The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Microbiome, Metagenomics, and High-Dimensional Compositional Data Analysis
Abstract
The human microbiome is the totality of all microbes in and on the human body, and its importance in health and disease has been increasingly recognized. High-throughput sequencing technologies have recently enabled scientists to obtain an unbiased quantification of all microbes constituting the microbiome. Often, a single sample can produce hundreds of millions of short sequencing reads. However, unique characteristics of the data produced by the new technologies, as well as the sheer magnitude of these data, make drawing valid biological inferences from microbiome studies difficult. Analysis of these big data poses great statistical and computational challenges. Important issues include normalization and quantification of relative taxa, bacterial genes, and metabolic abundances; incorporation of phylogenetic information into analysis of metagenomics data; and multivariate analysis of high-dimensional compositional data. We review existing methods, point out their limitations, and outline future research directions.
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Cites
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Lozupone, C., & Knight, R. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8228-8235.2005 · Cited by 8,227
Molecular Evolution and Phylogenetics
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A metagenome-wide association study of gut microbiota in type 2 diabetes
Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762
Host-Bacterial Mutualism in the Human Intestine
Bäckhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A., & Gordon, J. I. (2005) · Science · doi:10.1126/science.1104816 · Cited by 5,277
Richness of human gut microbiome correlates with metabolic markers
Le Chatelier, E., Nielsen, T., Qin, J., Prifti, E., Hildebrand, F., Falony, G., Almeida, M., Arumugam, M., Batto, J.-M., Kennedy, S., et al. (2013) · Nature · doi:10.1038/nature12506 · Cited by 4,662
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
Chen, J., & Li, H. (2013) · The Annals of Applied Statistics · doi:10.1214/12-aoas592 · Cited by 191
Self-citationA Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis
Xia, F., Chen, J., Fung, W. K., & Li, H. (2013) · Biometrics · doi:10.1111/biom.12079 · Cited by 144
Self-citation
Cited by
Lu, Y., Zhou, G., Ewald, J., Pang, Z., Shiri, T., & Xia, J. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad407 · Cited by 623
Consistent and correctable bias in metagenomic sequencing experiments
McLaren, M. R., Willis, A. D., & Callahan, B. J. (2019) · eLife · doi:10.7554/elife.46923 · Cited by 429
Analysis of Microbiome Data in the Presence of Excess Zeros
Kaul, A., Mandal, S., Davidov, O., & Peddada, S. D. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.02114 · Cited by 328
A phylogenetic transform enhances analysis of compositional microbiota data
Silverman, J. D., Washburne, A. D., Mukherjee, S., & David, L. A. (2017) · eLife · doi:10.7554/elife.21887 · Cited by 319
Clark, J. S., Nemergut, D., Seyednasrollah, B., Turner, P. J., & Zhang, S. (2017) · Ecological Monographs · doi:10.1002/ecm.1241 · Cited by 283
Metadata
- Authors
- Li, H.
- Venue
- Annual Review of Statistics and Its Application
- Publisher
- Annual Reviews
- Published
- 2015-04-10
- Volume
- 2
- Issue
- 1
- Pages
- 73-94
- ISSN
- 2326-8298 (ISSN-L)
- 2326-831X
- OpenAlex
- W2163903604
- Cited by
- 288
- References
- 9
- FWCI
- 1.40
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
