ANANSE

ANANSE infers enhancer-based gene regulatory networks (GRNs) and predicts key transcription factors that control cell fate transitions.

Key Features:

• Enhancer-Based Network Inference: Uses enhancer-encoded regulatory information to construct gene regulatory networks.
• Transcription Factor Binding Prediction: Predicts genome-wide transcription factor binding profiles by integrating enhancer activity and known transcription factor binding motifs.
• Cell Type-Specific GRN Construction: Constructs gene regulatory networks tailored to individual cell types using inferred binding profiles.
• Identification of Key Transcription Factors: Identifies transcription factors that control cell fate transitions by analyzing differential networks between cell types.
• Performance Superiority: Demonstrated improved prediction of major transcription factors for trans-differentiation compared to existing approaches.
• Application to Human Tissues: Applied to define an atlas of key transcription factors across 18 normal human tissues.

Scientific Applications:

• Cell Fate Determination Studies: Identifies transcription factors and regulatory interactions underlying cell differentiation and identity.
• Trans-differentiation Research: Pinpoints transcription factors predicted to be sufficient for converting one cell type into another.
• Gene Regulatory Network Analysis: Provides GRNs based on enhancer activity for studying complex transcriptional regulation.

Methodology:

Integrates enhancer activity data with known transcription factor binding motifs to predict genome-wide TF binding profiles, constructs cell type-specific GRNs from these profiles, and compares GRNs across cell types to identify differential interactions and predict key transcription factors.