ArticleComputational and structural biotechnology journal2021
AutoVEM: An automated tool to real-time monitor epidemic trends and key mutations in SARS-CoV-2 evolution.
Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Article
- SARS-CoV-2 within-host diversity of human hosts and its implications for viral immune evasion.mBio · 2023Article
- Article
- Bioinformatics for the Origin and Evolution of Viruses.Advances in experimental medicine and biology · 2022Article
- Genomic surveillance unfolds the SARS-CoV-2 transmission and divergence dynamics in Bangladesh.Frontiers in genetics · 2022Article
- AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus.Computational and structural biotechnology journal · 2021Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the global epidemic of SARS-CoV-2, it is important to effectively monitor the variation, haplotype subgroup epidemic trends and key mutations of SARS-CoV-2 over time. This is of great significance to the development of new vaccines, the update of therapeutic drugs, and the improvement of detection methods. The AutoVEM tool developed in the present study could complete all mutations detections, haplotypes classification, haplotype subgroup epidemic trends and candidate key mutations analysis for 131,576 SARS-CoV-2 genome sequences in 18 h on a 1 core CPU and 2 GB RAM computer. Through haplotype subgroup epidemic trends analysis of 131,576 genome sequences, the great significance of the previous 4 specific sites (C241T, C3037T, C14408T and A23403G) was further revealed, and 6 new mutation sites of highly linked (T445C, C6286T, C22227T, G25563T, C26801G and G29645T) were discovered for the first time that might be related to the infectivity, pathogenicity or host adaptability of SARS-CoV-2. In brief, we proposed an integrative method and developed an efficient automated tool to monitor haplotype subgroup epidemic trends and screen for the candidate key mutations in the evolution of SARS-CoV-2 over time for the first time, and all data could be updated quickly to track the prevalence of previous key mutations and new candidate key mutations because of high efficiency of the tool. In addition, the idea of combinatorial analysis in the present study can also provide a reference for the mutation monitoring of other viruses.
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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.