In this paper, we introduce QuST-LLM, an innovative extension of QuPath that utilizes the capabilities of large language models (LLMs) to analyze and interpret spatial transcriptomics (ST) data. This tool effectively simplifies the intricate and high-dimensional nature of ST data by offering a comprehensive workflow that includes data loading, region selection, gene expression analysis, and functional annotation. QuST-LLM employs LLMs to transform complex ST data into understandable and detailed biological narratives based on gene ontology annotations, thereby significantly improving the interpretability of ST data. Consequently, users can interact with their own ST data using natural language. Hence, QuST-LLM provides researchers with a potent functionality to unravel the spatial and functional complexities of tissues, fostering novel insights and advancements in biomedical research.

翻译：本文介绍了QuST-LLM，这是QuPath的一项创新性扩展工具，它利用大型语言模型（LLMs）的能力来分析和解读空间转录组学（ST）数据。该工具通过提供包含数据加载、区域选择、基因表达分析和功能注释在内的完整工作流程，有效简化了ST数据复杂且高维的特性。QuST-LLM运用LLMs，基于基因本体注释将复杂的ST数据转化为易于理解且详尽的生物学描述，从而显著提升了ST数据的可解释性。因此，用户能够使用自然语言与自身的ST数据进行交互。由此可见，QuST-LLM为研究人员提供了一个强大的功能，以揭示组织在空间和功能上的复杂性，从而推动生物医学研究的新见解与进展。