Efficient Methods for Dating Evolutionary Divergences

Reliable estimates of divergence times are crucial for biological studies to decipher temporal patterns of macro- and microevolution of genes and organisms. Molecular sequences have become the primary source of data for estimating divergence times. The sizes of molecular data sets have grown quickly due to the development of inexpensive sequencing technology. To deal with the increasing volumes of molecular data, many efficient dating methods are being developed. These methods not only relax the molecular clock and offer flexibility to use multiple clock calibrations, but also complete calculations much more quickly than Bayesian approaches. Here, we discuss the theoretical and practical aspects of these non-Bayesian approaches and present a guide to using these methods effectively. We suggest that the computational speed and reliability of non-Bayesian relaxed-clock methods offer opportunities for enhancing scientific rigour and reproducibility in biological research for large and small data sets.