TFregulomeR

TFregulomeR integrates cistrome and methylome datasets to enable integrative analyses of transcription factor (TF) binding dynamics and context-specific regulation across cell types and DNA methylation states.

Key Features:

• Implementation: Implemented as an R library for programmatic analysis of TF binding and epigenetic data.
• Comprehensive Data Integration: Links to an up-to-date compendium of ChIP-seq cistrome datasets mapping genomic binding landscapes of numerous TFs across diverse cell types.
• Cell-Specific Analysis: Maps and analyzes TF binding sites (TFBSs) within specific cellular contexts to capture dynamic genomic occupancy.
• Functional Characterization: Characterizes TF binding partners and identifies cell-specific TFBSs to explore TF functions under varying conditions.
• Epigenetic Dimension: Incorporates DNA methylation profiles from datasets such as MethMotif to assess how methylation influences TF binding.
• Ontological Insights: Examines target gene ontologies associated with TFs to reveal variation driven by different TF partnerships and binding contexts.
• Re-analysis Capabilities: Enables re-analysis of characterized TFs and has uncovered database inadequacies, including mischaracterization of leucine zipper TFBSs due to improper assembly of position weight matrices from mixed homodimer and heterodimer binding sites.

Scientific Applications:

• Dissection of transcriptional regulation: Supports analyses that dissect how TFs regulate gene expression in a spatiotemporal and cell-specific manner.
• Epigenetic influence on TF binding: Enables studies of how DNA methylation (e.g., MethMotif profiles) modulates TF binding and regulatory outcomes.
• Database validation and refinement: Facilitates re-analysis of existing TF binding data to identify and correct misassembled position weight matrices and mischaracterized TFBSs, including leucine zipper sites.

Methodology:

Implemented as an R library that integrates ChIP-seq cistrome datasets and MethMotif methylome profiles, maps TFBSs across cell types, characterizes TF binding partners, assembles and analyzes position weight matrices, and performs gene ontology analysis of target genes.