AA
AAV vector design: capsid selection, promoter optimization, payload capacity.
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数据与复现
VA
varcadd-pathogenicity
维护者 FreedomIntelligence · 最近更新 2026年4月1日
VARCADD pathogenicity scoring for coding variants from structure and evolution.
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/varcadd-pathogenicity
- 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
核心说明
- Genome-wide pathogenicity prediction leveraging standing variation data to improve accuracy over traditional CADD scores。
- Variant Prioritization：Ranking candidate variants in rare disease cases。
- VUS Interpretation：Assessing variants of uncertain significance。
- Research：Annotating novel variants in population studies。
- Variant Prioritization：Ranking candidate variants in rare disease cases. VUS Interpretation：Assessing variants of uncertain significance. * Research：Annotating novel variants in population studies。
原始文档
SKILL.md 摘录
Core Capabilities
- Score Generation: Calculate C-scores for SNVs and indels.
- Annotation: Add functional context (conservation, protein domains).
- Filtering: Identify likely pathogenic variants based on thresholds.
Workflow
- Input: VCF file.
- Annotate: Run varCADD model.
- Filter: Keep variants with Score > X.
- Output: Annotated VCF or ranked table.
Example Usage
User: "Score these variants from patient X."
Agent Action:
适用场景
- Use varcadd-pathogenicity ，用于 medicinal chemistry 、 drug-discovery work。
- Apply varcadd-pathogenicity to compound，target，或 screening workflows。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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