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arXiv · 2310.09493

Summary Statistics Knockoffs Inference with Family-wise Error Rate Control

Catherine Xinrui Yu·Jiaqi Gu·Zhaomeng Chen·Zihuai He
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Abstract

Testing multiple hypotheses of conditional independence with provable error rate control is a fundamental problem with various applications. To infer conditional independence with family-wise error rate (FWER) control when only summary statistics of marginal dependence are accessible, we adopt GhostKnockoff to directly generate knockoff copies of summary statistics and propose a new filter to select features conditionally dependent to the response with provable FWER control. In addition, we develop a computationally efficient algorithm to greatly reduce the computational cost of knockoff copies generation without sacrificing power and FWER control. Experiments on simulated data and a real dataset of Alzheimer's disease genetics demonstrate the advantage of proposed method over the existing alternatives in both statistical power and computational efficiency.

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Catherine Xinrui Yu, Jiaqi Gu, Zhaomeng Chen, Zihuai He. 2023-10-14. Summary Statistics Knockoffs Inference with Family-wise Error Rate Control. https://arxiv.org/abs/2310.09493

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