Benchmarking Metagenomics Tools for Taxonomic Classification
Author(s) -
Simon H. Ye,
Katherine J. Siddle,
Daniel J. Park,
Pardis C. Sabeti
Publication year - 2019
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2019.07.010
Subject(s) - biology , benchmarking , metagenomics , biological classification , computational biology , data science , evolutionary biology , genetics , computer science , gene , marketing , business
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.
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