Key points are not available for this paper at this time.
Datasets collected by high-throughput sequencing (HTS) of 16S rRNA gene amplimers, metagenomes or metatranscriptomes are commonplace and being used to study human disease states, ecological differences between sites, and the built environment. There is increasing awareness that microbiome datasets generated by HTS are compositional because they have an arbitrary total imposed by the instrument. However, many investigators are either unaware of this or assume specific properties of the compositional data. The purpose of this review is to alert investigators to the dangers inherent in ignoring the compositional nature of the data, and point out that HTS datasets derived from microbiome studies can and should be treated as compositions at all stages of analysis. We briefly introduce compositional data, illustrate the pathologies that occur when compositional data are analyzed inappropriately, and finally give guidance and point to resources and examples for the analysis of microbiome datasets using compositional data analysis.
Building similarity graph...
Analyzing shared references across papers
Loading...
Gregory B. Gloor
Jean M. Macklaim
Vera Pawlowsky‐Glahn
Frontiers in Microbiology
Western University
Universitat Politècnica de Catalunya
Universitat de Girona
Building similarity graph...
Analyzing shared references across papers
Loading...
Gloor et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69d777b2b4cef8fedc48feb7 — DOI: https://doi.org/10.3389/fmicb.2017.02224
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: