Brief Bioinform. 2019 Jul 19;20(4):1125-1136. doi: 10.1093/bib/bbx120.
Microbiome research has grown rapidly over the past decade, with a proliferation of new methods that seek to make sense of large, complex data sets. Here, we survey two of the primary types of methods for analyzing microbiome data: read classification and metagenomic assembly, and we review some of the challenges facing these methods. All of the methods rely on public genome databases, and we also discuss the content of these databases and how their quality has a direct impact on our ability to interpret a microbiome sample.
过去十年间，微生物组研究发展迅速，新方法层出不穷，旨在从大量复杂的数据集里找到规律。在这里，我们调查了两种主要的微生物组数据分析方法：读分类和宏基因组组装，并回顾了这些方法所面临的一些挑战。所有的方法都依赖于公共基因组数据库，我们还讨论了这些数据库的内容，以及它们的质量如何直接影响我们解读微生物组样本的能力。
