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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.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/aipoch-ai/crispr-grna-designer
Or

CRISPR 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

ParameterTypeRequiredDescription
gene_symbolstringYesHGNC gene symbol (e.g., TP53, BRCA1)
target_exonintNoSpecific exon number (default: all coding exons)
genome_buildstringNoReference genome: hg38 (default), hg19, mm10
pam_sequencestringNoPAM motif: NGG (default), NAG, NGCG
guide_lengthintNogRNA length in bp (default: 20)
gc_content_minfloatNoMinimum GC% (default: 30)
gc_content_maxfloatNoMaximum GC% (default: 70)
poly_t_thresholdintNoMax consecutive T's (default: 4)
off_target_checkboolNoEnable off-target prediction (default: true)
max_mismatchesintNoMax 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:

  1. Position-weighted matrix: G at position 20 (+3), C at 19 (+2), etc.
  2. GC content penalty: Outside 40-60% range reduces score
  3. Self-complementarity: Hairpin formation penalty
  4. Poly-T penalty: Transcription terminator sequences
score = w1*position_score + w2*gc_score + w3*secondary_score + w4*poly_t_score

Off-Target Prediction

  1. Seed region: Positions 12-20 (PAM-proximal) weighted 3x
  2. Bulge/mismatch tolerance: Allow up to max_mismatches
  3. Genomic location: Coding regions flagged as high-risk
  4. 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

Author@aipoch-ai
Stars4473
Views0
Updated2026-05-01
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-aipoch-ai-crispr-grna-designer": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags

#crispr#grna#genome-editing#bioinformatics#off-target#cas9
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