ViralFlow: an automated workflow for SARS-CoV-2 genome assembly, lineage assignment, mutations and intrahost variants detection

Author:

Dezordi Filipe ZimmerORCID,de Lima Campos TúlioORCID,Carneiro Jeronimo Pedro MiguelORCID,Aksenen Cleber FurtadoORCID,Almeida Suzana PortoORCID,Wallau Gabriel LuzORCID

Abstract

ABSTRACTThe 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.

Publisher

Cold Spring Harbor Laboratory

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