数据与复现生物信息与基因组学FreedomIntelligence/OpenClaw-Medical-Skills数据与复现

bio-ribo-seq-orf-detection

维护者 FreedomIntelligence · 最近更新 2026年4月1日

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.

OpenClawNanoClaw分析处理复现实验bio-ribo-seq-orf-detection🧬 bioinformatics (gptomics bio-* suite)bioinformatics — differential expression & transcriptomicsdetect

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

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

维护者: FreedomIntelligence
许可: MIT
最近更新: 2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

CLI：RiboCode ，用于 periodicity-based ORF detection。
R：ORFik ，用于 ORF quantification 、 annotation。
检测 translated ORFs ，面向 my Ribo-seq data" → Identify actively translated open reading frames ，涵盖 uORFs 、 novel ORFs ，使用 3-nucleotide periodicity as evidence of active translation. CLI：RiboCode ，用于 periodicity-based ORF detection R：ORFik ，用于 ORF quantification 、 annotation。
prepare_transcripts \ -g annotation.gtf \ -f genome.fa \ -o ribocode_annot。

原始文档

SKILL.md 摘录

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