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MALVIRUS: an integrated application for viral variant analysis

BACKGROUND: Being able to efficiently call variants from the increasing amount of sequencing data daily produced from multiple viral strains is of the utmost importance, as demonstrated during the COVID-19 pandemic, in order to track the spread of the viral strains across the globe. RESULTS: We pres...

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Autores principales: Ciccolella, Simone, Denti, Luca, Bonizzoni, Paola, Della Vedova, Gianluca, Pirola, Yuri, Previtali, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017741/
https://www.ncbi.nlm.nih.gov/pubmed/35439933
http://dx.doi.org/10.1186/s12859-022-04668-0
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author Ciccolella, Simone
Denti, Luca
Bonizzoni, Paola
Della Vedova, Gianluca
Pirola, Yuri
Previtali, Marco
author_facet Ciccolella, Simone
Denti, Luca
Bonizzoni, Paola
Della Vedova, Gianluca
Pirola, Yuri
Previtali, Marco
author_sort Ciccolella, Simone
collection PubMed
description BACKGROUND: Being able to efficiently call variants from the increasing amount of sequencing data daily produced from multiple viral strains is of the utmost importance, as demonstrated during the COVID-19 pandemic, in order to track the spread of the viral strains across the globe. RESULTS: We present MALVIRUS, an easy-to-install and easy-to-use application that assists users in multiple tasks required for the analysis of a viral population, such as the SARS-CoV-2. MALVIRUS allows to: (1) construct a variant catalog consisting in a set of variations (SNPs/indels) from the population sequences, (2) efficiently genotype and annotate variants of the catalog supported by a read sample, and (3) when the considered viral species is the SARS-CoV-2, assign the input sample to the most likely Pango lineages using the genotyped variations. CONCLUSIONS: Tests on Illumina and Nanopore samples proved the efficiency and the effectiveness of MALVIRUS in analyzing SARS-CoV-2 strain samples with respect to publicly available data provided by NCBI and the more complete dataset provided by GISAID. A comparison with state-of-the-art tools showed that MALVIRUS is always more precise and often have a better recall. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04668-0.
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spelling pubmed-90177412022-04-20 MALVIRUS: an integrated application for viral variant analysis Ciccolella, Simone Denti, Luca Bonizzoni, Paola Della Vedova, Gianluca Pirola, Yuri Previtali, Marco BMC Bioinformatics Software BACKGROUND: Being able to efficiently call variants from the increasing amount of sequencing data daily produced from multiple viral strains is of the utmost importance, as demonstrated during the COVID-19 pandemic, in order to track the spread of the viral strains across the globe. RESULTS: We present MALVIRUS, an easy-to-install and easy-to-use application that assists users in multiple tasks required for the analysis of a viral population, such as the SARS-CoV-2. MALVIRUS allows to: (1) construct a variant catalog consisting in a set of variations (SNPs/indels) from the population sequences, (2) efficiently genotype and annotate variants of the catalog supported by a read sample, and (3) when the considered viral species is the SARS-CoV-2, assign the input sample to the most likely Pango lineages using the genotyped variations. CONCLUSIONS: Tests on Illumina and Nanopore samples proved the efficiency and the effectiveness of MALVIRUS in analyzing SARS-CoV-2 strain samples with respect to publicly available data provided by NCBI and the more complete dataset provided by GISAID. A comparison with state-of-the-art tools showed that MALVIRUS is always more precise and often have a better recall. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04668-0. BioMed Central 2022-04-19 /pmc/articles/PMC9017741/ /pubmed/35439933 http://dx.doi.org/10.1186/s12859-022-04668-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Ciccolella, Simone
Denti, Luca
Bonizzoni, Paola
Della Vedova, Gianluca
Pirola, Yuri
Previtali, Marco
MALVIRUS: an integrated application for viral variant analysis
title MALVIRUS: an integrated application for viral variant analysis
title_full MALVIRUS: an integrated application for viral variant analysis
title_fullStr MALVIRUS: an integrated application for viral variant analysis
title_full_unstemmed MALVIRUS: an integrated application for viral variant analysis
title_short MALVIRUS: an integrated application for viral variant analysis
title_sort malvirus: an integrated application for viral variant analysis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017741/
https://www.ncbi.nlm.nih.gov/pubmed/35439933
http://dx.doi.org/10.1186/s12859-022-04668-0
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