The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Balances: a New Perspective for Microbiome Analysis
Open accessAbstract
We propose a new algorithm for the identification of microbial signatures. These microbial signatures can be used for diagnosis, prognosis, or prediction of therapeutic response based on an individual’s specific microbiota.
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828
The Statistical Analysis of Compositional Data
Aitchison, J. (1986) · doi:10.1007/978-94-009-4109-0 · Cited by 4,383
Microbial translocation is a cause of systemic immune activation in chronic HIV infection
Brenchley, J. M., Price, D. A., Schacker, T. W., Asher, T. E., Silvestri, G., Rao, S., Kazzaz, Z., Bornstein, E., Lambotte, O., Altmann, D., et al. (2006) · Nature Medicine · doi:10.1038/nm1511 · Cited by 3,559
Microbiome Datasets Are Compositional: And This Is Not Optional
Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V., & Egozcue, J. J. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.02224 · Cited by 3,044 · cited 1×
“Except for the fact that microbiome abundance tables contain many zeros, microbiome data fit the definition of compositional data and, as already acknowledged by many authors (5, 6), their analysis requires the use of a proper mathematical theory (7).”
Self-citationAnalysis of composition of microbiomes: a novel method for studying microbial composition
Mandal, S., Van Treuren, W., White, R. A., Eggesbø, M., Knight, R., & Peddada, S. D. (2015) · Microbial Ecology in Health & Disease · doi:10.3402/mehd.v26.27663 · Cited by 1,942
Fernandes, A. D., Reid, J. N., Macklaim, J. M., McMurrough, T. A., Edgell, D. R., & Gloor, G. B. (2014) · Microbiome · doi:10.1186/2049-2618-2-15 · Cited by 1,329
It's all relative: analyzing microbiome data as compositions
Gloor, G. B., Wu, J. R., Pawlowsky-Glahn, V., & Egozcue, J. J. (2016) · Annals of Epidemiology · doi:10.1016/j.annepidem.2016.03.003 · Cited by 323
Self-citation
Cited by
Establishing microbial composition measurement standards with reference frames
Morton, J. T., Marotz, C., Washburne, A., Silverman, J., Zaramela, L. S., Edlund, A., Zengler, K., & Knight, R. (2019) · Nature Communications · doi:10.1038/s41467-019-10656-5 · Cited by 613
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 microbial compositions: a review of normalization and differential abundance analysis
Lin, H., & Peddada, S. D. (2020) · npj Biofilms and Microbiomes · doi:10.1038/s41522-020-00160-w · Cited by 341
“Some examples include gneiss 18 , phylofactorization 61,62 , PhILR 63 , and selbal 64 .”
BackgroundLongitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma
Björk, J. R., Bolte, L. A., Maltez Thomas, A., Lee, K. A., Rossi, N., Wind, T. T., Smit, L. M., Armanini, F., Asnicar, F., Blanco-Miguez, A., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02803-3 · Cited by 156
Becker, A., Schmartz, G. P., Gröger, L., Grammes, N., Galata, V., Philippeit, H., Weiland, J., Ludwig, N., Meese, E., Tierling, S., et al. (2021) · doi:10.1101/2021.02.07.21251098 · Cited by 102
Metadata
- Authors
- Rivera-Pinto, J., Egozcue, J. J., Pawlowsky-Glahn, V., Paredes, R., Noguera-Julian, M., & Calle, M. L.
- Venue
- mSystems
- Publisher
- American Society for Microbiology
- Published
- 2018-08-28
- Volume
- 3
- Issue
- 4
- ISSN
- 2379-5077 (ISSN-L)
- OpenAlex
- W2950746887
- Cited by
- 288
- References
- 9
- FWCI
- 9.26
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: Balances: a New Perspective for Microbiome Analysis. https://app.cochat.ai/papers/10.1128/msystems.00053-18
- The paper
- Rivera-Pinto, J., Egozcue, J. J., Pawlowsky-Glahn, V., Paredes, R., Noguera-Julian, M., & Calle, M. L. (2018). Balances: a New Perspective for Microbiome Analysis. mSystems. https://doi.org/10.1128/msystems.00053-18
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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.
