To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("gaga")

In most cases, you don't need to download the package archive at all.

gaga

GaGa hierarchical model for high-throughput data analysis

Bioconductor version: Release (2.14)

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>

To install this package, start R and enter:

Citation (from within R, enter citation("gaga")):

Installation

source("http://bioconductor.org/biocLite.R")
biocLite("gaga")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("gaga")

 

PDF R Script Manual for the gaga library
PDF   Reference Manual

Details

biocViews Classification, DifferentialExpression, MassSpectrometry, MultipleComparison, OneChannel, Software
Version 2.10.0
In Bioconductor since BioC 2.2 (R-2.7)
License GPL (>= 2)
Depends R (>= 2.8.0), Biobase, coda, EBarrays, mgcv
Imports
Suggests
System Requirements
URL
Depends On Me
Imports Me casper
Suggests Me

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source gaga_2.10.0.tar.gz
Windows Binary gaga_2.10.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) gaga_2.10.0.tgz
Mac OS X 10.9 (Mavericks) gaga_2.10.0.tgz
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