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Evaluating and Optimizing the Performance of Software Commonly Used for the Taxonomic Classification of DNA Sequence Data

Journal article
Authors Rodney T Richardson
Johan Bengtsson-Palme
Reed M Johnson
Published in Molecular Ecology Resources
Volume 17
Issue 4
Pages 760–769
ISSN 1755-098X
Publication year 2017
Published at Centre for antibiotic resistance research, CARe
Institute of Biomedicine, Department of Infectious Medicine
Pages 760–769
Language en
Links doi.org/10.1111/1755-0998.12628
Keywords RTAX, UTAX, DNA Barcoding, DNA Metabarcoding, RDP Naïve Bayesian Classifier, Taxonomic Assignment
Subject categories Bioinformatics and Systems Biology, Biological Systematics


The taxonomic classification of DNA sequences has become a critical component of numerous ecological research applications; however, few studies have evaluated the strengths and weaknesses of commonly used sequence classification approaches. Further, the methods and software available for sequence classification are diverse, creating an environment in which it may be difficult to determine the best course of action and the tradeoffs made using different classification approaches. Here, we provide an in silico evaluation of three DNA sequence classifiers, the RDP Naïve Bayesian Classifier, RTAX and UTAX. Further, we discuss the results, merits and limitations of both the classifiers and our method of classifier evaluation. Our methods of comparison are simple, yet robust, and will provide researchers a methodological and conceptual foundation for making such evaluations in a variety of research situations. Generally, we found a considerable trade-off between accuracy and sensitivity for the classifiers tested, indicating a need for further improvement of sequence classification tools.

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