流程自动化科研基础设施FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
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varCADD

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

varCADD。

OpenClawNanoClaw分析处理复现实验varcaddopenclaw medical skillsadditional scientific toolsvarcadd

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/varCADD

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

  • 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

  1. Score Generation: Calculate C-scores for SNVs and indels.
  2. Annotation: Add functional context (conservation, protein domains).
  3. Filtering: Identify likely pathogenic variants based on thresholds.

Workflow

  1. Input: VCF file.
  2. Annotate: Run varCADD model.
  3. Filter: Keep variants with Score > X.
  4. Output: Annotated VCF or ranked table.

Example Usage

User: "Score these variants from patient X."

Agent Action:

适用场景

  • Use varCADD in 科研工作流 aligned ,支持 this subject area。
  • Follow upstream documentation ,用于 full working procedure。

不适用场景

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

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