Multiple Testing of Mix‐and‐Match Feature Sets in Multi‐Omics

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Authors: Mitra Ebrahimpoor, Renee Xavier de Menezes, Ningning Xu, Jelle J. Goeman
Cited by: 1
References: 33

Abstract

Integrated analysis of multi-omics datasets holds great promise for uncovering complex biological processes. However, the large dimensionality of omics data poses significant interpretability and multiple testing challenges. Simultaneous enrichment analysis (SEA) was introduced to address these issues in single-omics analysis, providing an in-built multiple testing correction and enabling simultaneous feature set testing. In this article, we introduce OCEAN, an extension of SEA to multi-omics data. OCEAN is a flexible approach to analyze potentially all possible two-way feature sets from any pair of genomics datasets. We also propose two new error rates which are in line with the two-way structure of the data and facilitate interpretation of the results. The power and utility of OCEAN are demonstrated by analyzing copy number and gene expression data for breast and colon cancer.

Fields of Study & Subjects

Genomic variations and chromosomal abnormalities Gene expression and cancer classification Bioinformatics and Genomic Networks

Publication details

Journal / source
Statistics in Medicine
Publisher
Wiley
Volume
45
Issue
1-2
Pages
e70367–e70367
Publication date
1 January 2026
Language
EN