FLASHMM | Linear mixed-effects model | The fast and scalable algorithm | Functions | Example | Simulating scRNA-seq data | DE analysis of scRNA-seq data | LMM design | LMM fitting | Hypothesis testing | Using ML method | Methods | LMM parameter estimation | Remarks | Session info | References
Package: FLASHMM 1.3.0
Changjiang Xu
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.
Authors:
FLASHMM_1.3.0.tar.gz
FLASHMM_1.3.0.zip(r-4.7-any)FLASHMM_1.3.0.zip(r-4.6-any)FLASHMM_1.3.0.zip(r-4.5-any)
FLASHMM_1.3.0.tgz(r-4.6-any)FLASHMM_1.3.0.tgz(r-4.5-any)
FLASHMM_1.3.0.tar.gz(r-4.7-any)FLASHMM_1.3.0.tar.gz(r-4.6-any)
FLASHMM_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
FLASHMM/json (API)
| # Install 'FLASHMM' in R: |
| install.packages('FLASHMM', repos = c('https://baderlab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/baderlab/flashmm/issues
Last updated from:3fe4db9cbf. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 151 | ||
| source / vignettes | OK | 228 | ||
| linux-release | OK | 139 | ||
| macos-release | OK | 200 | ||
| macos-oldrel | OK | 215 | ||
| windows-devel | OK | 80 | ||
| windows-release | OK | 68 | ||
| windows-oldrel | OK | 79 | ||
| wasm-release | OK | 117 |
Exports:contrast.matrixflashmmlmmlmmfitlmmtestsimuRNAseqsslmm
