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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 |
Maintainer: | Seungjun Ahn <seungjun.ahn at mountsinai.org> |
License: | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | MedZIsc results |
Reference manual: | MedZIsc.html , MedZIsc.pdf |
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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