ArticleEvolutionary bioinformatics online2008
How to summarize estimates of ancestral divergence times.
Article in Evolutionary bioinformatics online, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Article
- Wilson and Sarich (1969): The birth of a molecular evolution research paradigm.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Mitogenomes Reveal Multiple Colonization of Mountains by Rattus in Sundaland.The Journal of heredity · 2020Article
- Evaluating the boundaries of marine biogeographic regions of the Southwestern Atlantic using halacarid mites (Halacaridae), meiobenthic organisms with a low dispersal potential.Ecology and evolution · 2019Article
- Turnover of southern cypresses in the post-Gondwanan world: extinction, transoceanic dispersal, adaptation and rediversification.The New phytologist · 2019Article
- Assessing the Performance of Ks Plots for Detecting Ancient Whole Genome Duplications.Genome biology and evolution · 2018Article
- Testing the molecular clock using mechanistic models of fossil preservation and molecular evolution.Proceedings. Biological sciences · 2017Article
- Horsetails Are Ancient Polyploids: Evidence from Equisetum giganteum.The Plant cell · 2015Article
- A genome triplication associated with early diversification of the core eudicots.Genome biology · 2012Article
- Performance of relaxed-clock methods in estimating evolutionary divergence times and their credibility intervals.Molecular biology and evolution · 2010Article
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Abstract
The use of molecular sequence data has increased interest in trying to date evolutionary events, with researchers wanting both an estimate of the divergence time and a confidence interval for that estimate. However, two methodological issues have recently been raised with respect to precision of the estimates: (i) the time of the ancestral event is over-estimated; and (ii) the confidence interval is asymmetrical. I argue that if the estimates of divergence time are considered to be samples from a lognormal probability distribution, then this would explain both of these problems. This implies that divergence times should be presented using geometric means rather than arithmetic means, both for estimates and for their confidence intervals. I present analyses based on both computer simulations and empirical data to show that this approach is effective for both single-gene and multiple-gene data sets. Treating divergence time as a lognormal variable thus provides a simple unifying framework for dealing with many of the problems associated with the estimation of divergence (and possibly coalescence) times. Use of this approach (based on geometric means) can, unfortunately, lead to very different biological conclusions compared to the currently used calculation methods (based on arithmetic means).
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