Network-Based Pathway Enrichment Analysis with Incomplete Network Information

TL;DR

This paper introduces a new method for pathway enrichment analysis that accounts for incomplete and condition-specific network information by combining data-driven network estimation with existing biological databases.

Contribution

It proposes a constrained network estimation framework that integrates high-dimensional omics data with existing interaction databases for more accurate pathway analysis.

Findings

The method improves pathway enrichment detection accuracy.

It performs well in simulated and real data scenarios.

Theoretical properties of the estimator are established.

Abstract

Pathway enrichment analysis has become a key tool for biomedical researchers to gain insight into the underlying biology of differentially expressed genes, proteins and metabolites. It reduces complexity and provides a system-level view of changes in cellular activity in response to treatments and/or in disease states. Methods that use existing pathway network information have been shown to outperform simpler methods that only take into account pathway membership. However, despite significant progress in understanding the association amongst members of biological pathways, and expansion of data bases containing information about interactions of biomolecules, the existing network information may be incomplete or inaccurate, and is not cell-type or disease condition-specific. We propose a constrained network estimation framework that combines network estimation based on cell- and condition-specific high-dimensional Omics data with interaction information from existing data bases. The resulting pathway topology information is subsequently used to provide a framework for simultaneous testing of differences in expression levels of pathway members, as well as their interactions. We study the asymptotic properties of the proposed network estimator and the test for pathway enrichment, and investigate its small sample performance in simulated and real data settings.