ArticleViruses2022
Assessment of Inter-Laboratory Differences in SARS-CoV-2 Consensus Genome Assemblies between Public Health Laboratories in Australia.
Article in Viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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Who cites it
9 citing papers in PubMed.
- Whole-genome sequencing data from long-term serial passaging of 11 SARS-CoV-2 isolates.Microbiology resource announcements · 2025Article
- Illumina MiSeq and iSeq platforms yield comparable results for viral genomic sequencing.Journal of virological methods · 2025Article
- Long-term serial passaging of SARS-CoV-2 reveals signatures of convergent evolution.Journal of virology · 2025Article
- Enhancing public health surveillance: a comparative study of platform-specific and hybrid assembly approaches in SARS-CoV-2 genome sequencing.Microbial genomics · 2025Article
- PathoSeq-QC: a decision support bioinformatics workflow for robust genomic surveillance.Bioinformatics (Oxford, England) · 2025Article
- Observational
- Bioinformatic investigation of discordant sequence data for SARS-CoV-2: insights for robust genomic analysis during pandemic surveillance.Microbial genomics · 2023Article
- matOptimize: a parallel tree optimization method enables online phylogenetics for SARS-CoV-2.Bioinformatics (Oxford, England) · 2022Article
- Modeling infection from SARS-CoV-2 wastewater concentrations: promise, limitations, and future directions.Journal of water and health · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Whole-genome sequencing of viral isolates is critical for informing transmission patterns and for the ongoing evolution of pathogens, especially during a pandemic. However, when genomes have low variability in the early stages of a pandemic, the impact of technical and/or sequencing errors increases. We quantitatively assessed inter-laboratory differences in consensus genome assemblies of 72 matched SARS-CoV-2-positive specimens sequenced at different laboratories in Sydney, Australia. Raw sequence data were assembled using two different bioinformatics pipelines in parallel, and resulting consensus genomes were compared to detect laboratory-specific differences. Matched genome sequences were predominantly concordant, with a median pairwise identity of 99.997%. Identified differences were predominantly driven by ambiguous site content. Ignoring these produced differences in only 2.3% (5/216) of pairwise comparisons, each differing by a single nucleotide. Matched samples were assigned the same Pango lineage in 98.2% (212/216) of pairwise comparisons, and were mostly assigned to the same phylogenetic clade. However, epidemiological inference based only on single nucleotide variant distances may lead to significant differences in the number of defined clusters if variant allele frequency thresholds for consensus genome generation differ between laboratories. These results underscore the need for a unified, best-practices approach to bioinformatics between laboratories working on a common outbreak problem.
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