1 Introduction | 2 Minimum spanning trees | 3 Statistical methods | 4 Notes on handling RNA-seq count data | 5 Case studies | 6 Session info
Package: GSAR 1.47.0
Yasir Rahmatallah
GSAR: Gene Set Analysis in R
Gene set analysis using specific alternative hypotheses. Tests for differential expression, scale and net correlation structure.
Authors:
GSAR_1.47.0.tar.gz
GSAR_1.47.0.zip(r-4.7)GSAR_1.47.0.zip(r-4.6)GSAR_1.47.0.zip(r-4.5)
GSAR_1.47.0.tgz(r-4.6-any)GSAR_1.47.0.tgz(r-4.5-any)
GSAR_1.47.0.tar.gz(r-4.7-any)GSAR_1.47.0.tar.gz(r-4.6-any)
GSAR_1.47.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GSAR/json (API)
| # Install 'GSAR' in R: |
| install.packages('GSAR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- p53DataSet - P53 Dataset of the NCI-60 Cell Lines
On BioConductor:GSAR-1.47.0(bioc 3.24)GSAR-1.46.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
softwarestatisticalmethoddifferentialexpression
Last updated from:cfe0abe6a2. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 258 | ||
| linux-devel-x86_64 | NOTE | 280 | ||
| source / vignettes | OK | 432 | ||
| linux-release-x86_64 | NOTE | 284 | ||
| macos-release-arm64 | NOTE | 101 | ||
| macos-oldrel-arm64 | NOTE | 114 | ||
| windows-devel | NOTE | 964 | ||
| windows-release | NOTE | 910 | ||
| windows-oldrel | NOTE | 807 | ||
| wasm-release | OK | 221 |
Exports:ADtestAggrFtestCVMtestfindMST2findMST2.PPIGSNCAtestHDP.rankingKStestMDtestplotMST2.pathwayradial.rankingRADtestRCVMtestRKStestRMDtestTestGeneSetsWWtest
Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs
