Abstract：
Microbial strains are interpreted as a lineage derived from a recent ancestor that have not experienced \"too many\" recombination events and can be successfully retrieved with culture-independent techniques using metagenomic sequencing. Such a strain variability has been increasingly shown to display additional phenotypic heterogeneities that affect host health, such as virulence, transmissibility, and antibiotics resistance. New statistical and computational methods have recently been developed to track the strains in samples based on shotgun metagenomics data either based on reference genome sequences or Metagenome-assembled genomes (MAGs). In this paper, we review some recent statistical methods for strain identifications based on frequency counts at a set of single nucleotide variants (SNVs) within a set of single-copy marker genes. These methods differ in terms of whether reference genome sequences are needed, how SNVs are called, what methods of deconvolution are used and whether the methods can be applied to multiple samples. We conclude our review with areas that require further research.
摘要：
微生物菌株被解释为来自最近的祖先的谱系，该祖先没有经历过“太多”重组事件，并且可以通过使用宏基因组测序的非培养技术成功检索。这种菌株的变异性越来越显示出影响宿主健康的额外表型异质性。如毒力，可传播性，和抗生素抗性。最近已经开发了新的统计和计算方法来基于基于参考基因组序列或宏基因组组装的基因组（MAG）的shot弹枪宏基因组学数据跟踪样品中的菌株。在本文中,我们回顾了一些最新的基于单拷贝标记基因中一组单核苷酸变异体(SNV)频率计数的菌株鉴定统计方法.这些方法在是否需要参考基因组序列方面有所不同，SNV是如何被称为，使用了哪些反卷积方法以及这些方法是否可以应用于多个样本。我们总结了需要进一步研究的领域。
