With the progression of the COVID-19 pandemic, large datasets of SARS-CoV-2 genome sequences were collected to closely monitor the evolution of the virus and identify the novel variants/strains. By analyzing genome sequencing data, health authorities can 'hunt' novel emerging variants of SARS-CoV-2 as early as possible, and then monitor their evolution and spread. We designed VariantHunter, a highly flexible and user-friendly tool for systematically monitoring the evolution of SARS-CoV-2 at global and regional levels. In VariantHunter, amino acid changes are analyzed over an interval of 4 weeks in an arbitrary geographical area (continent, country, or region); for every week in the interval, the prevalence is computed and changes are ranked based on their increase or decrease in prevalence. VariantHunter supports two main types of analysis: lineage-independent and lineage-specific. The former considers all the available data and aims to discover new viral variants. The latter evaluates specific lineages/viral variants to identify novel candidate designations (sub-lineages and sub-variants). Both analyses use simple statistics and visual representations (diffusion charts and heatmaps) to track viral evolution. A dataset explorer allows users to visualize available data and refine their selection. VariantHunter is a web application free to all users. The two types of supported analysis (lineage-independent and lineage-specific) allow user-friendly monitoring of the viral evolution, empowering genomic surveillance without requiring any computational background.Database URL: http://gmql.eu/variant_hunter/

VariantHunter: a method and tool for fast detection of emerging SARS-CoV-2 variants / P. Pinoli, A. Canakoglu, S. Ceri, M. Chiara, E. Ferrandi, L. Minotti, A. Bernasconi. - In: DATABASE. - ISSN 1758-0463. - 2023:(2023), pp. baad044.1-baad044.8. [10.1093/database/baad044]

VariantHunter: a method and tool for fast detection of emerging SARS-CoV-2 variants

M. Chiara;E. Ferrandi;
2023

Abstract

With the progression of the COVID-19 pandemic, large datasets of SARS-CoV-2 genome sequences were collected to closely monitor the evolution of the virus and identify the novel variants/strains. By analyzing genome sequencing data, health authorities can 'hunt' novel emerging variants of SARS-CoV-2 as early as possible, and then monitor their evolution and spread. We designed VariantHunter, a highly flexible and user-friendly tool for systematically monitoring the evolution of SARS-CoV-2 at global and regional levels. In VariantHunter, amino acid changes are analyzed over an interval of 4 weeks in an arbitrary geographical area (continent, country, or region); for every week in the interval, the prevalence is computed and changes are ranked based on their increase or decrease in prevalence. VariantHunter supports two main types of analysis: lineage-independent and lineage-specific. The former considers all the available data and aims to discover new viral variants. The latter evaluates specific lineages/viral variants to identify novel candidate designations (sub-lineages and sub-variants). Both analyses use simple statistics and visual representations (diffusion charts and heatmaps) to track viral evolution. A dataset explorer allows users to visualize available data and refine their selection. VariantHunter is a web application free to all users. The two types of supported analysis (lineage-independent and lineage-specific) allow user-friendly monitoring of the viral evolution, empowering genomic surveillance without requiring any computational background.Database URL: http://gmql.eu/variant_hunter/
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
Settore BIOS-08/A - Biologia molecolare
2023
Article (author)
File in questo prodotto:
File Dimensione Formato  
baad044.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 2.46 MB
Formato Adobe PDF
2.46 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1115568
Citazioni
  • ???jsp.display-item.citation.pmc??? 2
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
  • OpenAlex ND
social impact