Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold

• Published in: PloS one Vol. 17; no. 2; p. e0264443
• Main Authors: Chiarello, Marlène, McCauley, Mark, Villéger, Sébastien, Jackson, Colin R.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 24.02.2022; Public Library of Science (PLoS)
• Subjects: Animals; Bacteriology; Bias; Biodiversity; Biodiversity and Ecology; Biological diversity; Biology; Biology and Life Sciences; Bivalvia - microbiology; Cluster Analysis; Clustering; Computer and Information Sciences; Data Analysis; Data mining; Data processing; Datasets; Datasets as Topic; Diversity indices; DNA, Bacterial; Earth Sciences; Ecological effects; Ecology and Environmental Sciences; Environmental Sciences; Fluvial sediments; Freshwater invertebrates; Gastrointestinal Microbiome; Genera; Genetic aspects; Genetic Variation; Identification and classification; Invertebrates - microbiology; Life Sciences; Methods; Microbial populations; Microbiological research; Microbiology and Parasitology; Microorganisms; Mollusks; Noise reduction; Phylogenetics; Pipelines; Production methods; Quantitative Methods; Rarefaction; Ribosomal RNA; Rivers; Rivers - microbiology; RNA, Ribosomal, 16S - genetics; rRNA 16S; Sediments; Sequence Analysis, DNA; Seston; Taxonomy; France; United States > US; Water; Millions; Unifrac; Sequences; Gene database; Dynamics; Bacteria; Index; Evenness; Community

Advances in the analysis of amplicon sequence datasets have introduced a methodological shift in how research teams investigate microbial biodiversity, away from sequence identity-based clustering (producing Operational Taxonomic Units, OTUs) to denoising methods (producing amplicon sequence variant...