nebula: Negative Binomial Mixed Models Using Large-Sample Approximation for Differential Expression Analysis of ScRNA-Seq Data

A fast negative binomial mixed model for conducting association analysis of multi-subject single-cell data. It can be used for identifying marker genes, differential expression and co-expression analyses. The model includes subject-level random effects to account for the hierarchical structure in multi-subject single-cell data. See He et al. (2021) <doi:10.1038/s42003-021-02146-6>.

Version: 1.5.3
Depends: R (≥ 4.1)
Imports: Rcpp (≥ 1.0.7), nloptr, stats, Matrix, methods, Rfast, trust, parallelly (≥ 1.34.0), doFuture (≥ 0.12.2), future (≥ 1.32.0), foreach (≥ 1.5.2), doRNG (≥ 1.8.6), Seurat, SingleCellExperiment
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, utils, rmarkdown
Published: 2024-02-15
DOI: 10.32614/CRAN.package.nebula
Author: Liang He [aut, cre], Raghav Sharma [ctb]
Maintainer: Liang He <hyx520101 at>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: nebula results


Reference manual: nebula.pdf
Vignettes: A fast negative binomial mixed model for analyzing multi-subject single-cell data


Package source: nebula_1.5.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): nebula_1.5.3.tgz, r-oldrel (arm64): nebula_1.5.3.tgz, r-release (x86_64): nebula_1.5.3.tgz, r-oldrel (x86_64): nebula_1.5.3.tgz
Old sources: nebula archive


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