Comparing a Menagerie of Models for Estimating Molecular Divergence Times

Details Comparing a Menagerie of Models for Estimating Molecular Divergence Times Comparing a Menagerie of Models for Estimating Molecular Divergence Times

2007-12-28

arxiv.org/abs/0712.4332v1

Biology

Quantitative Biology

Genomics

Scientific paper

Estimation of molecular evolutionary divergence times requires models of rate change. These vary with regard to the assumption of what quantity is penalized. The possibilities considered are the rate of evolution, the log of the rate of evolution and the inverse of the rate of evolution. These models also vary with regard to how time affects the expected variance of rate change. Here the alternatives are not at all, linearly with time and as the product of rate and time. This results in a set of nine models, both random walks and Brownian motion. A priori any of these models could be correct, yet different researchers may well prefer, or simply use, one rather than the others. Another variable is whether to use a scaling factor to take account of the variance of the process of rate change being unknown and therefore avoid minimizing the penalty function with unrealistically large times. Here the difference these models and assumptions make on a tree of mammals, with the root fixed and with a single internal node fixed, is measured. The similarity of models is measured as the correlation of their time estimates and visualized with a least squares tree. The fit of model to data is measured and Q-Q plots are shown. Comparing model estimates with each other, the age of clades within Laurasiatheria are seen to vary far more across models than those within Supraprimates (informally called Euarchontoglires). Especially problematic are the often-used fossil calibrated nodes of horse/rhino and whale/hippo clashing with times within Supraprimates and in particular no fossil rodent teeth older than ~60 mybp. A scaling factor in addition to penalizing rate change is seen to yield consistent relative time estimates irrespective of exactly where the calibration point is placed.

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