gaga
GaGa hierarchical model for high-throughput data analysis
Bioconductor version: 3.23 · Package version: 2.58.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Implements the GaGa model for high-throughput data analysis, including differential expression analysis, supervised gene clustering and classification. Additionally, it performs sequential sample size calculations using the GaGa and LNNGV models (the latter from EBarrays package).
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("gaga")Details
| Maintainer | David Rossell <rosselldavid@gmail.com> |
| Author | David Rossell <rosselldavid@gmail.com>. |
| License | GPL (>= 2) |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Classification, DifferentialExpression, ImmunoOncology, MassSpectrometry, MultipleComparison, OneChannel, Software |
| Package Short Url | https://bioconductor.org/packages/gaga/ |
Citation
From within R, enter citation("gaga"):
David Rossell. gaga: GaGa hierarchical model for high-throughput data analysis. doi:10.18129/B9.bioc.gaga, R package version 2.58.0, https://bioconductor.org/packages/gaga.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | gaga_2.58.0.tar.gz |
| Windows binary (x86_64) | gaga_2.58.0.zip |
| macOS binary (arm64) | gaga_2.58.0.tgz |
| macOS binary (x86_64) | gaga_2.58.0.tgz |
Reverse dependencies
Imports Me (1): casper