What question did this study set out to answer?

To evaluate the prevalence of recurrent artefactual intra-host single-nucleotide variants in deep-sequencing SARS-CoV-2 data and develop a dataset-aware masking method to improve evolutionary inferences.

August 20, 2026Molecular Biology and EvolutionOpen Access

Identification and Masking of Artefactual and Misleading Within-Host Variants in Deep-Sequencing SARS-CoV-2 Data

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Authors

KAKlara M. AnkerOpen Data Institute RPRosario Evans PenaUniversity of Oxford SKSteven A. KempUniversity of Cambridge

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Implication

Genomic analysis reveals sequencing-centre-specific artefactual variants in SARS-CoV-2 deep-sequencing data, suggesting dataset-aware masking is crucial for accurate transmission inference.

Key Points

To evaluate the prevalence of recurrent artefactual intra-host single-nucleotide variants in deep-sequencing SARS-CoV-2 data and develop a dataset-aware masking method to improve evolutionary inferences.
Analyzed intra-host single-nucleotide variants (iSNVs) across SARS-CoV-2 deep-sequencing data from the UK Office for National Statistics COVID-19 Infection Survey.
Developed a systematic, dataset-aware bioinformatic framework to identify and mask recurrent, noise-adapted artefactual iSNVs across distinct sequencing datasets.
Demonstrated that recurrent artefactual iSNVs persist under conservative minor allele frequency thresholds and are predominantly specific to individual sequencing centres rather than primer sets.
Showed that masking dataset-specific artefactual variants reduced spurious sharing of low-frequency variants and altered downstream estimates of within-host diversity and transmission bottleneck sizes.

Cite This Study

Anker et al. (2026) studied this question.

synapsesocial.com/papers/6a86b4cb8a91293e6a1cc4c7 https://doi.org/10.1093/molbev/msag209

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Implication

Genomic analysis reveals sequencing-centre-specific artefactual variants in SARS-CoV-2 deep-sequencing data, suggesting dataset-aware masking is crucial for accurate transmission inference.

Identification and Masking of Artefactual and Misleading Within-Host Variants in Deep-Sequencing SARS-CoV-2 Data

Discussion

Member takes

Implication

Key Points

Cite This Study

Identification and Masking of Artefactual and Misleading Within-Host Variants in Deep-Sequencing SARS-CoV-2 Data

Discussion

Member takes

Implication

Key Points

Cite This Study

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