PCI Genomics

239

Title *

COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequencesuse asterix (*) to get italics

Authors *

Gonché Danesh, Corentin Boennec, Laura Verdurme, Mathilde Roussel, Sabine Trombert-Paolantoni, Benoit Visseaux, Stephanie Haim-Boukobza, Samuel AlizonPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year *

2023

Picture *

Abstract *

<p style="text-align: justify;">Phylodynamic analyses 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 <a href="https://gitlab.in2p3.fr/ete/CoV-flow" target="_blank" rel="noopener">https://gitlab.in2p3.fr/ete/CoV-flow</a>, 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.</p>

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https://gisaid.org/You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://

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https://gitlab.in2p3.fr/ete/CoV-flow/scriptsYou should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://

Indicate the full web address (DOI, SWHID or URL) giving public access to these codes (if you have any problems with the deposit of your codes, please contact contact@genomics.peercommunityin.org). In case all raw codes are included in the preprint, indicate the DOI or URL of the preprint. *

https://zenodo.org/record/8016623You should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://

Keywords (optional)

COVID-19, molecular epidemiology, sequence database, phylogenetics, public health

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields *

Bioinformatics, Evolutionary genomics

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Submission date

2022-12-12 09:04:01

Recommender

Emmanuelle Lerat

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