TFEA.ChIP

TFEA.ChIP identifies transcription factor enrichment within gene sets by leveraging ChIP-Seq–derived TF–gene associations to elucidate TF-mediated regulatory signals in transcriptomic data.

Key Features:

• Database Integration: Uses a database built from ChIP-Seq experiments sourced from ENCODE and GEO linking TFs to target genes across 1075 experiments, over 150 cell types, and 327 transcription factors.
• DNase-based Correlation Mapping: Establishes TF–gene connections by correlating DNase Hypersensitive Sites across various cell lines.
• Enrichment Scoring: Computes enrichment using Fisher’s exact association test or Gene Set Enrichment Analysis (GSEA) for predefined gene sets and lists of differentially expressed genes.
• Validation and Performance: Validated on 144 gene sets representing genetic and chemical perturbations, identifying relevant TFs in 103 datasets with a median area under the curve (AUC) of 0.86.
• Comparative Analysis: RNAseq-based analyses showed that ChIP-Seq–based approaches provide greater biological context than PWM-based methods.
• Database Extensibility: Supports expansion and customization of the TF–gene database.

Scientific Applications:

• Identification of transcriptional regulators: Detects TFs likely responsible for co-regulation within gene sets derived from transcriptomic profiles.
• Analysis of genetic and chemical perturbations: Prioritizes TFs implicated in transcriptional responses to genetic or chemical treatments.
• Interpretation of transcriptomic data: Provides context-rich insights to elucidate TF-mediated regulatory networks from differential expression and RNAseq data.

Methodology:

Constructs a TF–gene database from ChIP-Seq experiments (ENCODE, GEO); links TFs to genes via correlations of DNase Hypersensitive Sites across cell lines; assesses enrichment using Fisher’s exact association test or Gene Set Enrichment Analysis (GSEA) and accepts predefined gene sets or lists of differentially expressed genes.