MODalyseR

MODalyseR identifies and refines network-based disease modules and predicts hub regulators by integrating regulatory mechanisms with transcriptomics data to prioritize disease-associated genes.

Key Features:

• Disease Module Identification: Uses network-based approaches to identify clusters of interacting genes associated with specific diseases.
• Regulatory Mechanism Integration: Incorporates regulatory information to predict hub regulators within identified disease modules.
• Pipeline Integration and Extension: Builds upon and extends the functionalities of the MODifieR and ComHub packages for enhanced module analysis.
• Transcriptomics Data Utilization: Processes transcriptomics data to refine modules and prioritize disease-associated genes based on expression evidence.
• Case Study Demonstration: Applied to multiple sclerosis where it identified IKZF1 as a candidate hub regulator corroborated by independent ChIP-seq data.

Scientific Applications:

• Complex disease research: Enables analysis of diseases such as multiple sclerosis, cancer, and neurodegenerative disorders through module-centric network analysis.
• Pathogenesis discovery: Facilitates identification of gene clusters and regulators implicated in disease mechanisms.
• Therapeutic target identification: Prioritizes candidate genes and hub regulators for potential therapeutic intervention.
• Prediction of treatment outcomes and adverse effects: Supports assessment of module-level predictors relevant to treatment response and side effects.

Methodology:

Combines and extends MODifieR and ComHub components to perform network-based module inference and hub regulator prediction using transcriptomics data and integrated regulatory-mechanism information.