PhenoGMM: Gaussian Mixture Modeling of Cytometry Data Quantifies Changes in Microbial Community Structure

Peter Rubbens; Ruben Props; Frederiek-Maarten Kerckhof; Nico Boon; Willem Waegeman

doi:10.1128/mSphere.00530-20

mSphere (Feb 2021)

PhenoGMM: Gaussian Mixture Modeling of Cytometry Data Quantifies Changes in Microbial Community Structure

Peter Rubbens,
Ruben Props,
Frederiek-Maarten Kerckhof,
Nico Boon,
Willem Waegeman

Affiliations

Peter Rubbens: ORCiD; KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
Ruben Props: Center for Microbial Ecology and Technology (CMET), Ghent University, Ghent, Belgium
Frederiek-Maarten Kerckhof: ORCiD; Center for Microbial Ecology and Technology (CMET), Ghent University, Ghent, Belgium
Nico Boon: ORCiD; Center for Microbial Ecology and Technology (CMET), Ghent University, Ghent, Belgium
Willem Waegeman: KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium

DOI: https://doi.org/10.1128/mSphere.00530-20
Journal volume & issue: Vol. 6, no. 1

Abstract

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Microorganisms are vital components in various ecosystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA.

Published in mSphere

ISSN: 2379-5042 (Online)
Publisher: American Society for Microbiology
Country of publisher: United States
LCC subjects: Science: Microbiology
Website: https://journals.asm.org/journal/msphere

About the journal