Optimal detection of weak positive latent dependence between two sequences of multiple tests

JOURNAL OF MULTIVARIATE ANALYSIS

卷:160

Article

Zhao, Sihai Dave¹  Cai, T. Tony²  Li, Hongzhe³ 

[1] Univ Illinois, Dept Stat, Urbana, IL 61801 USA

[2] Univ Penn, Wharton Sch, Dept Stat, Philadelphia, PA 19104 USA

[3] Univ Penn, Dept Biostat & Epidemiol, Perelman Sch Med, Philadelphia, PA 19104 USA

关键词: Detection boundary;    Higher criticism;    Independence testing;    Optimal adaptivity;    Sparsity;   

DOI  :  10.1016/j.jmva.2017.06.009

来源: Elsevier

【 摘 要 】

It is frequently of interest to jointly analyze two paired sequences of multiple tests. This paper studies the problem of detecting whether there are more pairs of tests that are significant in both sequences than would be expected by chance. The asymptotic detection boundary is derived in terms of parameters such as the sparsity of non-null cases in each sequence, the effect sizes of the signals, and the magnitude of the dependence between the two sequences. A new test for detecting weak dependence is also proposed, shown to be asymptotically adaptively optimal, studied in simulations, and applied to study genetic pleiotropy in 10 pediatric autoimmune diseases. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

Free