cosmosR

cosmosR integrates phosphoproteomics, transcriptomics, and metabolomics datasets based on prior knowledge of signaling, metabolic, and gene regulatory networks to estimate activities of transcription factors and kinases and derive network-level causal reasoning.

Key Features:

• Multi-omics integration: Integrates phosphoproteomics, transcriptomics, and metabolomics datasets using prior knowledge networks.
• Activity estimation: Estimates the activities of transcription factors and kinases from multi-omics data.
• Causal reasoning: Finds network-level causal reasoning to connect molecular observations across omics layers.
• Mechanistic hypothesis generation: Provides mechanistic hypotheses for experimental observations across multi-omics datasets.

Scientific Applications:

• Multi-omics data analysis: Analyzes phosphoproteomics, transcriptomics, and metabolomics data in a unified network framework.
• Signaling network inference: Infers signaling, metabolic, and gene regulatory network relationships from prior knowledge.
• Regulatory activity prediction: Predicts transcription factor and kinase activities from integrated omics measurements.

Methodology:

COSMOS uses prior knowledge of signaling, metabolic, and gene regulatory networks to integrate multi-omics datasets and perform network-level causal reasoning.