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
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

Documentation:

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

Downloads:

Package source:	nebula_1.5.3.tar.gz
Windows binaries:	r-devel: nebula_1.5.3.zip, r-release: nebula_1.5.3.zip, r-oldrel: nebula_1.5.3.zip
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

Linking:

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