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 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:
Downloads:
Linking:
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