PT - JOURNAL ARTICLE AU - Gonché Danesh AU - Corentin Boennec AU - Laura Verdurme AU - Mathilde Roussel AU - Sabine Trombert-Paolantoni AU - Benoit Visseaux AU - Stéphanie Haim-Boukobza AU - Samuel Alizon TI - COVFlow: virus phylodynamics analyses from selected SARS-CoV-2 sequences AID - 10.1101/2022.06.17.496544 DP - 2023 Jan 01 TA - bioRxiv PG - 2022.06.17.496544 4099 - http://biorxiv.org/content/early/2023/02/10/2022.06.17.496544.short 4100 - http://biorxiv.org/content/early/2023/02/10/2022.06.17.496544.full AB - 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.Competing Interest StatementThe authors have declared no competing interest.