FLASHMM: Fast and Scalable Single Cell Differential Expression Analysis
using Mixed-Effects Models
A fast and scalable linear mixed-effects model (LMM) estimation algorithm
for analysis of single-cell differential expression. The algorithm uses
summary-level statistics and requires less computer memory to fit the LMM.
| Version: |
1.1.0 |
| Imports: |
stats, MASS, Matrix |
| Suggests: |
knitr, bookdown, rmarkdown, devtools, BiocManager, SingleCellExperiment, ExperimentHub |
| Published: |
2025-03-11 |
| DOI: |
10.32614/CRAN.package.FLASHMM |
| Author: |
Changjiang Xu [aut, cre],
Gary Bader [aut] |
| Maintainer: |
Changjiang Xu <changjiang.xu at utoronto.ca> |
| BugReports: |
https://github.com/BaderLab/FLASHMM/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/BaderLab/FLASHMM |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
FLASHMM results |
Documentation:
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