ArticleNPJ biofilms and microbiomes2016
A perspective on 16S rRNA operational taxonomic unit clustering using sequence similarity.
Article in NPJ biofilms and microbiomes, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 131 papers, 1 of them a synthesis that pooled it.
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Who cites it
131 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Gut Microbiome in Psychosis From Mice to Men: A Systematic Review of Preclinical and Clinical Studies.Frontiers in psychiatry · 2020Pooled it
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- Use of MALDI-TOF mass spectrometry for identification of Weissella tructae.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026Article
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71 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The standard pipeline for 16S amplicon analysis starts by clustering sequences within a percent sequence similarity threshold (typically 97%) into 'Operational Taxonomic Units' (OTUs). From each OTU, a single sequence is selected as a representative. This representative sequence is annotated, and that annotation is applied to all remaining sequences within that OTU. This perspective paper will discuss the known shortcomings of this standard approach using results obtained from the Human Microbiome Project. In particular, we will show that the traditional approach of using pairwise sequence alignments to compute sequence similarity can result in poorly clustered OTUs. As OTUs are typically annotated based upon a single representative sequence, poorly clustered OTUs can have significant impact on downstream analyses. These results suggest that we need to move beyond simple clustering techniques for 16S analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.