EPEE

EPEE infers differential transcription factor (TF) activity from gene expression data using multivariate modeling and context-specific TF–gene regulatory networks.

Key Features:

• Multivariate TF Activity Modeling: Uses a single multivariate model to jointly estimate activities of multiple transcription factors with overlapping regulons.
• Context-Specific Regulatory Networks: Incorporates TF–gene regulatory networks specific to biological context to improve TF activity inference.
• Resolution of Coupled Regulons: Accounts for coupling among transcription factors that share target genes to resolve overlapping regulatory effects.
• Flexible Target Regulation Modeling: Models different regulatory effects of a transcription factor across its target genes, capturing influences such as co-activators or repressors.

Scientific Applications:

• Regulatory Genomics Analysis: Infers transcription factor activity from gene expression datasets.
• Differential Regulatory Activity Studies: Identifies transcription factor perturbations across biological conditions.
• Functional Genomics Research: Investigates regulatory mechanisms in biological contexts such as immunology, cancer, and hematopoiesis.

Methodology:

EPEE integrates gene expression data with context-specific TF–gene regulatory networks and applies a multivariate model to simultaneously estimate transcription factor activities while accounting for overlapping regulons.