Metadensity

Metadensity visualizes CLIP signal distributions around transcript features to characterize RNA-binding protein (RBP) binding patterns.

Key Features:

• Metagene Plot Generation: Generates metagene plots that visualize the distribution of CLIP signals around specific transcript features such as branchpoints.
• High-Resolution Signal Preservation: Maintains near-nucleotide resolution of CLIP data without scaling features by length to preserve spatial detail of RBP binding.
• Normalization with Background Controls: Normalizes immunoprecipitated libraries using background controls such as size-matched inputs to reduce non-specific signal.
• User-Defined Feature Windowing: Applies user-defined windowing around specified transcript features for targeted analysis.
• Averaging Across Transcripts: Averages normalized, windowed signals across selected transcripts to produce representative profiles.
• Python Implementation: Implemented in Python for computational processing of CLIP datasets.

Scientific Applications:

• RBP binding-site mapping: Maps and visualizes binding distributions of RNA-binding proteins across transcript features using CLIP data.
• Splicing regulation analysis: Investigates splicing factors and their association with alternatively spliced exons and branchpoints.
• Comparative CLIP visualization: Compares CLIP datasets via metagene profiles to interpret binding dynamics and common motifs.

Methodology:

Normalize immunoprecipitated libraries to background controls (e.g., size-matched inputs), apply user-defined windowing around specified transcript features, preserve near-nucleotide resolution without scaling by feature length, and average windowed normalized signals across selected transcripts to produce metagene plots; implemented in Python.