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SARS-CoV-2 RECoVERY: a multi-platform open-source bioinformatic pipeline for the automatic construction and analysis of SARS-CoV-2 genomes from NGS sequencing data

Luca De Sabato, Gabriele Vaccari, View ORCID ProfileArnold Knijn, Giovanni Ianiro, Ilaria Di Bartolo, Stefano Morabito
doi: https://doi.org/10.1101/2021.01.16.425365
Luca De Sabato
1Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
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Gabriele Vaccari
1Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
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  • For correspondence: gabriele.vaccari@iss.it
Arnold Knijn
2European Reference Laboratory for Escherichia coli, Istituto Superiore di Sanità, Rome, Italy
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  • ORCID record for Arnold Knijn
Giovanni Ianiro
1Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
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Ilaria Di Bartolo
1Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
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Stefano Morabito
2European Reference Laboratory for Escherichia coli, Istituto Superiore di Sanità, Rome, Italy
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Abstract

Background Since its first appearance in December 2019, the novel Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), spread worldwide causing an increasing number of cases and deaths (35,537,491 and 1,042,798, respectively at the time of writing, https://covid19.who.int). Similarly, the number of complete viral genome sequences produced by Next Generation Sequencing (NGS), increased exponentially. NGS enables a rapid accumulation of a large number of sequences. However, bioinformatics analyses are critical and require combined approaches for data analysis, which can be challenging for non-bioinformaticians.

Results A user-friendly and sequencing platform-independent bioinformatics pipeline, named SARS-CoV-2 RECoVERY (REconstruction of CoronaVirus gEnomes & Rapid analYsis) has been developed to build SARS-CoV-2 complete genomes from raw sequencing reads and to investigate variants. The genomes built by SARS-CoV-2 RECoVERY were compared with those obtained using other software available and revealed comparable or better performances of SARS–CoV2 RECoVERY. Depending on the number of reads, the complete genome reconstruction and variants analysis can be achieved in less than one hour. The pipeline was implemented in the multi-usage open-source Galaxy platform allowing an easy access to the software and providing computational and storage resources to the community.

Conclusions SARS-CoV-2 RECoVERY is a piece of software destined to the scientific community working on SARS-CoV-2 phylogeny and molecular characterisation, providing a performant tool for the complete reconstruction and variants’ analysis of the viral genome. Additionally, the simple software interface and the ability to use it through a Galaxy instance without the need to implement computing and storage infrastructures, make SARS-CoV-2 RECoVERY a resource also for virologists with little or no bioinformatics skills.

Availability and implementation The pipeline SARS-CoV-2 RECoVERY (REconstruction of COronaVirus gEnomes & Rapid analYsis) is implemented in the Galaxy instance ARIES (https://aries.iss.it).

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted February 05, 2021.
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SARS-CoV-2 RECoVERY: a multi-platform open-source bioinformatic pipeline for the automatic construction and analysis of SARS-CoV-2 genomes from NGS sequencing data
Luca De Sabato, Gabriele Vaccari, Arnold Knijn, Giovanni Ianiro, Ilaria Di Bartolo, Stefano Morabito
bioRxiv 2021.01.16.425365; doi: https://doi.org/10.1101/2021.01.16.425365
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SARS-CoV-2 RECoVERY: a multi-platform open-source bioinformatic pipeline for the automatic construction and analysis of SARS-CoV-2 genomes from NGS sequencing data
Luca De Sabato, Gabriele Vaccari, Arnold Knijn, Giovanni Ianiro, Ilaria Di Bartolo, Stefano Morabito
bioRxiv 2021.01.16.425365; doi: https://doi.org/10.1101/2021.01.16.425365

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