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GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences
The COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a reso...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778918/ https://www.ncbi.nlm.nih.gov/pubmed/33045727 http://dx.doi.org/10.1093/nar/gkaa808 |
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author | Fang, Shuyi Li, Kailing Shen, Jikui Liu, Sheng Liu, Juli Yang, Lei Hu, Chang-Deng Wan, Jun |
author_facet | Fang, Shuyi Li, Kailing Shen, Jikui Liu, Sheng Liu, Juli Yang, Lei Hu, Chang-Deng Wan, Jun |
author_sort | Fang, Shuyi |
collection | PubMed |
description | The COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a resource to provide comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete genomes. The database allows user to browse, search and download SNVs at any individual or multiple SARS-CoV-2 genomic positions, or within a chosen genomic region or protein, or in certain country/area of interest. GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes. For each month, the top 100 SNVs that were firstly identified world-widely can be retrieved. GESS also explores SNVs occurring simultaneously with specific SNVs of user's interests. Furthermore, the database can be of great help to calibrate mutation rates and identify conserved genome regions. Taken together, GESS is a powerful resource and tool to monitor SARS-CoV-2 migration and evolution according to featured genomic variations. It provides potential directive information for prevalence prediction, related public health policy making, and vaccine designs. |
format | Online Article Text |
id | pubmed-7778918 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77789182021-01-06 GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences Fang, Shuyi Li, Kailing Shen, Jikui Liu, Sheng Liu, Juli Yang, Lei Hu, Chang-Deng Wan, Jun Nucleic Acids Res Database Issue The COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a resource to provide comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete genomes. The database allows user to browse, search and download SNVs at any individual or multiple SARS-CoV-2 genomic positions, or within a chosen genomic region or protein, or in certain country/area of interest. GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes. For each month, the top 100 SNVs that were firstly identified world-widely can be retrieved. GESS also explores SNVs occurring simultaneously with specific SNVs of user's interests. Furthermore, the database can be of great help to calibrate mutation rates and identify conserved genome regions. Taken together, GESS is a powerful resource and tool to monitor SARS-CoV-2 migration and evolution according to featured genomic variations. It provides potential directive information for prevalence prediction, related public health policy making, and vaccine designs. Oxford University Press 2020-10-12 /pmc/articles/PMC7778918/ /pubmed/33045727 http://dx.doi.org/10.1093/nar/gkaa808 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Fang, Shuyi Li, Kailing Shen, Jikui Liu, Sheng Liu, Juli Yang, Lei Hu, Chang-Deng Wan, Jun GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences |
title | GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences |
title_full | GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences |
title_fullStr | GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences |
title_full_unstemmed | GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences |
title_short | GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences |
title_sort | gess: a database of global evaluation of sars-cov-2/hcov-19 sequences |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778918/ https://www.ncbi.nlm.nih.gov/pubmed/33045727 http://dx.doi.org/10.1093/nar/gkaa808 |
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