#55 Phylogenetics and the likelihood gradient with Xiang Ji

<p>In this episode, we chat about phylogenetics with <a href="http://xiang-ji-ncsu.github.io/">Xiang Ji</a>. We start with a general introduction to the field and then go deeper into the likelihood-based methods (maximum likelihood and Bayesian inference). In particular, we talk about the different ways to calculate the likelihood gradient, including a linear-time exact gradient algorithm recently published by Xiang and his colleagues.</p> <p>Links:</p> <ul> <li><a href="https://academic.oup.com/mbe/article/37/10/3047/5847600">Gradients Do Grow on Trees: A Linear-Time <em>O(N)</em>-Dimensional Gradient for Statistical Phylogenetics</a> (Xiang Ji, Zhenyu Zhang, Andrew Holbrook, Akihiko Nishimura, Guy Baele, Andrew Rambaut, Philippe Lemey, Marc A Suchard)</li> <li><a href="https://github.com/beagle-dev/beagle-lib">BEAGLE</a>: the package that implements the gradient algorithm</li> <li><a href="http://beast.community/">BEAST</a>: the program that implements the Hamiltonian Monte Carlo sampler and the molecular clock models</li> </ul>