Uniform Manifold Approximation and Projection (UMAP) Reveals Composite Patterns and Resolves Visualization Artifacts in Microbiome Data

George Armstrong; Cameron Martino; Gibraan Rahman; Antonio Gonzalez; Yoshiki Vázquez-Baeza; Gal Mishne; Rob Knight

doi:10.1128/mSystems.00691-21

mSystems (Oct 2021)

Uniform Manifold Approximation and Projection (UMAP) Reveals Composite Patterns and Resolves Visualization Artifacts in Microbiome Data

George Armstrong,
Cameron Martino,
Gibraan Rahman,
Antonio Gonzalez,
Yoshiki Vázquez-Baeza,
Gal Mishne,
Rob Knight

Affiliations

George Armstrong: Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
Cameron Martino: ORCiD; Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
Gibraan Rahman: Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
Antonio Gonzalez: Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
Yoshiki Vázquez-Baeza: Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
Gal Mishne: Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, California, USA
Rob Knight: ORCiD; Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA

DOI: https://doi.org/10.1128/mSystems.00691-21
Journal volume & issue: Vol. 6, no. 5

Abstract

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UMAP provides an additional method to visualize microbiome data. The method is extensible to any beta diversity metric used with PCoA, and our results demonstrate that UMAP can indeed improve visualization quality and correspondence with biological and technical variables of interest.

Published in mSystems

ISSN: 2379-5077 (Online)
Publisher: American Society for Microbiology
Country of publisher: United States
LCC subjects: Science: Microbiology
Website: https://journals.asm.org/journal/msystems

About the journal