Benchmarking Metagenomics Tools for Taxonomic Classification.

By S. Ye, Katherine J. Siddle, Daniel J. Park, Pardis C Sabeti. Cell, 2019

463 citations recorded by the source corpus.

Metagenomic sequencing is revolutionizing the detection and characterization of microbial species, and a wide variety of software tools are available to perform taxonomic classification of these data. The fast pace of development of these tools and the complexity of metagenomic data make it important that researchers are able to benchmark their performance. Here, we review current approaches for metagenomic analysis and evaluate the performance of 20 metagenomic classifiers using simulated and experimental datasets. We describe the key metrics used to assess performance, offer a framework for the comparison of additional classifiers, and discuss the future of metagenomic data analysis.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/873d2ae67ee0db53e5a671de22a7e8cf28ef2ce3

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Citations in the corpus

A practical guide to amplicon and metagenomic analysis of microbiome data (2020, methodology): “For a review about benchmarking 20 tools of taxonomic classi ﬁ cation, please see Ye et al. (2019).”
Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2020, methodology): “These three profiling tools have consistently been shown to outperform other methods across multiple evaluations (McIntyre et al., 2017; Meyer et al., 2019; Milanese et al., 2019; Sczyrba et al., 2017; Truong et al., 2015; Ye et al., 2019) .”
IDseq—An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring (2020, unknown): “IDseq analysis of unambiguously mapped datasets A recent study evaluated the performance of 20 taxonomic classifiers for mNGS data on 10 reference datasets that are commonly used for benchmarking, containing computationally simulated reads from between 12 and 525 bacterial species [46].”