Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen)

By Andrew Rambaut, T. T. Lam, Luiz Max Carvalho, Oliver George Pybus. Virus Evolution, 2016

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Gene sequences sampled at different points in time can be used to infer molecular phylogenies on a natural timescale of months or years, provided that the sequences in question undergo measurable amounts of evolutionary change between sampling times. Data sets with this property are termed heterochronous and have become increasingly common in several fields of biology, most notably the molecular epidemiology of rapidly evolving viruses. Here we introduce the cross-platform software tool, TempEst (formerly known as Path-O-Gen), for the visualization and analysis of temporally sampled sequence data. Given a molecular phylogeny and the dates of sampling for each sequence, TempEst uses an interactive regression approach to explore the association between genetic divergence through time and sampling dates. TempEst can be used to (1) assess whether there is sufficient temporal signal in the data to proceed with phylogenetic molecular clock analysis, and (2) identify sequences whose genetic divergence and sampling date are incongruent. Examination of the latter can help identify data quality problems, including errors in data annotation, sample contamination, sequence recombination, or alignment error. We recommend that all users of the molecular clock models implemented in BEAST first check their data using TempEst prior to analysis.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/5317cfc19eb349e1471ab0b522b56d74c8b098bc

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Citations in the corpus

treeio: an R package for phylogenetic tree input and output with richly annotated and associated data. (2019, background): “For example, it is advisable to identify and remove sequences whose genetic divergence and sampling date are incongruent before applying a molecular clock model to virus data (Rambaut et al. 2016).”
Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic (2020, methodology): “In order to examine temporal signal in the sequenced data, we plotted root-totip divergence against sampling time using TempEst (Rambaut et al., 2016) based on a maximum likelihood tree.”
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil (2021, methodology): “We first regressed root-to-tip genetic distances against sequence sampling dates (32) for the P.”