The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Exact sequence variants should replace operational taxonomic units in marker-gene data analysis
Open accessAbstract
Recent advances have made it possible to analyze high-throughput marker-gene sequencing data without resorting to the customary construction of molecular operational taxonomic units (OTUs): clusters of sequencing reads that differ by less than a fixed dissimilarity threshold. New methods control errors sufficiently such that amplicon sequence variants (ASVs) can be resolved exactly, down to the level of single-nucleotide differences over the sequenced gene region. The benefits of finer resolution are immediately apparent, and arguments for ASV methods have focused on their improved resolution. Less obvious, but we believe more important, are the broad benefits that derive from the status of ASVs as consistent labels with intrinsic biological meaning identified independently from a reference database. Here we discuss how these features grant ASVs the combined advantages of closed-reference OTUs—including computational costs that scale linearly with study size, simple merging between independently processed data sets, and forward prediction—and of de novo OTUs—including accurate measurement of diversity and applicability to communities lacking deep coverage in reference databases. We argue that the improvements in reusability, reproducibility and comprehensiveness are sufficiently great that ASVs should replace OTUs as the standard unit of marker-gene analysis and reporting.
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Cites
DADA2: High–resolution sample inference from Illumina amplicon data
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016) · Nature Methods · doi:10.1038/nmeth.3869 · Cited by 35,698
Self-citationDeblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns
Amir, A., McDonald, D., Navas-Molina, J. A., Kopylova, E., Morton, J. T., Zech Xu, Z., Kightley, E. P., Thompson, L. R., Hyde, E. R., Gonzalez, A., et al. (2017) · mSystems · doi:10.1128/msystems.00191-16 · Cited by 1,881
Temporal and spatial variation of the human microbiota during pregnancy
DiGiulio, D. B., Callahan, B. J., McMurdie, P. J., Costello, E. K., Lyell, D. J., Robaczewska, A., Sun, C. L., Goltsman, D. S. A., Wong, R. J., Shaw, G., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1502875112 · Cited by 1,129
Self-citationBaxter, N. T., Ruffin, M. T., Rogers, M. A. M., & Schloss, P. D. (2016) · Genome Medicine · doi:10.1186/s13073-016-0290-3 · Cited by 354
Cited by
Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A., & Callahan, B. J. (2018) · Microbiome · doi:10.1186/s40168-018-0605-2 · Cited by 3,493
Self-citationA communal catalogue reveals Earth's multiscale microbial diversity
Thompson, L. R., Sanders, J. G., McDonald, D., Amir, A., Ladau, J., Locey, K. J., Prill, R. J., Tripathi, A., Gibbons, S. M., Ackermann, G., et al. (2017) · Nature · doi:10.1038/nature24621 · Cited by 2,684
Microbiome definition re-visited: old concepts and new challenges
Berg, G., Rybakova, D., Fischer, D., Cernava, T., Vergès, M.-C. C., Charles, T., Chen, X., Cocolin, L., Eversole, K., Corral, G. H., et al. (2020) · Microbiome · doi:10.1186/s40168-020-00875-0 · Cited by 2,275
Best practices for analysing microbiomes
Knight, R., Vrbanac, A., Taylor, B. C., Aksenov, A., Callewaert, C., Debelius, J., Gonzalez, A., Kosciolek, T., McCall, L.-I., McDonald, D., et al. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0029-9 · Cited by 2,030
Durazzi, F., Sala, C., Castellani, G., Manfreda, G., Remondini, D., & De Cesare, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-82726-y · Cited by 594
Metadata
- Authors
- Callahan, B. J., McMurdie, P. J., & Holmes, S. P.
- Venue
- The ISME Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-07-21
- Volume
- 11
- Issue
- 12
- Pages
- 2639-2643
- ISSN
- 1751-7362 (ISSN-L)
- 1751-7370
- OpenAlex
- W2592367925
- Cited by
- 3,300
- References
- 4
- FWCI
- 75.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Callahan, B. J., McMurdie, P. J., & Holmes, S. P. (2017). Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. The ISME Journal. https://doi.org/10.1038/ismej.2017.119
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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