Lagkouvardos Ilias, Fischer Sandra, Kumar Neeraj, Clavel Thomas
ZIEL-Core Facility Microbiome/NGS, Technical University of Munich , Freising , Germany.
PeerJ. 2017 Jan 11;5:e2836. doi: 10.7717/peerj.2836. eCollection 2017.
The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of sequencing datasets can choose among a range of multipurpose software platforms, the use of which can be intimidating for non-expert users. Among available pipeline options for high-throughput 16S rRNA gene analysis, the R programming language and software environment for statistical computing stands out for its power and increased flexibility, and the possibility to adhere to most recent best practices and to adjust to individual project needs. Here we present the Rhea pipeline, a set of R scripts that encode a series of well-documented choices for the downstream analysis of Operational Taxonomic Units (OTUs) tables, including normalization steps, - and -diversity analysis, taxonomic composition, statistical comparisons, and calculation of correlations. Rhea is primarily a straightforward starting point for beginners, but can also be a framework for advanced users who can modify and expand the tool. As the community standards evolve, Rhea will adapt to always represent the current state-of-the-art in microbial profiles analysis in the clear and comprehensive way allowed by the R language. Rhea scripts and documentation are freely available at https://lagkouvardos.github.io/Rhea.
16S rRNA基因扩增子图谱对于理解微生物在各种环境中的影响至关重要,再加上测序成本的大幅降低,导致微生物测序项目激增。越来越多希望利用测序数据集的科学家和临床医生可以在一系列多用途软件平台中进行选择,而这些软件平台的使用可能会让非专业用户望而却步。在用于高通量16S rRNA基因分析的现有流程选项中,用于统计计算的R编程语言和软件环境因其强大的功能、更高的灵活性以及遵循最新最佳实践并根据个别项目需求进行调整的可能性而脱颖而出。在这里,我们展示了Rhea流程,这是一组R脚本,它们为操作分类单元(OTU)表的下游分析编码了一系列有详细记录的选择,包括标准化步骤、α多样性和β多样性分析、分类组成、统计比较以及相关性计算。Rhea主要是初学者的一个直接起点,但对于可以修改和扩展该工具的高级用户来说,它也可以成为一个框架。随着社区标准的发展,Rhea将始终以R语言所允许的清晰、全面的方式进行调整,以代表微生物图谱分析的当前最新技术水平。Rhea脚本和文档可在https://lagkouvardos.github.io/Rhea上免费获取。