A Novel Sparse Compositional Technique Reveals Microbial Perturbations

Author:

Martino Cameron12,Morton James T.13,Marotz Clarisse A.1,Thompson Luke R.45ORCID,Tripathi Anupriya1,Knight Rob136,Zengler Karsten167

Affiliation:

1. Department of Pediatrics, University of California San Diego, La Jolla, California, USA

2. Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, California, USA

3. Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA

4. Department of Biological Sciences and Northern Gulf Institute, University of Southern Mississippi, Hattiesburg, Mississippi, USA

5. Ocean Chemistry and Ecosystems Division, Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, stationed at Southwest Fisheries Science Center, La Jolla, California, USA

6. Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA

7. Department of Bioengineering, University of California San Diego, La Jolla, California, USA

Abstract

By accounting for the sparse compositional nature of microbiome data sets, robust Aitchison PCA can yield high discriminatory power and salient feature ranking between microbial niches. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/DEICODE ; additionally, a QIIME 2 plugin is provided to perform this analysis at https://library.qiime2.org/plugins/q2-deicode .

Funder

HHS | National Institutes of Health

National Science Foundation

U.S. Department of Energy

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

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