Combined Sum of Squares Penalties for Molecular Divergence Time Estimation
Peter J. Waddell, Prasanth Kalakota

TL;DR
This paper introduces combined sum of squares penalties for estimating molecular divergence times under rate variation models, highlighting the importance of calibration data quality and model choice.
Contribution
It develops a novel penalized least squares approach incorporating multiple sources of uncertainty for divergence time estimation.
Findings
Estimated placental mammal root age decreased from 125 to 94 million years.
Calibration uncertainties significantly inflate divergence time estimates.
Better fossil and molecular data are needed for more accurate dating.
Abstract
Estimates of molecular divergence times when rates of evolution vary require the assumption of a model of rate change. Brownian motion is one such model, and since rates cannot become negative, a log Brownian model seems appropriate. Divergence time estimates can then be made using weighted least squares penalties. As sequences become long, this approach effectively becomes equivalent to penalized likelihood or Bayesian approaches. Different forms of the least squares penalty are considered to take into account correlation due to shared ancestors. It is shown that a scale parameter is also needed since the sum of squares changes with the scale of time. Errors or uncertainty on fossil calibrations, may be folded in with errors due to the stochastic nature of Brownian motion and ancestral polymorphism, giving a total sum of squares to be minimized. Applying these methods to placental…
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Taxonomy
TopicsMechanical and Optical Resonators · Analytical Chemistry and Sensors · Various Chemistry Research Topics
