Surveys of environmental microbial communities using metagenomic approach produce vast volumes of multidimensional data regarding the phylogenetic and functional composition of the microbiota. Faced with such complex data, a metagenomic researcher needs to select the means for data analysis properly. Data visualization became an indispensable part of the exploratory data analysis and serves a key to the discoveries. While the molecular-genetic analysis of even a single bacterium presents multiple layers of data to be properly displayed and perceived, the studies of microbiota are significantly more challenging. Here we present a review of the state-of-art methods for the visualization of metagenomic data in a multi-level manner: from the methods applicable to an in-depth analysis of a single metagenome to the techniques appropriate for large-scale studies containing hundreds of environmental samples.

中文翻译：

---

宏基因组数据可视化和分析方法。

使用宏基因组方法对环境微生物群落进行调查产生了大量关于微生物群的系统发育和功能组成的多维数据。面对如此复杂的数据，宏基因组研究人员需要正确选择数据分析的手段。数据可视化成为探索性数据分析不可或缺的一部分，是发现的关键。虽然即使是对单个细菌的分子遗传学分析也提供了要正确显示和感知的多层数据，但对微生物群的研究却更具挑战性。在这里，我们回顾了以多层次方式可视化宏基因组数据的最新方法：