Molecular & Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
BMC Bioinformatics. 2012;13 Suppl 13(Suppl 13):S11. doi: 10.1186/1471-2105-13-S13-S11. Epub 2012 Aug 24.
BACKGROUND: Microbial metagenomic analyses rely on an increasing number of publicly available tools. Installation, integration, and maintenance of the tools poses significant burden on many researchers and creates a barrier to adoption of microbiome analysis, particularly in translational settings. METHODS: To address this need we have integrated a rich collection of microbiome analysis tools into the Genboree Microbiome Toolset and exposed them to the scientific community using the Software-as-a-Service model via the Genboree Workbench. The Genboree Microbiome Toolset provides an interactive environment for users at all bioinformatic experience levels in which to conduct microbiome analysis. The Toolset drives hypothesis generation by providing a wide range of analyses including alpha diversity and beta diversity, phylogenetic profiling, supervised machine learning, and feature selection. RESULTS: We validate the Toolset in two studies of the gut microbiota, one involving obese and lean twins, and the other involving children suffering from the irritable bowel syndrome. CONCLUSIONS: By lowering the barrier to performing a comprehensive set of microbiome analyses, the Toolset empowers investigators to translate high-volume sequencing data into valuable biomedical discoveries.
背景:微生物宏基因组分析依赖于越来越多的公开工具。这些工具的安装、集成和维护给许多研究人员带来了巨大的负担,也为微生物组分析的采用设置了障碍,特别是在转化研究环境中。
方法:为了满足这一需求,我们将丰富的微生物组分析工具集成到 Genboree 微生物组工具集中,并通过 Genboree Workbench 以软件即服务(SaaS)模型向科学界公开这些工具。Genboree 微生物组工具集为具有不同生物信息学经验水平的用户提供了一个交互式环境,用于进行微生物组分析。该工具集通过提供广泛的分析,包括 alpha 多样性和 beta 多样性、系统发育分析、有监督机器学习和特征选择,驱动假设生成。
结果:我们在两项肠道微生物组研究中验证了该工具集,其中一项涉及肥胖和瘦素双胞胎,另一项涉及患有肠易激综合征的儿童。
结论:通过降低执行全面微生物组分析的门槛,该工具集使研究人员能够将高通量测序数据转化为有价值的生物医学发现。
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