SGV-caller: SARS-CoV-2 genome variation caller

Given the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continuous analysis of its genomic variations at the nucleotide level is imperative to monitor the emergence of novel variants of concern. The Global Initiative on Sharing All Influenza Data (GISAID) serves as the <i>de facto</i> standard database for the genomic information of SARS-CoV-2. However, limitations of its data-sharing policy hinder the comprehensive analysis of genomic variations. To address this problem, we developed SGV-caller, a bioinformatics pipeline for analyzing the frequently updated GISAID database. SGV-caller compares input datasets with pre-existing databases and generates local databases encompassing nucleotide, amino acid, and codon-level genomic variations for each SARS-CoV-2 genome. Furthermore, SGV-caller accommodates SARS-CoV-2 genomes from non-GISAID sources as well as other viral genomes. SGV-caller source code and test data are available at https://github.com/wujiaqi06/SGV-caller.

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Publication Details

Journal
Heliyon
Published
2025-02-01
DOI
https://doi.org/10.1016/j.heliyon.2025.e42613
Citations
1
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
1.40

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article

SGV-caller: SARS-CoV-2 genome variation caller

Junko S. Takeuchi, Jiaqi Wu, So Nakagawa, Kirill Kryukov
1 citations
Heliyon
SARS-CoV-2 and COVID-19 Research
1.40
article

SGV-caller: SARS-CoV-2 genome variation caller

Junko S. Takeuchi, Jiaqi Wu, So Nakagawa, Kirill Kryukov
article en
1 citations

Abstract

Given the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continuous analysis of its genomic variations at the nucleotide level is imperative to monitor the emergence of novel variants of concern. The Global Initiative on Sharing All Influenza Data (GISAID) serves as the <i>de facto</i> standard database for the genomic information of SARS-CoV-2. However, limitations of its data-sharing policy hinder the comprehensive analysis of genomic variations. To address this problem, we developed SGV-caller, a bioinformatics pipeline for analyzing the frequently updated GISAID database. SGV-caller compares input datasets with pre-existing databases and generates local databases encompassing nucleotide, amino acid, and codon-level genomic variations for each SARS-CoV-2 genome. Furthermore, SGV-caller accommodates SARS-CoV-2 genomes from non-GISAID sources as well as other viral genomes. SGV-caller source code and test data are available at https://github.com/wujiaqi06/SGV-caller.

HeliyonVol. 11(4)
National Institute of Genetics (JP), Tokai University (JP), National Center for Global Health and Medicine (JP), Research Organization of Information and Systems (JP)
Core Research for Evolutional Science and Technology
Openalex Percentile: Top 24%
SARS-CoV-2 and COVID-19 Research
1.40
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SGV-caller: SARS-CoV-2 genome variation caller — Junko S. Takeuchi, Jiaqi Wu, et al. · Heliyon (2025) | TGRS Research Map | TGRS