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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: 1.0.0
Imports: stats, MASS, Matrix
Suggests: knitr, bookdown, rmarkdown, devtools, SingleCellExperiment, ExperimentHub
Published: 2025-01-14
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:

Reference manual: FLASHMM.pdf
Vignettes: Single-cell differential expression analysis with FLASHMM (source, R code)

Downloads:

Package source: FLASHMM_1.0.0.tar.gz
Windows binaries: r-devel: FLASHMM_1.0.0.zip, r-release: FLASHMM_1.0.0.zip, r-oldrel: FLASHMM_1.0.0.zip
macOS binaries: r-release (arm64): FLASHMM_1.0.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): FLASHMM_1.0.0.tgz, r-oldrel (x86_64): not available

Linking:

Please use the canonical form https://CRAN.R-project.org/package=FLASHMM to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.