gaga
This is the released version of gaga; for the devel version, see gaga.
GaGa hierarchical model for high-throughput data analysis
Bioconductor version: Release (3.20)
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).
Author: David Rossell <rosselldavid at gmail.com>.
Maintainer: David Rossell <rosselldavid at gmail.com>
citation("gaga")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("gaga")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("gaga")| Manual for the gaga library | R Script | |
| Reference Manual |
Details
| biocViews | Classification, DifferentialExpression, ImmunoOncology, MassSpectrometry, MultipleComparison, OneChannel, Software |
| Version | 2.52.0 |
| In Bioconductor since | BioC 2.2 (R-2.7) (16.5 years) |
| License | GPL (>= 2) |
| Depends | R (>= 2.8.0), Biobase, coda, EBarrays, mgcv |
| Imports | |
| System Requirements | |
| URL |
See More
| Suggests | |
| Linking To | |
| Enhances | parallel |
| Depends On Me | |
| Imports Me | casper |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | gaga_2.52.0.tar.gz |
| Windows Binary (x86_64) | gaga_2.52.0.zip |
| macOS Binary (x86_64) | gaga_2.52.0.tgz |
| macOS Binary (arm64) | gaga_2.52.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/gaga |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/gaga |
| Bioc Package Browser | https://code.bioconductor.org/browse/gaga/ |
| Package Short Url | https://bioconductor.org/packages/gaga/ |
| Package Downloads Report | Download Stats |