Automation and evaluation of the SOWH Test with SOWHAT
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Abstract
The Swofford-Olsen-Waddell-Hillis (SOWH) test evaluates statistical support for incongruent phylogenetic topologies. It is commonly applied to determine if the maximum likelihood tree in a phylogenetic analysis is significantly different than an alternative hypothesis. The SOWH test compares the observed difference in log-likelihood between two topologies to a null distribution of differences in log-likelihood generated by parametric resampling. The test is a well-established phylogenetic method for topology testing, but it is sensitive to model misspecification, it is computationally burdensome to perform, and its implementation requires the investigator to make several decisions that each have the potential to affect the outcome of the test. We analyzed the effects of multiple factors using seven data sets to which the SOWH test was previously applied. These factors include a number of sample replicates, likelihood software, the introduction of gaps to simulated data, the use of distinct models of evolution for data simulation and likelihood inference, and a suggested test correction wherein an unresolved "zero-constrained" tree is used to simulate sequence data. To facilitate these analyses and future applications of the SOWH test, we wrote SOWHAT, a program that automates the SOWH test. We find that inadequate bootstrap sampling can change the outcome of the SOWH test. The results also show that using a zero-constrained tree for data simulation can result in a wider null distribution and higher p-values, but does not change the outcome of the SOWH test for most of the data sets tested here. These results will help others implement and evaluate the SOWH test and allow us to provide recommendations for future applications of the SOWH test. SOWHAT is available for download from https://github.com/josephryan/SOWHAT.
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The BFGS optimization method has been reported previously to produce unstable results on nucleotide alignments.
“The BFGS optimization method was turned off in the analyses of nucleotide alignments since it has been reported previously to produce unstable results (Church et al. 2015).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Church et al. 2015
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- Authors
- Church, S. H., Ryan, J. F., & Dunn, C. W.
- Affiliations
- Brown University (US)
- Corresponding author
- Church, Samuel H.
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-07-30
- Volume
- 64
- Issue
- 6
- Pages
- 1048-1058
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- PMC
- PMC4604836
- OpenAlex
- W2165758583
- Cited by
- 50
- References
- 20
- Citations by year
- 2023: 5 · 2022: 7 · 2021: 1 · 2020: 5 · 2019: 2 · 2018: 14 · 2017: 5 · 2016: 2 · 2015: 5 · 2014: 4
- FWCI
- 3.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Systematic Biology (publishedVersion, cc-by-nc)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (1004057)
- Brown University
- Office of Experimental Program to Stimulate Competitive Research (EPS‐1004057, 1004057)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- maximum likelihood tree, bootstrap sampling, model misspecification, phylogenetic simulation
- MeSH terms
- Classification, Computer Simulation, Data Interpretation, Statistical, Phylogeny, Software, Primulaceae
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