The DOI matches its Crossref record; 210 of the 210 references it cites were found in a registry or an index.
A clinician's guide to microbiome analysis
Abstract
Microbiome analysis involves determining the composition and function of a community of microorganisms in a particular location. For the gastroenterologist, this technology opens up a rapidly evolving set of challenges and opportunities for generating novel insights into the health of patients on the basis of microbiota characterizations from intestinal, hepatic or extraintestinal samples. Alterations in gut microbiota composition correlate with intestinal and extraintestinal disease and, although only a few mechanisms are known, the microbiota are still an attractive target for developing biomarkers for disease detection and management as well as potential therapeutic applications. In this Review, we summarize the major decision points confronting new entrants to the field or for those designing new projects in microbiome research. We provide recommendations based on current technology options and our experience of sequencing platform choices. We also offer perspectives on future applications of microbiome research, which we hope convey the promise of this technology for clinical applications.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Rapid improvements in sequencing technology have facilitated the development of two techniques that are integral to answering these questions: 16S sequencing and whole genome shotgun sequencing (Claesson et al., 2017).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Claesson et al., 2017
In the citing paper
“The large intestine is thus an important host site for microbial metabolism, a convenient truth that fortunately aligns with our reliance on the analysis of stool samples to gain insights into our microbial inhabitants (Fraher et al., 2012;Claesson et al., 2017).”
From Gut reactions: Breaking down xenobiotic–microbiome interactions (2019) · cites this paper as Claesson et al., 2017
Citations
Cites
Items 201–210 of 210
OTUbase: an R infrastructure package for operational taxonomic unit data
Beck, D., Settles, M. L., & Foster, J. A. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr196 · Cited by 20
Ander, C., Schulz-Trieglaff, O. B., Stoye, J., et al. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-s5-s2 · Cited by 19
MetaCAA: A clustering-aided methodology for efficient assembly of metagenomic datasets
Reddy, R. M., Mohammed, M. H., & Mande, S. S. (2014) · Genomics · doi:10.1016/j.ygeno.2014.02.007 · Cited by 18
FunFrame: functional gene ecological analysis pipeline
Weisman, D., Yasuda, M., & Bowen, J. L. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt123 · Cited by 15
SPANNER: taxonomic assignment of sequences using pyramid matching of similarity profiles
Porter, M. S., & Beiko, R. G. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt313 · Cited by 14
Reddy, R. M., Mohammed, M. H., & Mande, S. S. (2012) · Gene · doi:10.1016/j.gene.2012.06.014 · Cited by 13
GSTaxClassifier: a genomic signature based taxonomic classifier for metagenomic data analysis
Yu, F., Sun, Y., Liu, L., & Farmerie, W. G. (2009) · Bioinformation · doi:10.6026/97320630004046 · Cited by 13
Optimal preservation of liver biopsy samples for downstream translational applications
Sherker, A., Cherepanov, V., Alvandi, Z., et al. (2013) · Hepatology International · doi:10.1007/s12072-013-9423-6 · Cited by 11
Classification of Metagenomics Data at Lower Taxonomic Level Using a Robust Supervised Classifier
Hou, T., Liu, F., Liu, Y., et al. (2015) · Evolutionary Bioinformatics · doi:10.4137/ebo.s20523 · Cited by 5
Metaphor: Finding Bi-directional Best Hit homology relationships in (meta)genomic datasets
van der Veen, B. E., Harris, H. M. B., O’Toole, P. W., & Claesson, M. J. (2014) · Genomics · doi:10.1016/j.ygeno.2014.10.008 · Cited by 5
Self-citation
Research works printed but not linked: 1
- Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. metaSPAdes: a new versatile de novo metagenomics assembler. arXiv 1604.03071 (2016). · arXiv
Cited by
Sorted by citations
Cryan, J. F., O'Riordan, K. J., Cowan, C. S. M., Sandhu, K. V., Bastiaanssen, T. F. S., Boehme, M., Codagnone, M. G., Cussotto, S., Fulling, C., Golubeva, A. V., et al. (2019) · Physiological Reviews · doi:10.1152/physrev.00018.2018 · Cited by 5,286
Gut reactions: Breaking down xenobiotic–microbiome interactions
Clarke, G., Sandhu, K. V., Griffin, B. T., Dinan, T. G., Cryan, J. F., & Hyland, N. P. (2019) · Pharmacological Reviews · doi:10.1124/pr.118.015768 · Cited by 319
Systematic review: human gut dysbiosis induced by non-antibiotic prescription medications
Le Bastard, Q., Al‐Ghalith, G. A., Grégoire, M., Chapelet, G., Javaudin, F., Dailly, E., Batard, E., Knights, D., & Montassier, E. (2018) · Alimentary Pharmacology & Therapeutics · doi:10.1111/apt.14451 · Cited by 263
Age-dependent changes in GI physiology and microbiota: time to reconsider?
An, R., Wilms, E., Masclee, A. A. M., Smidt, H., Zoetendal, E. G., & Jonkers, D. (2018) · Gut · doi:10.1136/gutjnl-2017-315542 · Cited by 209
Cowan, C. S. M., Dinan, T. G., & Cryan, J. F. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13156 · Cited by 176
Metadata
- Authors
- Claesson, M. J., Clooney, A. G., & O'Toole, P. W.
- Affiliations
- University College Cork (IE)
- Corresponding author
- Claesson, Marcus J.
- Venue
- Nature Reviews Gastroenterology & Hepatology
- Published
- 2017-08-09
- Volume
- 14
- Issue
- 10
- Pages
- 585-595
- ISSN
- 1759-5045 (ISSN-L)
- 1759-5053
- OpenAlex
- W2743544008
- Cited by
- 153
- References
- 210
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 18 · 2023: 12 · 2022: 19 · 2021: 25 · 2020: 28 · 2019: 22 · 2018: 11 · 2017: 3
- FWCI
- 1.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Gastroenterology & Hepatology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Science Foundation Ireland
- APC Microbiome Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- microbiome analysis, gut microbiota, microbiota composition, microbiota function, biomarkers, microbiota-based therapy, intestinal diseases, extraintestinal diseases
- MeSH terms
- Gastrointestinal Microbiome, Genetic Techniques, Humans, Research Design, Computational Biology, Metagenomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
