COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences
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 COV...
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| Format: | Article |
| Language: | English |
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2023-10-01
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| Online Access: | https://peercommunityjournal.org/articles/10.24072/pcjournal.333/ |
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| author | Danesh, Gonché Boennec, Corentin Verdurme, Laura Roussel, Mathilde Trombert-Paolantoni, Sabine Visseaux, Benoit Haim-Boukobza, Stéphanie Alizon, Samuel |
| author_facet | Danesh, Gonché Boennec, Corentin Verdurme, Laura Roussel, Mathilde Trombert-Paolantoni, Sabine Visseaux, Benoit Haim-Boukobza, Stéphanie Alizon, Samuel |
| author_sort | Danesh, Gonché |
| collection | DOAJ |
| description | 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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| format | Article |
| id | doaj-art-42385eca574d4043a9ff9c4dcff1369d |
| institution | Kabale University |
| issn | 2804-3871 |
| language | English |
| publishDate | 2023-10-01 |
| publisher | Peer Community In |
| record_format | Article |
| series | Peer Community Journal |
| spelling | doaj-art-42385eca574d4043a9ff9c4dcff1369d2025-02-07T10:16:48ZengPeer Community InPeer Community Journal2804-38712023-10-01310.24072/pcjournal.33310.24072/pcjournal.333COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences Danesh, Gonché0https://orcid.org/0000-0001-8688-7666Boennec, Corentin1Verdurme, Laura2Roussel, Mathilde3Trombert-Paolantoni, Sabine4Visseaux, Benoit5Haim-Boukobza, Stéphanie6Alizon, Samuel7https://orcid.org/0000-0002-0779-9543MIVEGEC, CNRS, IRD, Université de Montpellier, FranceMIVEGEC, CNRS, IRD, Université de Montpellier, FranceLaboratoire CERBA, Saint Ouen L’Aumône, FranceLaboratoire CERBA, Saint Ouen L’Aumône, FranceLaboratoire CERBA, Saint Ouen L’Aumône, FranceLaboratoire CERBA, Saint Ouen L’Aumône, FranceLaboratoire CERBA, Saint Ouen L’Aumône, FranceMIVEGEC, CNRS, IRD, Université de Montpellier, France; Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, FrancePhylodynamic 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. https://peercommunityjournal.org/articles/10.24072/pcjournal.333/COVID-19molecular epidemiologysequence databasephylogeneticspublic health |
| spellingShingle | Danesh, Gonché Boennec, Corentin Verdurme, Laura Roussel, Mathilde Trombert-Paolantoni, Sabine Visseaux, Benoit Haim-Boukobza, Stéphanie Alizon, Samuel COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences Peer Community Journal COVID-19 molecular epidemiology sequence database phylogenetics public health |
| title | COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences
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| title_full | COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences
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| title_fullStr | COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences
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| title_full_unstemmed | COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences
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| title_short | COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences
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| title_sort | covflow phylodynamics analyses of viruses from selected sars cov 2 genome sequences |
| topic | COVID-19 molecular epidemiology sequence database phylogenetics public health |
| url | https://peercommunityjournal.org/articles/10.24072/pcjournal.333/ |
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