OCEAN: Flexible Feature Set Aggregation for Analysis of Multi-omics Data

arXiv (Cornell University)

Abstract

Integrated analysis of multi-omics datasets holds great promise for uncovering complex biological processes. However, the large dimension 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 paper, 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 is demonstrated by analyzing copy number and gene expression data for breast and colon cancer.

Authors 4

1. Mitra Ebrahimpoor
2. Renée X. de Menezes
   Affiliation as printed

   Biostatistics Centre , Department of Psychosocial Research and Epidemiology , Netherlands Cancer Institute , Amsterdam , The Netherlands

3. Ningning Xu Aachen Department of Biomedical Data Sciences

   Leiden University Medical Center

   Affiliation as printed

   Department of Biomedical Data Sciences , Leiden University Medical Center , Leiden , The Netherlands

4. Jelle J. Goeman Aachen Department of Biomedical Data Sciences

   Leiden University Medical Center

   Affiliation as printed

   Department of Biomedical Data Sciences , Leiden University Medical Center , Leiden , The Netherlands