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McBroome J, Martin J, de Bernardi Schneider A, Turakhia Y, Corbett-Detig R. Identifying SARS-CoV-2 regional introductions and transmission clusters in real time. Virus Evol 2022; 8:veac048. [PMID: 35769891 PMCID: PMC9214145 DOI: 10.1093/ve/veac048] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 04/04/2022] [Accepted: 06/13/2022] [Indexed: 12/31/2022] Open
Abstract
The unprecedented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) global sequencing effort has suffered from an analytical bottleneck. Many existing methods for phylogenetic analysis are designed for sparse, static datasets and are too computationally expensive to apply to densely sampled, rapidly expanding datasets when results are needed immediately to inform public health action. For example, public health is often concerned with identifying clusters of closely related samples, but the sheer scale of the data prevents manual inspection and the current computational models are often too expensive in time and resources. Even when results are available, intuitive data exploration tools are of critical importance to effective public health interpretation and action. To help address this need, we present a phylogenetic heuristic that quickly and efficiently identifies newly introduced strains in a region, resulting in clusters of infected individuals, and their putative geographic origins. We show that this approach performs well on simulated data and yields results largely congruent with more sophisticated Bayesian phylogeographic modeling approaches. We also introduce Cluster-Tracker (https://clustertracker.gi.ucsc.edu/), a novel interactive web-based tool to facilitate effective and intuitive SARS-CoV-2 geographic data exploration and visualization across the USA. Cluster-Tracker is updated daily and automatically identifies and highlights groups of closely related SARS-CoV-2 infections resulting from the transmission of the virus between two geographic areas by travelers, streamlining public health tracking of local viral diversity and emerging infection clusters. The site is open-source and designed to be easily configured to analyze any chosen region, making it a useful resource globally. The combination of these open-source tools will empower detailed investigations of the geographic origins and spread of SARS-CoV-2 and other densely sampled pathogens.
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Affiliation(s)
- Jakob McBroome
- Biomolecular Engineering and Genomics Institute, University of California, Santa Cruz 1156 High St, Santa Cruz, CA 95064, USA
| | - Jennifer Martin
- Biomolecular Engineering and Genomics Institute, University of California, Santa Cruz 1156 High St, Santa Cruz, CA 95064, USA
| | - Adriano de Bernardi Schneider
- Biomolecular Engineering and Genomics Institute, University of California, Santa Cruz 1156 High St, Santa Cruz, CA 95064, USA
| | - Yatish Turakhia
- Electrical and Computer Engineering, University of California, San Diego 9500 Gilman Dr, La Jolla, CA 92093, USA
| | - Russell Corbett-Detig
- Biomolecular Engineering and Genomics Institute, University of California, Santa Cruz 1156 High St, Santa Cruz, CA 95064, USA
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De Maio N, Boulton W, Weilguny L, Walker CR, Turakhia Y, Corbett-Detig R, Goldman N. phastSim: efficient simulation of sequence evolution for pandemic-scale datasets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.03.15.435416. [PMID: 33758852 PMCID: PMC7987011 DOI: 10.1101/2021.03.15.435416] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Sequence simulators are fundamental tools in bioinformatics, as they allow us to test data processing and inference tools, as well as being part of some inference methods. The ongoing surge in available sequence data is however testing the limits of our bioinformatics software. One example is the large number of SARS-CoV-2 genomes available, which are beyond the processing power of many methods, and simulating such large datasets is also proving difficult. Here we present a new algorithm and software for efficiently simulating sequence evolution along extremely large trees (e.g. > 100,000 tips) when the branches of the tree are short, as is typical in genomic epidemiology. Our algorithm is based on the Gillespie approach, and implements an efficient multi-layered search tree structure that provides high computational efficiency by taking advantage of the fact that only a small proportion of the genome is likely to mutate at each branch of the considered phylogeny. Our open source software is available from https://github.com/NicolaDM/phastSim and allows easy integration with other Python packages as well as a variety of evolutionary models, including indel models and new hypermutatability models that we developed to more realistically represent SARS-CoV-2 genome evolution.
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Affiliation(s)
- Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - William Boulton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Lukas Weilguny
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Conor R. Walker
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
| | - Yatish Turakhia
- Department of Electrical and Computer Engineering, University of California San Diego, San Diego, CA 92093, USA
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Nick Goldman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
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