
Users can select the most suitable method by considering the trade-offs highlighted in the study.
This work aids researchers in making informed decisions for constructing summary trees in phylogenetic studies.