标题： 零膨胀单细胞RNA测序数据的共同调节器统计框架 显示英文标题

标题： A Statistical Framework for Co-Mediators of Zero-Inflated Single-Cell RNA-Seq Data

摘要： 单细胞RNA测序(scRNA-seq)已经革新了细胞异质性的研究，使得在单个细胞水平上进行详细的分子表征成为可能。 然而，由于零膨胀和复杂的中介结构，将高维单细胞数据整合到因果中介分析中仍然具有挑战性。 我们提出了一种新的中介框架，利用零膨胀负二项模型来描述细胞水平的中介分布，并使用贝塔回归来处理零膨胀比例。 受试者水平的中介变量从细胞水平的数据中汇总，以进行评估基因表达与临床结果之间因果路径的中介分析。 广泛的模拟研究表明该方法具有更高的功效并能控制错误发现率。 我们进一步通过应用到ROSMAP单细胞转录组数据来展示该方法的实用性，揭示出生物学上有意义的中介效应，从而增强对疾病机制的理解。 显示英文摘要

摘要： Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity, enabling detailed molecular profiling at the individual cell level. However, integrating high-dimensional single-cell data into causal mediation analysis remains challenging due to zero inflation and complex mediator structures. We propose a novel mediation framework leveraging zero-inflated negative binomial models to characterize cell-level mediator distributions and beta regression for zero-inflation proportions. Subject-level mediators are aggregated from cell-level data to perform mediation analysis assessing causal pathways linking gene expression to clinical outcomes. Extensive simulation studies demonstrate improved power and controlled false discovery rates. We further illustrate the utility of this approach through application to ROSMAP single-cell transcriptomic data, uncovering biologically meaningful mediation effects that enhance understanding of disease mechanisms.