RiboDiPA

RiboDiPA performs differential pattern analysis of Ribo-seq data to identify genes with statistically significant differences in ribosome occupancy patterns across conditions.

Key Features:

• Pattern-Based Analysis: Emphasizes analysis of ribosome footprint patterns at single-codon resolution to detect nuanced changes in translation dynamics.
• Statistical Rigor: Employs robust statistical methodologies to identify significant differences in ribosome occupancy patterns between experimental conditions.
• R Package Implementation: Implemented as an R package for Differential Pattern Analysis of Ribo-seq data.
• Organism Versatility: Applicable to a wide array of model organisms, from yeast to mammals.
• Gene-Level Detection: Identifies genes exhibiting statistically significant differences in ribosome occupancy patterns.

Scientific Applications:

• Complementary Insights: Provides insights complementary to translational efficiency analyses by focusing on differential ribosome footprint patterns.
• Global and Local Translational Differences: Reveals both global translational differences between conditions and local ribosome binding patterns at a codon level.

Methodology:

Performs pattern-based analysis at single-codon resolution using robust statistical testing, implemented in an R package, and validated on simulated Ribo-seq footprint data and two benchmark datasets.