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crispr-guide-design

crispr-guide-design,来自 FreedomIntelligence/OpenClaw-Medical-Skills 的 agent 技能。

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技能内容

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COPYRIGHT NOTICE

This file is part of the "Universal Biomedical Skills" project.

Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>

All Rights Reserved.

#

This code is proprietary and confidential.

Unauthorized copying of this file, via any medium is strictly prohibited.

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Provenance: Authenticated by MD BABU MIA

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name: crispr-guide-design

description: Guide foundry

keywords:

  • CRISPR
  • sgRNA
  • Doench
  • off-target
  • oligos

measurable_outcome: Return the requested number of guides (default ≥4) with efficiency + specificity scores, coordinates, and cloning oligos within 10 minutes per gene.

license: MIT

metadata:

author: CRISPR-GPT Team

version: "1.0.0"

compatibility:

  • system: Python 3.10+

allowed-tools:

  • run_shell_command
  • read_file

CRISPR Design Agent

Automate sgRNA selection, scoring, off-target evaluation, and oligo generation for CRISPR experiments using the documented workflow.

When to Use

  • Designing CRISPR knockout/knock-in experiments that need validated guides.
  • Locating all PAM-compatible target sites in a gene or locus.
  • Filtering guides by efficiency/off-target metrics before cloning.

Core Capabilities

  1. Target discovery: Scan sequences for PAM motifs (e.g., NGG).
  2. Efficiency scoring: Evaluate GC content, homopolymers, Doench/DeepCRISPR/CFD scores.
  3. Filtering & ranking: Remove risky guides (SNP overlap, off-target hits) and output the best candidates.

Workflow

  1. Resolve gene symbol + organism to canonical transcript coordinates and target region.
  2. Enumerate PAM-compatible sites; extract spacers for the chosen Cas variant.
  3. Score guides (efficiency + specificity) and compute GC metrics.
  4. Run off-target search (≤3 mismatches) to flag problematic loci.
  5. Filter/rank guides, generate cloning oligos/primers, and emit JSON/CSV outputs with coordinates.

Example Usage

python3 Skills/Genomics/CRISPR_Design_Agent/crispr_designer.py \
    --sequence "ATGGAGGAGCCGCAGTCAGATCCTAGCGTCGAGCCCCCTCTGAGTCAGGAAACATTTTCAGACCTATGGAAACTGTGAGTGGATCCATTGGAAGGGC" \
    --output guides.json

Guardrails

  • Always state genome build and Cas variant assumptions.
  • Avoid guides overlapping common SNPs when avoid_variants is true.
  • Flag high off-target density near coding regions for manual review.

References

  • See README.md and prompt.md for detailed schema plus supporting literature.

<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

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