The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
A large-scale benchmark study of existing algorithms for taxonomy-independent microbial community analysis
Open accessAbstract
Recent advances in massively parallel sequencing technology have created new opportunities to probe the hidden world of microbes. Taxonomy-independent clustering of the 16S rRNA gene is usually the first step in analyzing microbial communities. Dozens of algorithms have been developed in the last decade, but a comprehensive benchmark study is lacking. Here, we survey algorithms currently used by microbiologists, and compare seven representative methods in a large-scale benchmark study that addresses several issues of concern. A new experimental protocol was developed that allows different algorithms to be compared using the same platform, and several criteria were introduced to facilitate a quantitative evaluation of the clustering performance of each algorithm. We found that existing methods vary widely in their outputs, and that inappropriate use of distance levels for taxonomic assignments likely resulted in substantial overestimates of biodiversity in many studies. The benchmark study identified our recently developed ESPRIT-Tree, a fast implementation of the average linkage-based hierarchical clustering algorithm, as one of the best algorithms available in terms of computational efficiency and clustering accuracy.
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Cites
Prokaryotes: The unseen majority
Whitman, W. B., Coleman, D. C., & Wiebe, W. J. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.12.6578 · Cited by 4,871
Human gut microbiota in obesity and after gastric bypass
Zhang, H., DiBaise, J. K., Zuccolo, A., Kudrna, D., Braidotti, M., Yu, Y., Parameswaran, P., Crowell, M. D., Wing, R., Rittmann, B. E., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0812600106 · Cited by 1,880
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
Self-citationPyrosequencing analysis of the oral microflora of healthy adults
Keijser, B. J. F., Zaura, E., Huse, S. M., van der Vossen, J. M. B. M., Schuren, F. H. J., Montijn, R. C., ten Cate, J. M., & Crielaard, W. (2008) · Journal of Dental Research · doi:10.1177/154405910808701104 · Cited by 669 · cited 2×
“It has been reported that microbial communities are much more diverse than expected [19, 20], which suggests that the underlying assumption of MSA might not be valid because parts of the sequence are not homologous due to insertions and deletions, or because so much change has occurred that bases that are the same are…”
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Cited by
A general species delimitation method with applications to phylogenetic placements
Zhang, J., Kapli, P., Pavlidis, P., & Stamatakis, A. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt499 · Cited by 3,062
Environmental DNA for wildlife biology and biodiversity monitoring
Bohmann, K., Evans, A., Gilbert, M. T. P., Carvalho, G. R., Creer, S., Knapp, M., Yu, D. W., & de Bruyn, M. (2014) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2014.04.003 · Cited by 1,348
Ursell, L. K., Metcalf, J. L., Parfrey, L. W., & Knight, R. (2012) · Nutrition Reviews · doi:10.1111/j.1753-4887.2012.00493.x · Cited by 1,255
Self-citationCharacterization of the gut microbiome using 16S or shotgun metagenomics
Jovel, J., Patterson, J., Wang, W., Hotte, N., O'Keefe, S., Mitchel, T., Perry, T., Kao, D., Mason, A. L., Madsen, K. L., et al. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00459 · Cited by 942
Eren, A. M., Morrison, H. G., Lescault, P. J., Reveillaud, J., Vineis, J. H., & Sogin, M. L. (2015) · The ISME Journal · doi:10.1038/ismej.2014.195 · Cited by 607
Metadata
- Authors
- Sun, Y., Cai, Y., Huse, S. M., Knight, R., Farmerie, W. G., Wang, X., & Mai, V.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-04-27
- Volume
- 13
- Issue
- 1
- Pages
- 107-121
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W2130208436
- Cited by
- 170
- References
- 4
- FWCI
- 6.94
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Sun, Y., Cai, Y., Huse, S. M., Knight, R., Farmerie, W. G., Wang, X., & Mai, V. (2012). A large-scale benchmark study of existing algorithms for taxonomy-independent microbial community analysis. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbr009
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
