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Cited by 373

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Compositional analysis: a valid approach to analyze microbiome high-throughput sequencing data

Open access
Gloor, Gregory B., Reid, Gregor·2016·Canadian Journal of Microbiology

Abstract

A workshop held at the 2015 annual meeting of the Canadian Society of Microbiologists highlighted compositional data analysis methods and the importance of exploratory data analysis for the analysis of microbiome data sets generated by high-throughput DNA sequencing. A summary of the content of that workshop, a review of new methods of analysis, and information on the importance of careful analyses are presented herein. The workshop focussed on explaining the rationale behind the use of compositional data analysis, and a demonstration of these methods for the examination of 2 microbiome data sets. A clear understanding of bioinformatics methodologies and the type of data being analyzed is essential, given the growing number of studies uncovering the critical role of the microbiome in health and disease and the need to understand alterations to its composition and function following intervention with fecal transplant, probiotics, diet, and pharmaceutical agents.

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Metadata

Authors
Gloor, G. B., & Reid, G.
Venue
Canadian Journal of Microbiology
Published
2016-08
Volume
62
Issue
8
Pages
692-703
ISSN
  • 0008-4166 (ISSN-L)
  • 1480-3275
OpenAlex
W2340700016
Cited by
373
References
39
FWCI
12.94
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Compositional analysis: a valid approach to analyze microbiome high-throughput sequencing data. https://app.cochat.ai/papers/10.1139/cjm-2015-0821
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Gloor, G. B., & Reid, G. (2016). Compositional analysis: a valid approach to analyze microbiome high-throughput sequencing data. Canadian Journal of Microbiology. https://doi.org/10.1139/cjm-2015-0821

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