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ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection
The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. T...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877152/ https://www.ncbi.nlm.nih.gov/pubmed/35215811 http://dx.doi.org/10.3390/v14020217 |
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author | Dezordi, Filipe Zimmer Neto, Antonio Marinho da Silva Campos, Túlio de Lima Jeronimo, Pedro Miguel Carneiro Aksenen, Cleber Furtado Almeida, Suzana Porto Wallau, Gabriel Luz |
author_facet | Dezordi, Filipe Zimmer Neto, Antonio Marinho da Silva Campos, Túlio de Lima Jeronimo, Pedro Miguel Carneiro Aksenen, Cleber Furtado Almeida, Suzana Porto Wallau, Gabriel Luz |
author_sort | Dezordi, Filipe Zimmer |
collection | PubMed |
description | The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. 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 steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis. |
format | Online Article Text |
id | pubmed-8877152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88771522022-02-26 ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection Dezordi, Filipe Zimmer Neto, Antonio Marinho da Silva Campos, Túlio de Lima Jeronimo, Pedro Miguel Carneiro Aksenen, Cleber Furtado Almeida, Suzana Porto Wallau, Gabriel Luz Viruses Article The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. 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 steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis. MDPI 2022-01-23 /pmc/articles/PMC8877152/ /pubmed/35215811 http://dx.doi.org/10.3390/v14020217 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Dezordi, Filipe Zimmer Neto, Antonio Marinho da Silva Campos, Túlio de Lima Jeronimo, Pedro Miguel Carneiro Aksenen, Cleber Furtado Almeida, Suzana Porto Wallau, Gabriel Luz ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection |
title | ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection |
title_full | ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection |
title_fullStr | ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection |
title_full_unstemmed | ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection |
title_short | ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection |
title_sort | viralflow: a versatile automated workflow for sars-cov-2 genome assembly, lineage assignment, mutations and intrahost variant detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877152/ https://www.ncbi.nlm.nih.gov/pubmed/35215811 http://dx.doi.org/10.3390/v14020217 |
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