SAVoR

SAVoR visualizes and annotates RNA secondary structures with per‑base RNA‑seq metrics to integrate structural predictions, read‑derived abundance, and variant frequency for analysis of RNA regulation.

Key Features:

• Integration of RNA‑seq and structure predictions: Links RNA secondary structure predictions with sequencing data and genomic annotations to produce structure models annotated with sequence‑derived metrics.
• Per‑base visualization: Maps per‑base values such as read abundance and sequence variant frequency onto RNA secondary structure models to display distributions of signals along structures.
• Support for smRNA‑seq and microRNA analysis: Visualizes small RNA sequencing (smRNA‑seq) read distributions along microRNA precursors and annotates potential effects of single nucleotide polymorphisms (SNPs) on folding.
• Comparative analysis: Supports control versus treatment comparisons to identify regions of enrichment or differential expression within the context of RNA structures.

Scientific Applications:

• Structure–function studies: Investigates how RNA secondary structure influences RNA functionality, processing, localization, and stability.
• MicroRNA and small RNA characterization: Interprets smRNA‑seq read distributions on predicted microRNA precursor structures to inform biogenesis and processing analyses.
• Variant impact assessment: Assesses how SNPs and sequence variants correlate with changes in predicted RNA folding and associated sequencing signals.
• Differential expression within structures: Identifies structure‑localized regions of enrichment or depletion between experimental conditions.

Methodology:

Processes read alignment data from RNA‑seq experiments, computes per‑base values reflecting read abundance and sequence variant frequency, and maps those computed metrics onto RNA secondary structure models.