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 
[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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