The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Toward Accurate and Quantitative Comparative Metagenomics
Open accessAbstract
Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized.
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Human gut microbiome viewed across age and geography
Yatsunenko, T., Rey, F. E., Manary, M. J., Trehan, I., Dominguez-Bello, M. G., Contreras, M., Magris, M., Hidalgo, G., Baldassano, R. N., Anokhin, A. P., et al. (2012) · Nature · doi:10.1038/nature11053 · Cited by 7,815
Reagent and laboratory contamination can critically impact sequence-based microbiome analyses
Salter, S. J., Cox, M. J., Turek, E. M., Calus, S. T., Cookson, W. O., Moffatt, M. F., Turner, P., Parkhill, J., Loman, N. J., & Walker, A. W. (2014) · BMC Biology · doi:10.1186/s12915-014-0087-z · Cited by 3,463
A framework for human microbiome research
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11209 · Cited by 2,650
Quail, M., Smith, M. E., Coupland, P., Otto, T. D., Harris, S. R., Connor, T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-341 · Cited by 2,031 · cited 2×
“Commonly used sequencers have different error rates and patterns (Quail et al., 2012), but their effects on taxonomic (Sinha et al.”
BackgroundSparse and Compositionally Robust Inference of Microbial Ecological Networks
Kurtz, Z. D., Müller, C. L., Miraldi, E. R., Littman, D. R., Blaser, M. J., & Bonneau, R. A. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004226 · Cited by 1,799
Metagenomic microbial community profiling using unique clade-specific marker genes
Segata, N., Waldron, L., Ballarini, A., Narasimhan, V., Jousson, O., & Huttenhower, C. (2012) · Nature Methods · doi:10.1038/nmeth.2066 · Cited by 1,776
Improving RNA-Seq expression estimates by correcting for fragment bias
Roberts, A., Trapnell, C., Donaghey, J., Rinn, J. L., & Pachter, L. (2011) · Genome Biology · doi:10.1186/gb-2011-12-3-r22 · Cited by 1,725
Biogeography and individuality shape function in the human skin metagenome
Program, N. C. S., Oh, J., Byrd, A. L., Deming, C., Conlan, S., Kong, H. H., & Segre, J. A. (2014) · Nature · doi:10.1038/nature13786 · Cited by 1,148
Keeling, P. J., Burki, F., Wilcox, H. M., Allam, B., Allen, E. E., Amaral-Zettler, L. A., Armbrust, E. V., Archibald, J. M., Bharti, A. K., Bell, C. J., et al. (2014) · PLoS Biology · doi:10.1371/journal.pbio.1001889 · Cited by 1,042
Actionable Diagnosis of Neuroleptospirosis by Next-Generation Sequencing
Wilson, M. R., Naccache, S. N., Samayoa, E., Biagtan, M., Bashir, H., Yu, G., Salamat, S. M., Somasekar, S., Federman, S., Miller, S., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1401268 · Cited by 977
Cited by
Stochastic Community Assembly: Does It Matter in Microbial Ecology?
Zhou, J., & Ning, D. (2017) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.00002-17 · Cited by 2,773
Systems biology and multi-omics integration: viewpoints from the metabolomics research community
Pinu, F. R., Beale, D. J., Paten, A. M., Kouremenos, K., Swarup, S., Schirra, H. J., & Wishart, D. (2019) · Metabolites · doi:10.3390/metabo9040076 · Cited by 723
Genomic diversity landscape of the honey bee gut microbiota
Ellegaard, K. M., & Engel, P. (2019) · Nature Communications · doi:10.1038/s41467-019-08303-0 · Cited by 268
Potential and active functions in the gut microbiota of a healthy human cohort
Tanca, A., Abbondio, M., Palomba, A., Fraumene, C., Manghina, V., Cucca, F., Fiorillo, E., & Uzzau, S. (2017) · Microbiome · doi:10.1186/s40168-017-0293-3 · Cited by 172
Leonard, M. M., Valitutti, F., Karathia, H., Pujolassos, M., Kenyon, V., Fanelli, B., Troisi, J., Subramanian, P., Camhi, S., Colucci, A., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2020322118 · Cited by 162
Metadata
- Authors
- Nayfach, S., & Pollard, K. S.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2016-08
- Volume
- 166
- Issue
- 5
- Pages
- 1103-1116
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2509730012
- Cited by
- 292
- References
- 15
- FWCI
- 12.34
- Type
- journal article
- Language
- en
- Open access
- bronze
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