Modifying the false discovery rate procedure based on the information theory under arbitrary correlation structure and its performance in high-dimensional genomic data.

ABSTRACT:

Background

Controlling the False Discovery Rate (FDR) in Multiple Comparison Procedures (MCPs) has widespread applications in many scientific fields. Previous studies show that the correlation structure between test statistics increases the variance and bias of FDR. The objective of this study is to modify the effect of correlation in MCPs based on the information theory. We proposed three modified procedures (M1, M2, and M3) under strong, moderate, and mild assumptions based on the conditional Fisher Information of the consecutive sorted test statistics for controlling the false discovery rate under arbitrary correlation structure. The performance of the proposed procedures was compared with the Benjamini-Hochberg (BH) and Benjamini-Yekutieli (BY) procedures in simulation study an

SUBMITTER: Rastaghi S 

PROVIDER: S-EPMC10840263 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature