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ViralFlow: an automated workflow for SARS-CoV-2 genome assembly, lineage assignment, mutations and intrahost variants detection (preprint)
medrxiv; 2021.
Preprint Dans Anglais | medRxiv | ID: ppzbmed-10.1101.2021.10.01.21264424
ABSTRACT
The COVID-19 pandemic, a disease caused by the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology to monitor and study this emerging virus. The current deluge of SARS-CoV-2 genomic data being generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows for data analysis. Here, we describe a workflow developed by our group to process and analyze large-scale SARS-CoV-2 Illumina amplicon sequencing data. This workflow automates all the steps involved in SARS-CoV-2 genomic

analysis:

data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The workflow presented here (https//github.com/dezordi/ViralFlow) is available through Docker or Singularity images, allowing implementation in laptops for small scale analyses or in high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores makes it a versatile tool for SARS-CoV-2 genomic analysis.
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Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Sujet Principal: Infections à coronavirus / COVID-19 langue: Anglais Année: 2021 Type de document: Preprint

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Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Sujet Principal: Infections à coronavirus / COVID-19 langue: Anglais Année: 2021 Type de document: Preprint