ArticleiMetaOmics2026
Evidence tiers for strain-resolved long-read metagenomics.
Article in iMetaOmics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Long-read metagenomics links variants, repeats, and mobile elements across individual molecules and can reveal lineage turnover that is obscured at the species level. The strength of the resulting inference, however, depends on the type and genomic span of the recovered linkage. We distinguish four evidence units-strain profiles, local haplotype blocks, genome-scale strain candidates, and host-linkage evidence-and describe the diagnostics appropriate to each. Confidence is reported separately as candidate, supported, or high confidence in context, based on read assignment, allele coherence, coverage continuity, boundary support, and independent confirmation. Ambiguous placement, contamination, consensus collapse, coverage breaks, reference bias, or unresolved linkage should prompt more conservative terminology. Aligning terms with the available evidence reduces overstatement in claims of strain reconstruction, host assignment, persistence, replacement, and engraftment, while making analyses easier to compare and review.
Identifiers
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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 OpenQuestion graph.