A non-randomized procedure for large-scale heterogeneous multiple discrete testing based on randomized tests.

ABSTRACT: In the analysis of next-generation sequencing technology, massive discrete data are generated from short read counts with varying biological coverage. Conducting conditional hypothesis testing such as Fisher's Exact Test at every genomic region of interest thus leads to a heterogeneous multiple discrete testing problem. However, most existing multiple testing procedures for controlling the false discovery rate (FDR) assume that test statistics are continuous and become conservative for discrete tests. To overcome the conservativeness, in this article, we propose a novel multiple testing procedure for better FDR control on heterogeneous discrete tests. Our procedure makes decisions based on the marginal critical function (MCF) of randomized tests, which enables achieving a powerful and non-

SUBMITTER: Dai X 

PROVIDER: S-EPMC6565503 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature