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 1.46.0
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_1.46.0.tar.gz
GSAR_1.46.0.zip(r-4.7-any)GSAR_1.46.0.zip(r-4.6-any)GSAR_1.46.0.zip(r-4.5-any)
GSAR_1.46.0.tgz(r-4.6-any)GSAR_1.46.0.tgz(r-4.5-any)
GSAR_1.46.0.tar.gz(r-4.7-any)GSAR_1.46.0.tar.gz(r-4.6-any)
GSAR_1.46.0.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-release.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:06dfaa42f3 (on RELEASE_3_23). Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 223 | ||
| linux-devel | NOTE | 318 | ||
| source / vignettes | OK | 458 | ||
| linux-release | NOTE | 254 | ||
| macos-release | NOTE | 158 | ||
| macos-oldrel | NOTE | 142 | ||
| windows-devel | NOTE | 668 | ||
| windows-release | NOTE | 982 | ||
| windows-oldrel | NOTE | 810 | ||
| wasm-release | OK | 197 |
Exports:ADtestAggrFtestCVMtestfindMST2findMST2.PPIGSNCAtestHDP.rankingKStestMDtestplotMST2.pathwayradial.rankingRADtestRCVMtestRKStestRMDtestTestGeneSetsWWtest
Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs
