Cauchy combination test: a powerful test with analytic p-value calculation under arbitrary dependency structures.

ABSTRACT: Combining individual p-values to aggregate multiple small effects has a long-standing interest in statistics, dating back to the classic Fisher's combination test. In modern large-scale data analysis, correlation and sparsity are common features and efficient computation is a necessary requirement for dealing with massive data. To overcome these challenges, we propose a new test that takes advantage of the Cauchy distribution. Our test statistic has a simple form and is defined as a weighted sum of Cauchy transformation of individual p-values. We prove a non-asymptotic result that the tail of the null distribution of our proposed test statistic can be well approximated by a Cauchy distribution under arbitrary dependency structures. Based on this theoretical result, the p</

SUBMITTER: Liu Y 

PROVIDER: S-EPMC7531765 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature