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Metabolomics Analytics Workflow for Epidemiological Research: Perspectives from the Consortium of Metabolomics Studies (COMETS)

机译:流行病学研究的代谢组学分析工作流程:代谢组学研究联合会(COMETS)的观点

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摘要

The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility.
机译:代谢组学技术在流行病学研究中的应用正在成为阐明疾病病因和发现生物标志物的新方法。但是,代谢组学数据的分析非常复杂,因此迫切需要标准化分析工作流程和报告研究结果。为了指导此类指南的制定,我们对代谢组学研究联盟(COMETS)的47个队列代表进行了调查,以了解当前用于分析全球流行病学研究中的代谢组学数据的当前策略和程序。结果表明了各种应用的分析策略,从生物样本和数据预处理以及质量控制到统计分析和研究结果的报告。这些策略包括在代谢组学界普遍使用并在流行病学研究中应用的方法,以及预处理管线和数据分析的新方法。为了解决这些差异,我们建议使用开放源代码的计划,例如基于网络的在线工具COMETS Analytics,其中包括一些有用的工具,可指导流行病学研究中的分析工作流程和代谢组学分析结果的标准化报告。最终,这将改善统计分析,研究结果和研究可重复性的质量。

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