Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili, IISPV, Tarragona, Spain.
Metabolomics Interdisciplinary Laboratory, Department of Nutrition and Metabolism, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
Res Synth Methods. 2024 Jul;15(4):687-699. doi: 10.1002/jrsm.1713. Epub 2024 Mar 13.
Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics is significantly lower compared to other omics disciplines. Metabolomics is the study of small chemical compounds in living organisms, which provides important insights into an organism's phenotype. However, the wide variety of compounds and the different experimental methods used in metabolomics make it challenging to perform a thorough meta-analysis. Additionally, there is a lack of consensus on reporting statistical estimates, and the high number of compound naming synonyms further complicates the process. Easy-Amanida is a new tool that combines two R packages, "amanida" and "webchem", to enable meta-analysis of aggregate statistical data, like p-value and fold-change, while ensuring the compounds naming harmonization. The Easy-Amanida app is implemented in Shiny, an R package add-on for interactive web apps, and provides a workflow to optimize the naming combination. This article describes all the steps to perform the meta-analysis using Easy-Amanida, including an illustrative example for interpreting the results. The use of aggregate statistics metrics extends the use of Easy-Amanida beyond the metabolomics field.
元分析是临床研究中一种有用的工具，因为它可以结合多个临床研究的结果，在回答特定科学问题时提高精度。虽然在各种临床研究主题中使用元分析的出版物数量大幅增加，但与其他组学领域相比，代谢组学中发表的元分析数量要低得多。代谢组学是研究生物体中小分子化合物的学科，它为生物体的表型提供了重要的见解。然而，代谢组学中化合物的种类繁多，实验方法也各不相同，这使得进行全面的元分析具有挑战性。此外，在报告统计估计值方面缺乏共识，化合物命名同义词的数量众多也进一步使问题复杂化。Easy-Amanida 是一种新工具，它结合了两个 R 包，"amanida"和"webchem"，可以对聚合统计数据（如 p 值和倍数变化）进行元分析，同时确保化合物命名的协调。Easy-Amanida 应用程序是用 Shiny 实现的，Shiny 是一个用于交互式网络应用程序的 R 包附加组件，并提供了一个工作流程来优化命名组合。本文描述了使用 Easy-Amanida 进行元分析的所有步骤，包括一个解释结果的示例。聚合统计指标的使用扩展了 Easy-Amanida 在代谢组学领域之外的应用。
