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

Seungjun Ahn; Li Chen; Maaike van Gerwen; Panos Roussos; Zhigang Li

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arXiv · 2507.06113

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

Seungjun Ahn·Li Chen·Maaike van Gerwen·Panos Roussos·Zhigang Li

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Abstract

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. The model can identify expression level as well as expressed proportion that could mediate disease-leading causal pathway. 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.

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Seungjun Ahn, Li Chen, Maaike van Gerwen, Panos Roussos, Zhigang Li. 2025-07-08. A Statistical Framework for Co-Mediators of Zero-Inflated Single-Cell RNA-Seq Data. https://arxiv.org/abs/2507.06113

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