MOMA

MOMA implements the inference of candidate master regulator proteins from multi-omics data, together with ancillary analysis and visualization functions.

Key Features:

• Master Regulator Inference: Implements the MOMA algorithm to identify candidate master regulator proteins from multi-omics data.
• Ancillary Analysis Functions: Provides additional analytical functions to support the interpretation of multi-omics data.
• Visualization Functions: Includes functions for visualizing results from the master regulator analysis.

Scientific Applications:

• Multi-Omics Integration: Enables the integration of multiple omics data types to infer protein-level master regulators.
• Regulatory Network Analysis: Supports the identification of key regulatory proteins that may drive cellular phenotypes from complex omics datasets.

Methodology:

The MOMA algorithm infers candidate master regulator proteins from multi-omics data.