用大模型一键生成可复用的环形基因组图，省去复杂编程。
AuraGenome: An LLM-Powered Framework for On-the-Fly Reusable and Scalable Circular Genome Visualizations
- 七类智能代理协作：识别意图、规划布局、生成代码
- 支持环形/辐射/弦图多布局，可实时调整并导出报告
- 适合生物学家快速探索基因结构变异，免编程
环形基因组可视化对结构变异和基因调控研究至关重要。然而，现有工具常需复杂脚本和手动配置，过程耗时、易错且难上手。为此，我们提出AuraGenome，一个基于大语言模型的框架，可快速生成可复用、可扩展的多层环形基因组可视化图。该框架采用语义驱动的多智能体工作流，包含七个由LLM驱动的专用代理，分别承担意图识别、布局规划、代码生成等任务，将原始基因组数据自动转化为定制化可视化结果。系统支持环形、辐射及弦图等多种协同视图布局，适用于多层基因组数据展示。同时具备交互功能、配置复用、实时优化及高质量报告导出能力。通过两个案例研究和全面用户评估验证了其有效性。项目开源地址：https://github.com/Darius18/AuraGenome。
原文摘要 · Abstract (English)
Circular genome visualizations are essential for exploring structural variants and gene regulation. However, existing tools often require complex scripting and manual configuration, making the process time-consuming, error-prone, and difficult to learn. To address these challenges, we introduce AuraGenome, an LLM-powered framework for rapid, reusable, and scalable generation of multi-layered circular genome visualizations. AuraGenome combines a semantic-driven multi-agent workflow with an interactive visual analytics system. The workflow employs seven specialized LLM-driven agents, each assigned distinct roles such as intent recognition, layout planning, and code generation, to transform raw genomic data into tailored visualizations. The system supports multiple coordinated views tailored for genomic data, offering ring, radial, and chord-based layouts to represent multi-layered circular genome visualizations. In addition to enabling interactions and configuration reuse, the system supports real-time refinement and high-quality report export. We validate its effectiveness through two case studies and a comprehensive user study. AuraGenome is available at: https://github.com/Darius18/AuraGenome.
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