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EMERGEN-DB : The French database for SARS-CoV-2 genomic surveillance and research

Authors: Messak, Imane; Mohamed, Anliat; Antoinat, Chriara; Le Bars, Arthur; Tonazzolli, Arianna; Demaille, Benjamin; Sand, Olivier; +21 Authors

EMERGEN-DB : The French database for SARS-CoV-2 genomic surveillance and research

Abstract

In January 2021, the French Ministries of Health (MSS) and Research (MESRI) launched EMERGEN, a national plan for SARS-CoV-2 genomic surveillance, which aims at monitoring the evolution of the COVID-19 in France, detecting new variants and supporting the integration of viral genomic data and health data for both surveillance and research. We present two components of the EMERGEN-Bioinfo digital platform developed by the IFB (Institut Français de Bioinformatique): (a) EMERGEN-DB, the database that collects and manages non-sensitive metadata (sample collection, sequencing method, …) and consensus SARS-CoV-2 genomic sequences produced by the 55 sequencing platforms of the consortium. Developed under Django, it is equipped with both user-friendly and application programmatic interfaces (API) that currently offer over 121 entry points, enabling users to upload their data and query the database manually or in batch. EMERGEN-DB also offers numerous tools to facilitate real-time monitoring of variant evolution and expansion throughout France (alerts, etc.), data export via the APIs, data brokering services to curate and manage the metadata before submitting them to the international repositories such as GISAID and EBI-ENA, and finally data exploration and visualization (summary tables, figures, maps, …) through the interactive pages (activity, sampling, …). (b) Rtools4emergen, an R package enabling to query EMERGEN-DB, to visualize data and to automatically generate reports. To date, EMERGEN-DB collects metadata from ~64 sequencing platforms and has gathered more than 520513 records, of which 120186 were submitted to GISAID via our brokering tool.

Keywords

genomic surveillance, SARS-CoV-2, EMERGEN-Bioinfo, COVID-19, EMERGEN-DB

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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