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Cell. 2019 Aug 8;178(4):779-794. doi: 10.1016/j.cell.2019.07.010.

Benchmarking Metagenomics Tools for Taxonomic Classification.

Author information

1
Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Electronic address: yesimon@mit.edu.
2
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Center for Systems Biology, Department of Organismal and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
3
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
4
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Center for Systems Biology, Department of Organismal and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Department of Immunology and Infectious Disease, Harvard School of Public Health, Boston, MA 02115, USA; Howard Hughes Medical Institute (HHMI), Chevy Chase, MD 20815, USA.

Abstract

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.

PMID:
31398336
DOI:
10.1016/j.cell.2019.07.010

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