ribo-seq

Name: ribo-seq
Availability: InStock
Author: zongtingwei

Automate ribosome profiling analysis from raw reads to translation efficiency insights.

25|5|Updated Mar 22, 2026

Search Tags:#translation #bioinformatics #orf #periodicity #ribo-seq #ribosome-profiling #te

Ready to run

npx skills add https://github.com/zongtingwei/Bioclaw_Skills_Hub --skill ribo-seq

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ribo-seq
Source: https://github.com/zongtingwei/Bioclaw_Skills_Hub/tree/main/skills/transcriptomics/ribo-seq
Command: npx skills add https://github.com/zongtingwei/Bioclaw_Skills_Hub --skill ribo-seq

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Automates end-to-end ribosome profiling analysis from raw reads to translation efficiency insights, enabling researchers to extract meaningful translation signals with minimal manual setup.

Core Features & Use Cases

P-site aware preprocessing and read offset estimation
Periodicity validation, frame enrichment checks, and ORF discovery
Translation efficiency estimation and transcript-level reporting
Use Case: compare ribosome occupancy with RNA-seq to infer translational regulation across conditions

Quick Start

Provide ribo-seq reads (and optional matched RNA-seq) along with transcript annotations to run the workflow.

Frequently Asked Questions about ribo-seq

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I calculate translation efficiency from ribosome profiling and RNA-seq data?▼

To calculate translation efficiency, you compare ribosome occupancy from ribo-seq with matched RNA-seq data to infer translational regulation. This workflow requires providing ribo-seq reads, optional RNA-seq data, and transcript annotations.

What is P-site preprocessing and read offset estimation in ribosome profiling?▼

P-site preprocessing maps ribosome footprint reads to precise codon positions. This workflow automates P-site aware preprocessing and read offset estimation to extract meaningful translation signals from raw reads.

How do I validate 3-nucleotide periodicity and frame enrichment for ribosome profiling reads?▼

Validating 3-nucleotide periodicity confirms true ribosome footprints by checking frame enrichment. This workflow performs periodicity validation and frame enrichment checks automatically during end-to-end ribosome profiling analysis.

Can I use this workflow for ORF discovery from raw ribosome profiling reads?▼

Yes, you can use this workflow for ORF discovery from raw reads. It applies P-site preprocessing and periodicity validation to identify open reading frames and estimate translation efficiency at the transcript level.

Do I need a specific Python environment to run ribosome profiling and TE estimation?▼

Yes, ribosome profiling and TE estimation demands a Python environment with specific utilities. You need ribo-seq preprocessing utilities, pandas, and matplotlib installed to execute the end-to-end workflow.

What is the best way to automate end-to-end ribosome profiling analysis from raw reads?▼

The best way to automate end-to-end ribosome profiling analysis is using a workflow handling P-site preprocessing, periodicity validation, ORF discovery, and TE estimation with minimal manual setup, providing transcript-level reporting directly.