ArticleScientific reports2021
Data-driven analysis of amino acid change dynamics timely reveals SARS-CoV-2 variant emergence.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Article
- Unsupervised detection and fitness estimation of emerging SARS-CoV-2 variants: Application to wastewater samples (ANRS0160).PLoS computational biology · 2025Article
- Lightweight multiscale early warning system for influenza A spillovers.Science advances · 2025Article
- Epidemic-induced local awareness behavior inferred from surveys and genetic sequence data.Nature communications · 2025Article
- A codon usage-based approach for the stratification of Influenza A across recent spillovers.Computational and structural biotechnology journal · 2025Article
- Data-driven recombination detection in viral genomes.Nature communications · 2024Article
- Systematic analysis of SARS-CoV-2 Omicron subvariants' impact on B and T cell epitopes.PloS one · 2024Article
- VariantHunter: a method and tool for fast detection of emerging SARS-CoV-2 variants.Database : the journal of biological databases and curation · 2023Article
- Early warning of emerging infectious diseases based on multimodal data.Biosafety and health · 2023Review
- Editorial: Identification of phenotypically important genomic variants.Frontiers in bioinformatics · 2023Article
- Early detection of SARS-CoV-2 variants through dynamic co-mutation network surveillance.Frontiers in public health · 2023Article
- CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning.GigaScience · 2022Article
- Semantic interoperability: ontological unpacking of a viral conceptual model.BMC bioinformatics · 2022Article
- COVID-19 Variant Surveillance and Social Determinants in Central Massachusetts: Development Study.JMIR formative research · 2022Article
- Mapping Data to Deep Understanding: Making the Most of the Deluge of SARS-CoV-2 Genome Sequences.mSystems · 2022Article
- The seasonal behaviour of COVID-19 and its galectin-like culprit of the viral spike.Methods in microbiology · 2022Article
- Analysis of co-occurring and mutually exclusive amino acid changes and detection of convergent and divergent evolution events in SARS-CoV-2.Computational and structural biotechnology journal · 2022Article
- A New Way to Trace SARS-CoV-2 Variants Through Weighted Network Analysis of Frequency Trajectories of Mutations.Frontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Since its emergence in late 2019, the diffusion of SARS-CoV-2 is associated with the evolution of its viral genome. The co-occurrence of specific amino acid changes, collectively named 'virus variant', requires scrutiny (as variants may hugely impact the agent's transmission, pathogenesis, or antigenicity); variant evolution is studied using phylogenetics. Yet, never has this problem been tackled by digging into data with ad hoc analysis techniques. Here we show that the emergence of variants can in fact be traced through data-driven methods, further capitalizing on the value of large collections of SARS-CoV-2 sequences. For all countries with sufficient data, we compute weekly counts of amino acid changes, unveil time-varying clusters of changes with similar-rapidly growing-dynamics, and then follow their evolution. Our method succeeds in timely associating clusters to variants of interest/concern, provided their change composition is well characterized. This allows us to detect variants' emergence, rise, peak, and eventual decline under competitive pressure of another variant. Our early warning system, exclusively relying on deposited sequences, shows the power of big data in this context, and concurs to calling for the wide spreading of public SARS-CoV-2 genome sequencing for improved surveillance and control of the COVID-19 pandemic.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.