Typical RNA-seq call from DESeq2 | Acknowledgments | Example RNA-seq analysis | Running apeglm | Specific coefficients | Modeling zero-inflated counts | Modeling ratios of counts | Session Info | References
Package: apeglm 1.35.0
Anqi Zhu
apeglm: Approximate posterior estimation for GLM coefficients
apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.
Authors:
apeglm_1.35.0.tar.gz
apeglm_1.35.0.zip(r-4.7)apeglm_1.35.0.zip(r-4.6)apeglm_1.35.0.zip(r-4.5)
apeglm_1.35.0.tgz(r-4.6-x86_64)apeglm_1.35.0.tgz(r-4.6-arm64)apeglm_1.35.0.tgz(r-4.5-x86_64)apeglm_1.35.0.tgz(r-4.5-arm64)
apeglm_1.35.0.tar.gz(r-4.7-arm64)apeglm_1.35.0.tar.gz(r-4.7-x86_64)apeglm_1.35.0.tar.gz(r-4.6-arm64)apeglm_1.35.0.tar.gz(r-4.6-x86_64)
apeglm_1.35.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
apeglm/json (API)
| # Install 'apeglm' in R: |
| install.packages('apeglm', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:apeglm-1.35.0(bioc 3.24)apeglm-1.34.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
immunooncologysequencingrnaseqdifferentialexpressiongeneexpressionbayesiancpp
Last updated from:1bac11565b. Checks:1 ERROR, 13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 228 | ||
| linux-devel-arm64 | OK | 295 | ||
| linux-devel-x86_64 | OK | 383 | ||
| source / vignettes | OK | 338 | ||
| linux-release-arm64 | OK | 296 | ||
| linux-release-x86_64 | OK | 388 | ||
| macos-release-arm64 | OK | 242 | ||
| macos-release-x86_64 | OK | 512 | ||
| macos-oldrel-arm64 | OK | 260 | ||
| macos-oldrel-x86_64 | OK | 428 | ||
| windows-devel | OK | 294 | ||
| windows-release | OK | 267 | ||
| windows-oldrel | OK | 339 | ||
| wasm-release | OK | 314 |
Exports:apeglmbbEstDisplogLikNBsvalue
Dependencies:abindbbmlebdsmatrixBiobaseBiocGenericscodaDelayedArrayemdbookgenericsGenomicRangesIRangeslatticeMASSMatrixMatrixGenericsmatrixStatsmvtnormnumDerivplyrRcppRcppEigenRcppNumericalS4ArraysS4VectorsSeqinfoSparseArraySummarizedExperimentXVector
