单细胞技术的最新进展允许以单细胞分辨率表征实验扰动。虽然已经开发出分析此类实验的方法，但尚未探索应用严格的因果框架来推断单细胞水平的治疗效果。在这里，我们提出了一种基于因果推理的单细胞扰动分析方法，称为 CINEMA-OT（因果独立效应模块归因最优传输）。 CINEMA-OT 将混杂的变异源与扰动效应分开，以获得反映反事实细胞对的最佳传输匹配。这些细胞对代表因果扰动反应，允许进行许多新颖的分析，例如个体治疗效果分析、反应聚类、归因分析和协同分析。我们在多个模拟和真实数据集的一系列治疗效果估计任务上对 CINEMA-OT 进行了基准测试，并表明它优于其他单细胞扰动分析方法。最后，我们对两个新生成的数据集进行 CINEMA-OT 分析：（1）鼻病毒和香烟烟雾暴露的气道类器官，以及（2）免疫细胞的组合细胞因子刺激。在这些实验中，CINEMA-OT 揭示了香烟烟雾暴露减弱气道抗病毒反应的潜在机制，以及控制趋化因子分泌和外周免疫细胞招募的逻辑。© 2023。作者。

Recent advancements in single-cell technologies allow characterization of experimental perturbations at single-cell resolution. While methods have been developed to analyze such experiments, the application of a strict causal framework has not yet been explored for the inference of treatment effects at the single-cell level. Here we present a causal-inference-based approach to single-cell perturbation analysis, termed CINEMA-OT (causal independent effect module attribution + optimal transport). CINEMA-OT separates confounding sources of variation from perturbation effects to obtain an optimal transport matching that reflects counterfactual cell pairs. These cell pairs represent causal perturbation responses permitting a number of novel analyses, such as individual treatment-effect analysis, response clustering, attribution analysis, and synergy analysis. We benchmark CINEMA-OT on an array of treatment-effect estimation tasks for several simulated and real datasets and show that it outperforms other single-cell perturbation analysis methods. Finally, we perform CINEMA-OT analysis of two newly generated datasets: (1) rhinovirus and cigarette-smoke-exposed airway organoids, and (2) combinatorial cytokine stimulation of immune cells. In these experiments, CINEMA-OT reveals potential mechanisms by which cigarette-smoke exposure dulls the airway antiviral response, as well as the logic that governs chemokine secretion and peripheral immune cell recruitment.© 2023. The Author(s).