Deciphering the functional interactions of cells in tissues remains a major challenge. Here we describe DIALOGUE, a method to systematically uncover multicellular programs (MCPs)—combinations of coordinated cellular programs in different cell types that form higher-order functional units at the tissue level—from either spatial data or single-cell data obtained without spatial information. Tested on spatial datasets from the mouse hypothalamus, cerebellum, visual cortex and neocortex, DIALOGUE identified MCPs associated with animal behavior and recovered spatial properties when tested on unseen data while outperforming other methods and metrics. In spatial data from human lung cancer, DIALOGUE identified MCPs marking immune activation and tissue remodeling. Applied to single-cell RNA sequencing data across individuals or regions, DIALOGUE uncovered MCPs marking Alzheimer’s disease, ulcerative colitis and resistance to cancer immunotherapy. These programs were predictive of disease outcome and predisposition in independent cohorts and included risk genes from genome-wide association studies. DIALOGUE enables the analysis of multicellular regulation in health and disease.

破译组织中细胞的功能相互作用仍然是一个重大挑战。在这里，我们描述了 DIALOGUE，这是一种系统地揭示多细胞程序 (MCP) 的方法——不同细胞类型中协调的细胞程序的组合，在组织水平上形成高阶功能单元——来自空间数据或在没有空间信息的情况下获得的单细胞数据. 通过对来自小鼠下丘脑、小脑、视觉皮层和新皮层的空间数据集进行测试，DIALOGUE 确定了与动物行为相关的 MCP，并在对看不见的数据进行测试时恢复了空间特性，同时优于其他方法和指标。在来自人类肺癌的空间数据中，DIALOGUE 确定了标记免疫激活和组织重塑的 MCP。应用于跨个体或跨区域的单细胞RNA测序数据，DIALOGUE 发现了标记阿尔茨海默病、溃疡性结肠炎和癌症免疫疗法耐药性的 MCP。这些程序可预测独立队列中的疾病结果和易感性，并包括来自全基因组关联研究的风险基因。DIALOGUE 可以分析健康和疾病中的多细胞调节。