The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Updating the 97% identity threshold for 16S ribosomal RNA OTUs
Open accessAbstract
Motivation: The 16S ribosomal RNA (rRNA) gene is widely used to survey microbial communities. Sequences are often clustered into Operational Taxonomic Units (OTUs) as proxies for species. The canonical clustering threshold is 97% identity, which was proposed in 1994 when few 16S rRNA sequences were available, motivating a reassessment on current data. Results: Using a large set of high-quality 16S rRNA sequences from finished genomes, I assessed the correspondence of OTUs to species for five representative clustering algorithms using four accuracy metrics. All algorithms had comparable accuracy when tuned to a given metric. Optimal identity thresholds were ∼99% for full-length sequences and ∼100% for the V4 hypervariable region. Availability and implementation: Reference sequences and source code are provided in the Supplementary Material. Supplementary information: Supplementary data are available at Bioinformatics online.
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Cites
DADA2: High–resolution sample inference from Illumina amplicon data
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Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
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Comparison of the predicted and observed secondary structure of T4 phage lysozyme
Matthews, B. W. (1975) · Biochimica et Biophysica Acta (BBA) - Protein Structure · doi:10.1016/0005-2795(75)90109-9 · Cited by 5,399 · cited 8×
“I defined the correlation between OTUs and species (MCCsp), by considering a pair of sequences to be correctly classified if they belong to the same species and are in the same OTU.”
BackgroundInfluentialThe human microbiome: at the interface of health and disease
Cho, I., & Blaser, M. J. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3182 · Cited by 3,449
Ironing out the wrinkles in the rare biosphere through improved OTU clustering
Huse, S. M., Welch, D. M., Morrison, H. G., & Sogin, M. L. (2010) · Environmental Microbiology · doi:10.1111/j.1462-2920.2010.02193.x · Cited by 1,346
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Reduction of microbial diversity in grassland soil is driven by long-term climate warming
Wu, L., Zhang, Y., Guo, X., Ning, D., Zhou, X., Feng, J., Yuan, M. M., Liu, S., Guo, J., Gao, Z., et al. (2022) · Nature Microbiology · doi:10.1038/s41564-022-01147-3 · Cited by 404
The effect of 16S rRNA region choice on bacterial community metabarcoding results
Bukin, Y. S., Galachyants, Y. P., Morozov, I. V., Bukin, S. V., Zakharenko, A. S., & Zemskaya, T. I. (2019) · Scientific Data · doi:10.1038/sdata.2019.7 · Cited by 394
Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences
Edgar, R. C. (2018) · PeerJ · doi:10.7717/peerj.4652 · Cited by 319
Self-citationHigh-throughput microbial culturomics using automation and machine learning
Huang, Y., Sheth, R. U., Zhao, S., Cohen, L. A., Dabaghi, K., Moody, T., Sun, Y., Ricaurte, D., Richardson, M., Velez-Cortes, F., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01674-2 · Cited by 283
Dhillon, J., Li, Z., & Ortiz, R. M. (2019) · Current Developments in Nutrition · doi:10.1093/cdn/nzz079 · Cited by 69
Metadata
- Authors
- Edgar, R. C.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-02-28
- Volume
- 34
- Issue
- 14
- Pages
- 2371-2375
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2757805629
- Cited by
- 723
- References
- 6
- FWCI
- 24.25
- Type
- journal article
- Language
- en
- Open access
- bronze
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