IQ2MC: A New Framework to Infer Phylogenetic Time Trees Using IQ-TREE 3 and MCMCTree with Mixture Models

Piyumal Demotte, Muthukumaran Panchaksaram, Hashara Kumarasinghe , Nhan Ly-Trong, Mario dos Reis, Bui Quang Minh

IQ-TREE and MCMCtree are two widely used tools for inferring phylogenetic trees and 
estimating divergence times, respectively. As MCMCtree performs fast approximate Markov 
Chain Monte Carlo sampling to obtain the times along a fixed tree topology, it would be 
natural to use IQ-TREE to obtain the tree. However, integrating these tools seamlessly was 
not previously possible, as MCMCtree requires pre-calculation of the gradient and Hessian 
for fast approximate calculation of the likelihood, which were unavailable in IQ-TREE. 
Furthermore, MCMCtree only implements a small subset of substitution models, and 
complex models such as mixture models are not available. This is an important limitation 
because complex substitution models are required for reliable estimates of divergence times 
in deep phylogenies. Here, we introduce a new pipeline, IQ2MC, which facilitates the 
integration of IQ-TREE 3 and MCMCtree, substantially speeds up the pre-calculation steps, 
and allows the use of a wide range of IQ-TREE’s complex models in divergence time 
inference. IQ2MC provides an updated version IQ-TREE 3.0.1 to calculate the gradient and 
Hessian at the maximum likelihood branch lengths, and then MCMCtree is used for MCMC 
sampling of divergence times. IQ2MC also provides several advanced partition models and 
mixture models not available in the current MCMCtree workflow. We finally show the 
applications of IQ2MC on simulated and four empirical datasets of placental mammals, 
plants, eukaryotes/prokaryotes, and metazoan. A tutorial on how to use IQ2MC is available at 
https://iqtree.github.io/doc/Dating.