MODifieR

MODifieR infers disease-associated gene modules from transcriptomics-derived networks to characterize molecular interactions underlying complex diseases.

Key Features:

• Ensemble approach: Integrates nine distinct disease module inference methods into a single analytical framework.
• Transcriptomics input: Operates on transcriptomics-derived networks to detect gene modules associated with disease states.
• Standardized outputs: Produces standardized input and output formats to enable direct comparison and integration of module results.
• Result aggregation for robustness: Aggregates outputs from multiple methods to increase reliability and robustness of inferred disease modules.

Scientific Applications:

• Disease module identification: Detects gene modules critical for understanding molecular mechanisms underlying complex diseases.
• Integrated inference: Combines insights from multiple inference methods to generate more comprehensive models of disease-specific gene interactions.
• Method comparison: Facilitates comparative analysis across inference methods to assess consistency and robustness of disease network findings.

Methodology:

Uses transcriptomics data as network input; applies an ensemble of nine inference methods to identify candidate disease modules; standardizes outputs from each method to allow integration and comparison of inferred modules.