Abstract：
Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results.
摘要：
Shotgun宏基因组学是一种更具成本效益的方法，用于分析环境和宿主相关的微生物群落。然而,由于微生物群的复杂性和分析它们所需的分子技术，结果的可靠性和代表性取决于现场，实验室,和采用的生物信息学程序。这里,我们考虑了15个对下游生物信息学和统计数据处理产生重大影响的现场和实验室问题，以及结果解释，在细菌猎枪宏基因组研究中。我们考虑的问题包括样品的固有性质，研究设计，和实验室处理策略。我们确定了现场和实验室步骤与下游分析程序的联系，解释检测潜在陷阱的方法，并提出缓解措施，以克服或最小化它们在宏基因组研究中的影响。我们预计我们的指导方针将帮助数据科学家适当地处理和解释他们的数据。同时帮助现场和实验室研究人员实施策略以提高生成结果的质量。
