nebula: Negative Binomial Mixed Models Using Large-Sample Approximationfor 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: | 1.5.6 |
| 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: | 2025-12-07 |
| DOI: | 10.32614/CRAN.package.nebula |
| Author: | Liang He [aut, cre], Raghav Sharma [ctb] |
| Maintainer: | Liang He <hyx520101 at gmail.com> |
| BugReports: | https://github.com/lhe17/nebula/issues |
| License: | GPL-3 |
| URL: | https://github.com/lhe17/nebula |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | nebula results |
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