Best practices for analysing microbiomes.

Autor: Knight R; Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu.; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu.; Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA. robknight@ucsd.edu., Vrbanac A; Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA., Taylor BC; Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA., Aksenov A; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA., Callewaert C; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.; Center for Microbial Ecology and Technology, Ghent University, Ghent, Belgium., Debelius J; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA., Gonzalez A; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA., Kosciolek T; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA., McCall LI; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA., McDonald D; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA., Melnik AV; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA., Morton JT; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.; Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA., Navas J; Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA., Quinn RA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA., Sanders JG; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA., Swafford AD; Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA., Thompson LR; Department of Biological Sciences and Northern Gulf Institute, University of Southern Mississippi, Hattiesburg, MS, USA.; Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, stationed at Southwest Fisheries Science Center, National Marine Fisheries Service, La Jolla, CA, USA., Tripathi A; Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA., Xu ZZ; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA., Zaneveld JR; Division of Biological Sciences, School of Science Technology Engineering and Math, University of Washington Bothell, Bothell, WA, USA., Zhu Q; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA., Caporaso JG; Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA., Dorrestein PC; Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA.; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.; Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Jazyk: angličtina
Zdroj: Nature reviews. Microbiology [Nat Rev Microbiol] 2018 Jul; Vol. 16 (7), pp. 410-422.
DOI: 10.1038/s41579-018-0029-9
Abstrakt: Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.
Databáze: MEDLINE
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