Uniform Manifold Approximation and Projection (UMAP) Reveals Composite Patterns and Resolves Visualization Artifacts in Microbiome Data
George Armstrong, Cameron Martino, Gibraan Rahman, Antonio González, Yoshiki Vázquez‐Baeza, Gal Mishne, Rob Knight
Abstract
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. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/knightlab-analyses/umap-microbiome-benchmarking; additionally, we have provided a QIIME 2 plugin for UMAP at https://github.com/biocore/q2-umap.
Topics & Concepts
VisualizationProjection (relational algebra)MicrobiomeNonlinear dimensionality reductionManifold (fluid mechanics)Data visualizationComputer scienceArtificial intelligenceBiologyAlgorithmBioinformaticsEngineeringDimensionality reductionMechanical engineeringGut microbiota and healthBioinformatics and Genomic NetworksGene expression and cancer classification