COVFlow:选定SARS-CoV-2基因组序列的病毒系统动力学分析

Gonché Danesh, Corentin Boennec, Laura Verdurme, Mathilde Roussel, Sabine Trombert-Paolantoni, Benoit Visseaux, Stéphanie Haim-Boukobza, Samuel Alizon
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引用次数: 0

摘要

系统动力学分析可以产生重要和及时的数据,以优化对SARS-CoV-2疫情和流行的公共卫生反应。然而,它们的实现受到大量序列数据和难以参数化专用软件包的阻碍。我们介绍了COVFlow管道,可在https://gitlab.in2p3.fr/ete/CoV-flow上访问,它允许用户根据用户指定的标准从全球共享禽流感数据倡议(GISAID)数据库中选择序列,进行基本的系统发育分析,并生成一个XML文件,以便在Beast2软件包中运行。我们通过研究来自两个法国地区的Delta变体的两组序列来说明该工具的潜力。这种管道可以促进在局部水平上使用病毒序列数据,例如,在感兴趣的区域跟踪特定谱系或变体的动态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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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