RiboFlow

RiboFlow processes ribosome profiling sequencing data to organize read-length-resolved ribosome footprint information into a binary "ribo" format for quantitative analysis of translation and protein synthesis.

Key Features:

• Efficient Data Storage: Central "ribo" binary format that groups ribosome profiling data by ribosome footprint (read) lengths to retain read-length resolution.
• Pipeline Processing and Parallelization: A pipeline that converts raw ribosome profiling sequencing data into the "ribo" format with built-in parallelization for scalable processing.
• Portability: Pipeline designed for portability across diverse computational environments.
• Programming Interfaces: Programmatic interfaces RiboR (R) and RiboPy (Python) to access quality-control metrics, generate visualizations, and perform analyses.
• Integrated Ecosystem: Integration of data processing, storage, and analysis components to support studies of translation dynamics using read-length information.

Scientific Applications:

• Translation regulation analysis: Investigation of mechanisms underlying translational control by analyzing ribosome occupancy and footprint lengths.
• Quantitative protein synthesis estimation: Precise estimation of protein abundance from read-length-resolved ribosome profiling data.
• Differential translational expression: Analysis of differential gene expression at the translational level.
• Condition-specific translation effects: Exploration of how experimental conditions affect ribosome occupancy and protein synthesis.

Methodology:

Processes raw ribosome profiling sequencing data into the "ribo" binary format by grouping reads by ribosome footprint lengths and extracting metrics across a spectrum of read lengths, with support for parallelized execution.