The study of microbial communities crucially relies on the comparison of metagenomic next-generation sequencing data sets, for which several methods have been designed in recent years. Here, we review three key challenges in the comparison of such data sets: species identification and quantification, the efficient computation of distances between metagenomic samples and the identification of metagenomic features associated with a phenotype such as disease status. We present current solutions for such challenges, considering both reference-based methods relying on a database of reference genomes and reference-free methods working directly on all sequencing reads from the samples.

中文翻译：

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微生物组样本的比较：方法和计算挑战。

微生物群落的研究主要依赖于宏基因组下一代测序数据集的比较，近年来为此设计了几种方法。在这里，我们回顾了此类数据集比较中的三个关键挑战：物种识别和量化、宏基因组样本之间距离的有效计算以及与疾病状态等表型相关的宏基因组特征的识别。我们针对此类挑战提出了当前的解决方案，同时考虑了依赖于参考基因组数据库的基于参考的方法和直接对样本的所有测序读数工作的无参考方法。