TreeTime: Maximum-likelihood phylodynamic analysis

By Pavel Sagulenko, Vadim Puller, Richard A. Neher. bioRxiv, 2017

1,123 citations recorded by the source corpus.

Mutations that accumulate in the genome of replicating biological organisms can be used to infer their evolutionary history. In the case of measurably evolving organisms genomes often reveal their detailed spatiotemporal spread. Such phylodynamic analyses are particularly useful to understand the epidemiology of rapidly evolving viral pathogens. The number of genome sequences available for different pathogens, however, has increased dramatically over the last couple of years and traditional methods for phylodynamic analysis scale poorly with growing data sets. Here, we present TreeTime, a Python based framework for phylodynamic analysis using an approximate Maximum Likelihood approach. TreeTime can estimate ancestral states, infer evolution models, reroot trees to maximize temporal signals, estimate molecular clock phylogenies and population size histories. The run time of TreeTime scales linearly with data set size.

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/2168b13a869701ff842d4c855ab9bd5313511c9d

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Citations in the corpus

Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses OC43 and 229e (2020, positive): “…and Rahmann, 2012 ) within each HCoV directory follows the general outline of a Nextstrain build (Nextstrain, RRID:SCR_018223) and was used to align each gene to a reference strain and build a time-resolved phylogeny with IQ-Tree v1 ( Nguyen et al., 2015 ) and TimeTree ( Sagulenko et al., 2018 ).”
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10 (2018, background): “These programs use least-squares algorithms (LSD) or maximum likelihood inference (TreeDater, TreeTime) and provide rapid analysis on large data sets for a subset of the models that BEAST provides.”
Nextstrain: real-time tracking of pathogen evolution (2017, methodology): “This leverages the maximum likelihood phylodynamic analyses implemented in TreeTime [4], allowing a full analysis of the entire Ebola epidemic (n=1581 genomes) in under 2 hours on a modern laptop computer.”
A human coronavirus evolves antigenically to escape antibody immunity (2020, methodology): “(B) A plot produced by TreeTime (Sagulenko et al., 2018) showing the correlation between the distance of tip nodes from the root and sampling date.”