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Updated: Aug 7, 2026
08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
Supertree bootstrapping methods for assessing phylogenetic variation among genes in genome-scale data sets
J Gordon Burleigh1, Amy C Driskell, Michael J Sanderson
1Section of Evolution and Ecology, University of California, (J.G.B.), Davis, CA 95616, USA. jgburleigh@ucdavis.edu
Systematic Biology
|July 25, 2006
Summary
Nonparametric bootstrapping methods aid supertree inference confidence. Both input tree and stratified bootstrapping showed similar performance, often matching or exceeding supermatrix analysis support values for phylogenetic reconstruction.
Area of Science:
- Phylogenetics
- Computational Biology
- Genomics
Background:
- Assessing confidence in phylogenetic tree reconstruction is crucial.
- Supertree methods combine information from multiple gene trees.
- Bootstrapping is a common method for evaluating phylogenetic support.
Purpose of the Study:
- To evaluate two nonparametric bootstrapping methods for supertree inference.
- To compare supertree bootstrapping performance against supermatrix (total evidence) analysis.
- To investigate the utility of supertree bootstrapping for genome-scale data.
Main Methods:
- Input tree bootstrapping: gene trees sampled with replacement for replicate supertree analyses.
- Stratified bootstrapping: gene-specific bootstrap trees sampled randomly with replacement.
- Analysis of four published datasets with over 100 genes each.
Main Results:
- Both supertree bootstrapping methods yielded similar support values.
- Supertree bootstrap support was generally comparable to or slightly lower than supermatrix bootstrap support.
- In some cases, supertree bootstrap support exceeded supermatrix bootstrap support.
- Little difference was observed between input tree and stratified bootstrapping methods.
Conclusions:
- Nonparametric bootstrapping methods are valuable for assessing confidence in supertree inference.
- Supertree bootstrapping can provide insights into gene-specific variation in genome-scale datasets.
- These methods offer a complementary approach to supermatrix analysis for phylogenetic evaluation.
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