Statistical Framework for Co-Mediators of Zero-Inflated Single-Cell Data R package MedZIsc version 0.0.4 A causal mediation framework for single-cell data that incorporates two key features ('MedZIsc', pronounced Magics): (1) zero-inflation using beta regression and (2) overdispersed expression counts using negative binomial regression. This approach also includes a screening step based on penalized and marginal models to handle high-dimensionality. Full methodological details are available in our recent preprint by Ahn S and Li Z (2025) <doi:10.48550/arXiv.2505.22986>. Software Depends: R (>= 3.5.0) Imports: MASS, betareg, glmnet Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Seungjun Ahn <seungjun.ahn@mountsinai.org> Comprehensive R Archive Network (CRAN) Seungjun Ahn [cre, aut] (ORCID: <https://orcid.org/0000-0002-4816-8924>), Zhigang Li [ctb] GPL-3 2025-07-16 application/tgz https://CRAN.R-project.org/package=MedZIsc doi:10.32614/CRAN.package.MedZIsc