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Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin

Open access
Bokulich, Nicholas A., Kaehler, Benjamin D., Rideout, Jai Ram, Dillon, Matthew, Bolyen, Evan, Knight, Rob, Huttley, Gavin A., Gregory Caporaso, J.·2018·Microbiome
DOI 10.1186/s40168-018-0470-z
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Abstract

BACKGROUND: Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. RESULTS: We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). CONCLUSIONS: Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

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Metadata

Authors
Bokulich, N. A., Kaehler, B. D., Rideout, J. R., Dillon, M., Bolyen, E., Knight, R., Huttley, G. A., & Gregory Caporaso, J.
Venue
Microbiome
Publisher
Springer Science and Business Media LLC
Published
2018-05-17
Volume
6
Issue
1
Pages
90-90
ISSN
2049-2618 (ISSN-L)
DOI
10.1186/s40168-018-0470-z
OpenAlex
W2807194798
Cited by
5,881
References
6
FWCI
99.51
Type
journal article
Language
en
Open access
gold
Licence
creativecommons.org/licenses/by/4.0/ (tdm)

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CoChat. (2026). Citation check: Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. https://app.cochat.ai/papers/10.1186/s40168-018-0470-z
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Bokulich, N. A., Kaehler, B. D., Rideout, J. R., Dillon, M., Bolyen, E., Knight, R., Huttley, G. A., & Gregory Caporaso, J. (2018). Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. https://doi.org/10.1186/s40168-018-0470-z

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