August 2022 Detecting multiple replicating signals using adaptive filtering procedures
Jingshu Wang, Lin Gui, Weijie J. Su, Chiara Sabatti, Art B. Owen
Author Affiliations +
Ann. Statist. 50(4): 1890-1909 (August 2022). DOI: 10.1214/21-AOS2139


Replicability is a fundamental quality of scientific discoveries: we are interested in those signals that are detectable in different laboratories, different populations, across time etc. Unlike meta-analysis which accounts for experimental variability but does not guarantee replicability, testing a partial conjunction (PC) null aims specifically to identify the signals that are discovered in multiple studies. In many contemporary applications, for example, comparing multiple high-throughput genetic experiments, a large number M of PC nulls need to be tested simultaneously, calling for a multiple comparisons correction. However, standard multiple testing adjustments on the M PC p-values can be severely conservative, especially when M is large and the signals are sparse. We introduce AdaFilter, a new multiple testing procedure that increases power by adaptively filtering out unlikely candidates of PC nulls. We prove that AdaFilter can control FWER and FDR as long as data across studies are independent, and has much higher power than other existing methods. We illustrate the application of AdaFilter with three examples: microarray studies of Duchenne muscular dystrophy, single-cell RNA sequencing of T cells in lung cancer tumors and GWAS for metabolomics.

Funding Statement

Jingshu Wang and Lin Gui were supported by the National Science Foundation under grant DMS-2113646. Art B. Owen was supported by the National Science Foundation under grants IIS-1837931 and DMS-1521145. Chiara Sabatti was supported by the National Institutes of Health under grants R01MH101782 and U01HG007419.


We thank Y. Benjamini, M. Bogomolov, R. Heller and N. R. Zhang for helpful discussions.


Download Citation

Jingshu Wang. Lin Gui. Weijie J. Su. Chiara Sabatti. Art B. Owen. "Detecting multiple replicating signals using adaptive filtering procedures." Ann. Statist. 50 (4) 1890 - 1909, August 2022.


Received: 1 June 2020; Revised: 1 September 2021; Published: August 2022
First available in Project Euclid: 25 August 2022

Digital Object Identifier: 10.1214/21-AOS2139

Primary: 62J15
Secondary: 62P10

Keywords: composite null , high-throughput experiments , Meta-analysis , Multiple hypotheses testing , simultaneous signals

Rights: Copyright © 2022 Institute of Mathematical Statistics


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Vol.50 • No. 4 • August 2022
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