Cistrome-GO

Cistrome-GO performs functional enrichment analysis of transcription factor ChIP-seq peaks by implementing the BETA method to integrate ChIP-seq peak data with differential gene expression (DGE) to identify genes directly regulated by transcription factors and annotate their biological roles.

Key Features:

• BETA method: Implements the BETA algorithm for integrating binding evidence with regulatory impact.
• ChIP-seq peak analysis: Analyzes transcription factor ChIP-seq peaks and focuses on transcription factor binding sites.
• Integration with DGE: Integrates ChIP-seq peak data with differential gene expression (DGE) to identify directly regulated genes.
• Functional enrichment/ontology analysis: Performs ontology-based functional enrichment to characterize biological roles of transcription factors.
• Operational modes: Provides a solo mode using only ChIP-seq peaks and an ensemble mode combining ChIP-seq peaks with DGE.
• Species support: Supports analyses in human and mouse models.

Scientific Applications:

• TF target identification: Identifies genes directly regulated by transcription factors by combining binding and expression evidence.
• Functional annotation of TFs: Characterizes biological roles of transcription factors via ontology enrichment of target genes.
• Peak-only analysis: Enables ontology analysis based solely on ChIP-seq peak locations in solo mode.
• Integrated regulatory analysis: Provides a comprehensive view of TF-mediated gene regulation by integrating ChIP-seq and DGE in ensemble mode for human and mouse.

Methodology:

Implements the BETA method to integrate ChIP-seq peak data with differential gene expression; supports a solo mode using ChIP-seq peaks for ontology analysis and an ensemble mode combining peaks with DGE to identify directly regulated genes.