<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Alisoltani A</submitter><funding>NCATS NIH HHS</funding><funding>NIAID NIH HHS</funding><pagination>2714</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9781208</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>14(12)</volume><pubmed_abstract>The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased the demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. The majority of the currently available tools either require computational expertise to deploy them or limit user input to preselected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: (1) the visualization of the spatiotemporal dynamics of SARS-CoV-2 lineages and (2) a structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in pediatric, adult, and elderly populations (n > 1.7 million genomes). Whereas the spatiotemporal dynamics of the variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate the large-scale surveillance of circulating pathogens.</pubmed_abstract><journal>Viruses</journal><pubmed_title>ViralVar: A Web Tool for Multilevel Visualization of SARS-CoV-2 Genomes.</pubmed_title><pmcid>PMC9781208</pmcid><funding_grant_id>R21 AI163912</funding_grant_id><funding_grant_id>UL1 TR001422</funding_grant_id><funding_grant_id>U19 AI171110</funding_grant_id><funding_grant_id>U19 AI135964</funding_grant_id><pubmed_authors>Iranzadeh A</pubmed_authors><pubmed_authors>Dean TJ</pubmed_authors><pubmed_authors>Godzik A</pubmed_authors><pubmed_authors>Hultquist JF</pubmed_authors><pubmed_authors>Alisoltani A</pubmed_authors><pubmed_authors>Jaroszewski L</pubmed_authors><pubmed_authors>Simons LM</pubmed_authors><pubmed_authors>Ozer EA</pubmed_authors><pubmed_authors>Lorenzo-Redondo R</pubmed_authors></additional><is_claimable>false</is_claimable><name>ViralVar: A Web Tool for Multilevel Visualization of SARS-CoV-2 Genomes.</name><description>The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased the demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. The majority of the currently available tools either require computational expertise to deploy them or limit user input to preselected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: (1) the visualization of the spatiotemporal dynamics of SARS-CoV-2 lineages and (2) a structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in pediatric, adult, and elderly populations (n > 1.7 million genomes). Whereas the spatiotemporal dynamics of the variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate the large-scale surveillance of circulating pathogens.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Dec</publication><modification>2024-11-06T12:43:46.461Z</modification><creation>2024-11-06T12:43:46.461Z</creation></dates><accession>S-EPMC9781208</accession><cross_references><pubmed>36560718</pubmed><doi>10.3390/v14122714</doi></cross_references></HashMap>