ArticleiScience2022
Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Geoepidemiological perspective on COVID-19 pandemic review, an insight into the global impact.Frontiers in public health · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A key task of genomic surveillance of infectious viral diseases lies in the early detection of dangerous variants. Unexpected help to this end is provided by the analysis of deep sequencing data of viral samples, which are typically discarded after creating consensus sequences. Such analysis allows one to detect intra-host low-frequency mutations, which are a footprint of mutational processes underlying the origination of new variants. Their timely identification may improve public-health decision-making with respect to traditional approaches exploiting consensus sequences. We present the analysis of 220,788 high-quality deep sequencing SARS-CoV-2 samples, showing that many spike and nucleocapsid mutations of interest associated to the most circulating variants, including Beta, Delta, and Omicron, might have been intercepted several months in advance. Furthermore, we show that a refined genomic surveillance system leveraging deep sequencing data might allow one to pinpoint emerging mutation patterns, providing an automated data-driven support to virologists and epidemiologists.
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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 OpenQuestion graph.