Mergeomics

Mergeomics integrates multi-omics association data to identify and prioritize biological processes and regulatory network hubs perturbed in complex diseases.

Key Features:

• Multi-Omics Data Integration: Combines genomics, epigenomics, and transcriptomics association data across platforms and species for joint analysis.
• Identification of Perturbed Biological Processes: Detects biological processes that are disrupted in disease states using multi-omics association signals.
• Overlay on Molecular Interaction Networks: Maps identified disease-associated processes onto molecular interaction networks to pinpoint network hubs as potential key regulators.
• Versatility Across Data Types and Species: Accepts diverse datasets from different studies and species, enabling cross-platform and cross-species analyses.
• Performance Optimization and Evaluation: Performance has been optimized and evaluated with simulations and multiple independent datasets and benchmarked against alternative methods.
• Case Study Demonstrations: Applied to genome-wide, epigenome-wide, and transcriptome-wide datasets from human and mouse studies, including analyses of total cholesterol and fasting glucose.

Scientific Applications:

• Complex trait analysis: Integrates subtle, multidimensional perturbations across omics layers to study complex traits and diseases.
• Cross-species multi-omics comparison: Enables comparison and integration of human and mouse omics datasets to identify conserved disease processes.
• Prioritization of mechanistic targets: Ranks candidate biological processes and network hubs for follow-up experimental validation in translational research.
• Analysis of genome-, epigenome-, and transcriptome-wide datasets: Supports integrative analysis of genome-wide, epigenome-wide, and transcriptome-wide association results.

Methodology:

The pipeline implements independent modules: a Data Integration Module that aggregates diverse omics association data, a Process Identification Module that detects affected biological processes, and a Network Overlay Module that maps processes onto molecular interaction networks to identify regulatory hubs.