CAGEfightR

CAGEfightR identifies transcription start sites and predicts enhancers from Cap Analysis of Gene Expression (CAGE) data for downstream quantification, annotation, TSS shape analysis, and visualization.

Key Features:

• Fast, memory-efficient TSS identification: Tag clustering algorithms identify transcription start sites (TSSs) from CAGE tags.
• Enhancer prediction via bidirectional clustering: Bidirectional clustering of CAGE tags detects putative enhancers based on divergent transcription.
• Annotation with transcript and gene models: Annotates TSSs and predicted enhancers using existing transcript and gene models.
• Quantification of CAGE expression: Produces expression matrices quantifying CAGE signal for comparative analyses.
• TSS shape statistics: Calculates TSS shape metrics to characterize transcription initiation profiles.
• Visualization functions: Provides plotting and visualization of tag clusters, TSSs, and enhancers.
• R/Bioconductor integration: Implements data structures and workflows compatible with R and Bioconductor.

Scientific Applications:

• Gene regulation: Mapping TSSs and enhancers to investigate transcriptional regulation across conditions.
• Epigenetics: Linking CAGE-defined regulatory elements to chromatin and epigenetic studies of gene activity.
• Comparative genomics: Comparing CAGE expression profiles across species or conditions to identify conserved regulatory elements.

Methodology:

Performs unidirectional (tag) and bidirectional clustering algorithms on CAGE tags to identify TSSs and enhancers, computes TSS shape statistics, and integrates results with R/Bioconductor data structures.