论文标题
全球测试的代谢组学中的途径测试，允许事后选择途径
Pathway Testing in Metabolomics with Globaltest, Allowing Post Hoc Choice of Pathways
论文作者
论文摘要
全球测试是全球无效假设的强大测试，即一组特征与感兴趣的响应之间没有关联，这在代谢组学中很受欢迎。但是，评估多个途径需要多次测试校正。在本文中，我们提出了一种基于封闭测试的多个测试方法，该方法是专门为全球测试设计的。所提出的方法在所有可能的特征集上同时控制家庭错误率，因此允许事后推理，即研究人员可以在看到数据后选择途径数据库而不会损害错误控制。为了规避封闭测试的指数计算时间，我们得出了一个新颖的快捷方式，该快捷方式允许在代谢组学数据的尺度上执行精确的封闭测试。 Cran上有一个R软件包CTGT。我们说明了几个代谢组学数据示例的快捷方式。
The Globaltest is a powerful test for the global null hypothesis that there is no association between a group of features and a response of interest, which is popular in pathway testing in metabolomics. Evaluating multiple pathways, however, requires multiple testing correction. In this paper, we propose a multiple testing method, based on closed testing, specifically designed for the Globaltest. The proposed method controls the family-wise error rate simultaneously over all possible feature sets, and therefore allows post hoc inference, i.e. the researcher may choose the pathway database after seeing the data without jeopardizing error control. To circumvent the exponential computation time of closed testing, we derive a novel shortcut that allows exact closed testing to be performed on the scale of metabolomics data. An R package ctgt is available on CRAN. We illustrate the shortcut on several metabolomics data examples.
