Derandomizing Knockoffs
Derandomizing Knockoffs
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DOI：
10.1080/01621459.2021.1962720
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发表时间：
2020-12
影响因子：
3.7
通讯作者：
Zhimei Ren;Yuting Wei;E. Candès
中科院分区：
文献类型：
--
作者：
Zhimei Ren;Yuting Wei;E. Candès
Model-X仿制品是一种通用程序，可以利用任何特征重要性度量来产生变量选择算法，该算法在严格控制误报的数量或分数的同时发现真实效果。X型仿制品是一种随机化过程，依赖于合成（随机）变量的一次性构建。本文介绍了一种去随机化方法，通过聚合多次运行的knockoffs算法的选择结果。去随机化步骤被设计为是灵活的，并且可以适应于任何变量选择基础过程，以在不损害统计能力的情况下产生稳定的决策。当应用到基本过程的詹森和苏，我们证明，去随机化的敲除控制每个家庭的错误率（PFER）和k家庭的错误率（k-FWER）。此外，我们进行了广泛的数值研究，证明紧密的I型错误控制和显着增强的权力相比，替代变量选择算法。最后，我们将我们的方法应用于前列腺癌的多阶段全基因组关联研究，并报告与该疾病显著相关的基因组位置。当与其他研究交叉引用时，我们发现报告的关联已被复制。本文的补充材料，包括可用于复制作品的材料的标准化描述，可作为在线补充。
Abstract Model-X knockoffs is a general procedure that can leverage any feature importance measure to produce a variable selection algorithm, which discovers true effects while rigorously controlling the number or fraction of false positives. Model-X knockoffs is a randomized procedure which relies on the one-time construction of synthetic (random) variables. This article introduces a derandomization method by aggregating the selection results across multiple runs of the knockoffs algorithm. The derandomization step is designed to be flexible and can be adapted to any variable selection base procedure to yield stable decisions without compromising statistical power. When applied to the base procedure of Janson and Su, we prove that derandomized knockoffs controls both the per family error rate (PFER) and the k family-wise error rate (k-FWER). Furthermore, we carry out extensive numerical studies demonstrating tight Type I error control and markedly enhanced power when compared with alternative variable selection algorithms. Finally, we apply our approach to multistage genome-wide association studies of prostate cancer and report locations on the genome that are significantly associated with the disease. When cross-referenced with other studies, we find that the reported associations have been replicated. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.