Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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.
Cell. 2019 Aug 8;178(4):779-794. doi: 10.1016/j.cell.2019.07.010.
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.
宏基因组测序正在彻底改变微生物物种的检测和特征描述，并且有各种各样的软件工具可用于对这些数据进行分类学分类。这些工具的快速发展和宏基因组数据的复杂性使得研究人员能够对其性能进行基准测试变得非常重要。在这里，我们回顾了当前的宏基因组分析方法，并使用模拟和实验数据集评估了 20 种宏基因组分类器的性能。我们描述了用于评估性能的关键指标，为比较其他分类器提供了一个框架，并讨论了宏基因组数据分析的未来。
Microbiome. 2017-1-19
Genome Res. 2020-8
Genome Biol. 2017-9-21
BMC Bioinformatics. 2022-12-13
BMC Bioinformatics. 2020-7-28
Antonie Van Leeuwenhoek. 2025-8-22
NAR Genom Bioinform. 2025-7-17
NAR Genom Bioinform. 2025-7-4
Front Cell Infect Microbiol. 2025-6-17
Nat Rev Genet. 2019-6
Nat Commun. 2019-3-4
Genome Biol. 2019-3-4
Nature. 2019-2-11
Nat Biotechnol. 2019-2-4
Zotero 插件