crispr-grna-designer
Design CRISPR gRNA sequences for specific gene exons with off-target prediction and efficiency scoring. Trigger when user needs gRNA design, CRISPR guide RNA selection, or genome editing target analysis.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/aipoch-ai/crispr-grna-designerCRISPR gRNA Designer
Design optimal guide RNA (gRNA) sequences for CRISPR-Cas9 genome editing. Supports on-target efficiency scoring and off-target prediction.
Use Cases
- Design gRNAs for gene knockout (KO) experiments
- Select high-efficiency guides for specific exons
- Predict and minimize off-target effects
- Optimize for SpCas9, SpCas9-NG, xCas9 variants
Input Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
gene_symbol | string | Yes | HGNC gene symbol (e.g., TP53, BRCA1) |
target_exon | int | No | Specific exon number (default: all coding exons) |
genome_build | string | No | Reference genome: hg38 (default), hg19, mm10 |
pam_sequence | string | No | PAM motif: NGG (default), NAG, NGCG |
guide_length | int | No | gRNA length in bp (default: 20) |
gc_content_min | float | No | Minimum GC% (default: 30) |
gc_content_max | float | No | Maximum GC% (default: 70) |
poly_t_threshold | int | No | Max consecutive T's (default: 4) |
off_target_check | bool | No | Enable off-target prediction (default: true) |
max_mismatches | int | No | Max mismatches for off-target (default: 3) |
Output Format
{
"gene": "TP53",
"genome": "hg38",
"guides": [
{
"id": "TP53_E2_G1",
"exon": 2,
"sequence": "GAGCGCTGCTCAGATAGCGATGG",
"pam": "NGG",
"position": "chr17:7669609-7669631",
"strand": "+",
"gc_content": 52.2,
"efficiency_score": 0.78,
"off_target_count": 2,
"off_targets": [...],
"warnings": []
}
]
}
Scoring Algorithm
On-Target Efficiency Score (0-1)
Combines multiple position-specific features:
- Position-weighted matrix: G at position 20 (+3), C at 19 (+2), etc.
- GC content penalty: Outside 40-60% range reduces score
- Self-complementarity: Hairpin formation penalty
- Poly-T penalty: Transcription terminator sequences
score = w1*position_score + w2*gc_score + w3*secondary_score + w4*poly_t_score
Off-Target Prediction
- Seed region: Positions 12-20 (PAM-proximal) weighted 3x
- Bulge/mismatch tolerance: Allow up to
max_mismatches - Genomic location: Coding regions flagged as high-risk
- CFD score: Cutting Frequency Determination for off-target cleavage
Usage Examples
Basic gRNA Design
python scripts/main.py --gene TP53 --exon 4 --output results.json
High-Specificity Design (strict off-target filtering)
python scripts/main.py --gene BRCA1 --max-mismatches 2 --gc-min 35 --gc-max 65
Batch Processing
python scripts/main.py --gene-list genes.txt --genome mm10 --pam NAG
Technical Notes
⚠️ Difficulty: HIGH - Requires manual verification before experimental use
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-aipoch-ai-crispr-grna-designer": {
"enabled": true,
"auto_update": true
}
}
}Tags
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