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Dating Phylogenies with Hybrid Local Molecular Clocks Stephane Aris-Brosou1,2
 

Summary: Dating Phylogenies with Hybrid Local Molecular Clocks
Ste´phane Aris-Brosou1,2
*
1 Department of Biology, University of Ottawa, Ontario, Canada, 2 Department of Mathematics and Statistics, University of Ottawa, Ontario, Canada
Background. Because rates of evolution and species divergence times cannot be estimated directly from molecular data, all
current dating methods require that specific assumptions be made before inferring any divergence time. These assumptions
typically bear either on rates of molecular evolution (molecular clock hypothesis, local clocks models) or on both rates and
times (penalized likelihood, Bayesian methods). However, most of these assumptions can affect estimated dates, oftentimes
because they underestimate large amounts of rate change. Principal Findings. A significant modification to a recently
proposed ad hoc rate-smoothing algorithm is described, in which local molecular clocks are automatically placed on
a phylogeny. This modification makes use of hybrid approaches that borrow from recent theoretical developments in
microarray data analysis. An ad hoc integration of phylogenetic uncertainty under these local clock models is also described.
The performance and accuracy of the new methods are evaluated by reanalyzing three published data sets. Conclusions. It is
shown that the new maximum likelihood hybrid methods can perform better than penalized likelihood and almost as well as
uncorrelated Bayesian models. However, the new methods still tend to underestimate the actual amount of rate change. This
work demonstrates the difficulty of estimating divergence times using local molecular clocks.
Citation: Aris-Brosou S (2007) Dating Phylogenies with Hybrid Local Molecular Clocks. PLoS ONE 2(9): e879. doi:10.1371/journal.pone.0000879
INTRODUCTION
Estimating divergence times from molecular data is a special
statistical endeavor, as the parameters of interest cannot be

  

Source: Aris-Brosou, Stéphane - Department of Biology, University of Ottawa

 

Collections: Biology and Medicine