MedZIsc: Statistical Framework for Co-Mediators of Zero-Inflated Single-Cell Data

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>.

Version: 0.0.4
Depends: R (≥ 3.5.0)
Imports: MASS, betareg, glmnet
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-07-16
DOI: 10.32614/CRAN.package.MedZIsc
Author: Seungjun Ahn ORCID iD [cre, aut], Zhigang Li [ctb]
Maintainer: Seungjun Ahn <seungjun.ahn at mountsinai.org>
License: GPL-3
NeedsCompilation: no
CRAN checks: MedZIsc results

Documentation:

Reference manual: MedZIsc.html , MedZIsc.pdf

Downloads:

Package source: MedZIsc_0.0.4.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): MedZIsc_0.0.4.tgz, r-oldrel (x86_64): MedZIsc_0.0.4.tgz

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