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COVFlow: virus phylodynamics analyses from selected SARS-CoV-2 sequences
Gonche Danesh; Corentin Boennec; Laura Verdurme; Mathilde Roussel; Sabine Trombert; Benoit Visseaux; Stephanie Haim-Boukobza; Samuel Alizon.
Affiliation
  • Gonche Danesh; MIVEGEC, CNRS, IRD, Universite de Montpellier
  • Corentin Boennec; MIVEGEC, CNRS, IRD, Universite de Montpellier
  • Laura Verdurme; Laboratoire CERBA, France
  • Mathilde Roussel; Laboratoire CERBA, France
  • Sabine Trombert; Laboratoire CERBA, France
  • Benoit Visseaux; Laboratoire CERBA, France
  • Stephanie Haim-Boukobza; Laboratoire CERBA, France
  • Samuel Alizon; MIVEGEC, CNRS, IRD, Universite de Montpellier
Preprint in En | PREPRINT-BIORXIV | ID: ppbiorxiv-496544
ABSTRACT
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 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.
License
cc_by_nc_nd
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Language: En Year: 2022 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Language: En Year: 2022 Document type: Preprint