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bio-genome-engineering-grna-design

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

bio-genome-engineering-grna-design:Design guide RNAs ,用于 CRISPR-Cas9/Cas12a experiments ,使用 CRISPRscan 、 local scoring algorithms。 Score guides ,用于 on-target activity ,使用 Rule Set 2 、 Azimuth models。 适合在designing sgRNAs ,用于 gene knockout,activation,或 repression experiments时使用。

OpenClawNanoClaw分析处理复现实验bio-genome-engineering-grna-design🧬 bioinformatics (gptomics bio-* suite)bioinformatics — epidemiological & causal genomicsdesign

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-genome-engineering-grna-design

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

  • Python:custom PAM scanning ,支持 Bio.Seq,CRISPRscan scoring models。
  • Design guide RNAs ,用于 my CRISPR knockout experiment" → Scan target gene sequence ,用于 PAM sites,extract candidate spacer sequences,、 score them ,用于 on-target activity ,使用 Rule Set 2 或 CRISPRscan algorithms. Python:custom PAM scanning ,支持 Bio.Seq,CRISPRscan scoring models。
  • GC content 40-70%:optimal range (outside this = penalty)。
  • Position-specific nucleotide preferences。
  • No poly-T stretches (terminates Pol III transcription)。

原始文档

SKILL.md 摘录

but works well across species for Cas9

def crisprscan_score(guide_35mer): '''Score using CRISPRscan model

Input: 35-mer (6bp upstream + 20bp guide + 3bp PAM + 6bp downstream)
Output: Activity score 0-100

Requires the crisprscan package:
pip install crisprscan
'''
try:
    import crisprscan
    return crisprscan.score(guide_35mer)
except ImportError:
    # Fallback to simplified scoring
    return score_guide_activity(guide_35mer[6:26]) * 100

## Design Workflow

**Goal:** Design the top N guide RNAs for a target gene, optionally restricted to coding exon regions.

**Approach:** Scan both strands for PAM sites, optionally filter to guides within exon coordinates, score each guide for on-target activity using GC content and position-weight criteria, and return the highest-scoring candidates.

适用场景

  • 适合在designing sgRNAs ,用于 gene knockout,activation,或 repression experiments时使用。

不适用场景

  • Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。

上游相关技能

  • genome-engineering/off-target-prediction - Check off-targets after design
  • crispr-screens/library-design - Pool multiple guides for screens
  • primer-design/primer-basics - Design flanking primers for validation

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