Park Sung Yong, Nanda Sayan, Faraci Gina, Park Younghu, Lee Ha Youn
Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
J Biomed Inform. 2019;100S:100040. doi: 10.1016/j.yjbinx.2019.100040. Epub 2019 Apr 15.
Microbiome profiling holds great promise for the development of novel disease biomarkers and therapeutics. Next-generation sequencing is currently the preferred method for microbiome data collection and multiple standardized tools, packages, and pipelines have been developed for the purpose of raw data processing and microbial annotation. However, these currently available pipelines come with entry-level barriers such as high-performance hardware, software installation, and sequential command-line scripting that often deter end-users. We thus created Cloud Computing for Microbiome Profiling (CCMP, https://ccmp.usc.edu), a public cloud-based web tool which combines the analytical power of current microbiome analysis platforms with a user-friendly interface. CCMP is a free-of-charge software-as-a-service (SaaS) that simplifies user experience by enabling users to complete their analysis in a single step, uploading raw sequencing data files. Once users upload 16S ribosomal RNA gene sequence data, our pipeline performs taxonomic annotation, abundance profiling, and statistical tests to report microbiota signatures altered by diseases or experimental conditions. CCMP took a 125 gigabyte (GB) input of 16S ribosomal RNA gene sequence data from 1052 specimens in FASTQ format and reported figures and tables of taxonomic annotations, statistical tests, α and β diversity calculations, and principal coordinate analyses within 21 h. CCMP is the first fully-automated web interface that integrates three key solutions for large-scale data analysis: cloud computing, fast file transfer technology, and microbiome analysis tools. As a reliable platform that supplies consistent microbiome analysis, CCMP will advance microbiome research by making effortful bioinformatics easily accessible to public.
微生物组分析在新型疾病生物标志物和治疗方法的开发方面具有巨大潜力。下一代测序是目前微生物组数据收集的首选方法，并且已经开发了多种标准化工具、软件包和流程用于原始数据处理和微生物注释。然而，这些现有的流程存在入门障碍，例如高性能硬件、软件安装以及顺序命令行脚本编写，这常常阻碍终端用户。因此，我们创建了微生物组分析云计算平台（CCMP，https://ccmp.usc.edu），这是一个基于公共云的网络工具，它将当前微生物组分析平台的分析能力与用户友好界面相结合。CCMP是一种免费的软件即服务（SaaS），通过允许用户上传原始测序数据文件，一步完成分析，从而简化了用户体验。一旦用户上传16S核糖体RNA基因序列数据，我们的流程就会进行分类注释、丰度分析和统计测试，以报告因疾病或实验条件而改变的微生物群特征。CCMP以FASTQ格式接收了来自1052个样本的125吉字节（GB）的16S核糖体RNA基因序列数据，并在21小时内报告了分类注释、统计测试、α和β多样性计算以及主坐标分析的图表。CCMP是第一个集成了大规模数据分析三个关键解决方案的全自动网络界面：云计算、快速文件传输技术和微生物组分析工具。作为一个提供一致微生物组分析的可靠平台，CCMP将通过使费力的生物信息学易于公众使用来推动微生物组研究。
