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Article Dans Une Revue Peer Community Journal Année : 2023

COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences

Résumé

Phylodynamic analyses can generate important and timely data to optimise public health response to SARS-CoV-2 outbreaks and epidemics. However, their implementation is hampered by the massive amount of sequence data and the difficulty to parameterise dedicated software packages. We introduce the COVFlow pipeline, accessible at https://gitlab.in2p3.fr/ete/CoV-flow, which allows a user to select sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID) database according to user-specified criteria, to perform basic phylogenetic analyses, and to produce an XML file to be run in the Beast2 software package. We illustrate the potential of this tool by studying two sets of sequences from the Delta variant in two French regions. This pipeline can facilitate the use of virus sequence data at the local level, for instance, to track the dynamics of a particular lineage or variant in a region of interest.
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Dates et versions

hal-04246696 , version 1 (17-10-2023)

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Paternité

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Gonché Danesh, Corentin Boennec, Laura Verdurme, Mathilde Roussel, Sabine Trombert-Paolantoni, et al.. COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences. Peer Community Journal, 2023, 3, pp.e101. ⟨10.24072/pcjournal.333⟩. ⟨hal-04246696⟩
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