Shotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via theud Python Package Indexud and onud GitHubud and can be embedded into metagenome analysis workflows and programs.
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机译：gun弹枪的微生物群落宏基因组学揭示了有关在医学，生物技术和生态学中应用的相关菌株的信息。由于基础生物学系统和技术因素的复杂性，恢复它们的基因组是关键但非常具有挑战性的步骤。微生物群落是异质的，通常存在数百个来自不同物种或品系的当前基因组，它们的丰度各不相同，并且彼此之间和参考数据的相似程度不同。我们提供了一种用于基因组恢复和分析的通用概率模型，该模型汇总了通常用于从元基因组中进行基因组恢复的三种类型的信息。作为潜在的应用，我们展示了元基因组重叠群分类，基因组样品富集和基因组箱比较。开源实现MGLEX可通过 ud Python包索引 ud和on ud GitHub ud获得，并可嵌入到元基因组分析工作流程和程序中。
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