Nonparametric richness estimators Chao1 and ACE must not be used with amplicon sequence variant data.

ACE ASV Chao1 DADA2 OTU QIIME2 UNOISE amplicon sequence variant deblur operational taxonomic units

Journal

The ISME journal
ISSN: 1751-7370
Titre abrégé: ISME J
Pays: England
ID NLM: 101301086

Informations de publication

Date de publication:
13 Jun 2024
Historique:
received: 16 04 2024
revised: 15 05 2024
accepted: 11 06 2024
medline: 13 6 2024
pubmed: 13 6 2024
entrez: 13 6 2024
Statut: aheadofprint

Résumé

Microbial ecologists use alpha diversity metrics for estimating species richness and evenness from data obtained by high-throughput sequencing of small subunit ribosomal RNA genes. This perspective argues that the nonparametric richness estimators Chao1 and ACE should never be used with ASV data because the default process of generating amplicon sequence variants (ASVs) removes singletons, which are specifically required for these estimate calculations. In addition, retaining singletons, if/when possible, will contribute a large proportion of artifacts to this abundance category, leading to extreme richness overestimation. We recommend the use of alternative sequence clustering strategies and/or diversity metrics to avoid generating meaningless richness estimates from ASV data.

Identifiants

pubmed: 38869966
pii: 7692950
doi: 10.1093/ismejo/wrae106
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) [2024]. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.

Auteurs

Yongcui Deng (Y)

School of Geography, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, Jiangsu Province 210023, China.
Department of Biology, University of Waterloo, Waterloo, Ontario N2T 1P5, Canada.

Alexander K Umbach (AK)

Department of Biology, University of Waterloo, Waterloo, Ontario N2T 1P5, Canada.

Josh D Neufeld (JD)

Department of Biology, University of Waterloo, Waterloo, Ontario N2T 1P5, Canada.

Classifications MeSH