Data & ReproBioinformatics & GenomicsFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction

bio-ribo-seq-orf-detection

Maintainer FreedomIntelligence · Last updated April 1, 2026

Detect and quantify translated ORFs from Ribo-seq data including uORFs and novel ORFs using RiboCode and ORFquant. Use when identifying translated regions beyond annotated coding sequences or quantifying ORF-level translation.

OpenClawNanoClawAnalysisReproductionbio-ribo-seq-orf-detection🧬 bioinformatics (gptomics bio-* suite)bioinformatics — differential expression & transcriptomicsdetect

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-ribo-seq-orf-detection

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

CLI: RiboCode for periodicity-based ORF detection.
R: ORFik for ORF quantification and annotation.
Detect translated ORFs from my Ribo-seq data" → Identify actively translated open reading frames including uORFs and novel ORFs using 3-nucleotide periodicity as evidence of active translation. CLI: RiboCode for periodicity-based ORF detection R: ORFik for ORF quantification and annotation.
prepare_transcripts \ -g annotation.gtf \ -f genome.fa \ -o ribocode_annot.

Source Doc

Excerpt From SKILL.md

RiboCode Workflow

Goal: Detect actively translated ORFs from Ribo-seq data using 3-nucleotide periodicity as evidence of translation.

Approach: Prepare transcript annotations, then run RiboCode with specified read lengths to identify ORFs with significant periodicity.


## Step 2: Run RiboCode

RiboCode \
    -a ribocode_annot \
    -c config.txt \
    -l 27,28,29,30 \
    -o output_prefix

## One-Step RiboCode

**Goal:** Run the complete ORF detection pipeline in a single command without separate annotation preparation.

**Approach:** Use RiboCode_onestep which combines annotation preparation, offset determination, and ORF calling.

```bash