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PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification
MOTIVATION: Since the identification of the novel coronavirus (SARS-CoV-2), the scientific community has made a huge effort to understand the virus biology and to develop vaccines. Next-generation sequencing strategies have been successful in understanding the evolution of infectious diseases as wel...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013232/ https://www.ncbi.nlm.nih.gov/pubmed/35437474 http://dx.doi.org/10.7717/peerj.13300 |
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author | Oliveira, Renato R. M. Costa Negri, Tatianne Nunes, Gisele Medeiros, Inácio Araújo, Guilherme de Oliveira Silva, Fabricio Estefano Santana de Souza, Jorge Alves, Ronnie Oliveira, Guilherme |
author_facet | Oliveira, Renato R. M. Costa Negri, Tatianne Nunes, Gisele Medeiros, Inácio Araújo, Guilherme de Oliveira Silva, Fabricio Estefano Santana de Souza, Jorge Alves, Ronnie Oliveira, Guilherme |
author_sort | Oliveira, Renato R. M. |
collection | PubMed |
description | MOTIVATION: Since the identification of the novel coronavirus (SARS-CoV-2), the scientific community has made a huge effort to understand the virus biology and to develop vaccines. Next-generation sequencing strategies have been successful in understanding the evolution of infectious diseases as well as facilitating the development of molecular diagnostics and treatments. Thousands of genomes are being generated weekly to understand the genetic characteristics of this virus. Efficient pipelines are needed to analyze the vast amount of data generated. Here we present a new pipeline designed for genomic analysis and variant identification of the SARS-CoV-2 virus. RESULTS: PipeCoV shows better performance when compared to well-established SARS-CoV-2 pipelines, with a lower content of Ns and higher genome coverage when compared to the Wuhan reference. It also provides a variant report not offered by other tested pipelines. AVAILABILITY: https://github.com/alvesrco/pipecov. |
format | Online Article Text |
id | pubmed-9013232 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90132322022-04-17 PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification Oliveira, Renato R. M. Costa Negri, Tatianne Nunes, Gisele Medeiros, Inácio Araújo, Guilherme de Oliveira Silva, Fabricio Estefano Santana de Souza, Jorge Alves, Ronnie Oliveira, Guilherme PeerJ Bioinformatics MOTIVATION: Since the identification of the novel coronavirus (SARS-CoV-2), the scientific community has made a huge effort to understand the virus biology and to develop vaccines. Next-generation sequencing strategies have been successful in understanding the evolution of infectious diseases as well as facilitating the development of molecular diagnostics and treatments. Thousands of genomes are being generated weekly to understand the genetic characteristics of this virus. Efficient pipelines are needed to analyze the vast amount of data generated. Here we present a new pipeline designed for genomic analysis and variant identification of the SARS-CoV-2 virus. RESULTS: PipeCoV shows better performance when compared to well-established SARS-CoV-2 pipelines, with a lower content of Ns and higher genome coverage when compared to the Wuhan reference. It also provides a variant report not offered by other tested pipelines. AVAILABILITY: https://github.com/alvesrco/pipecov. PeerJ Inc. 2022-04-13 /pmc/articles/PMC9013232/ /pubmed/35437474 http://dx.doi.org/10.7717/peerj.13300 Text en © 2022 Oliveira et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Oliveira, Renato R. M. Costa Negri, Tatianne Nunes, Gisele Medeiros, Inácio Araújo, Guilherme de Oliveira Silva, Fabricio Estefano Santana de Souza, Jorge Alves, Ronnie Oliveira, Guilherme PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification |
title | PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification |
title_full | PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification |
title_fullStr | PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification |
title_full_unstemmed | PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification |
title_short | PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification |
title_sort | pipecov: a pipeline for sars-cov-2 genome assembly, annotation and variant identification |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013232/ https://www.ncbi.nlm.nih.gov/pubmed/35437474 http://dx.doi.org/10.7717/peerj.13300 |
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