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
Read online
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.
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