Bioconductor-mirror/gaga: GaGa hierarchical model for high-throughput data analysis
Version 2.23.0

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).

Getting started

Package details

AuthorDavid Rossell <[email protected]>.
Bioconductor views Classification DifferentialExpression MassSpectrometry MultipleComparison OneChannel
MaintainerDavid Rossell <[email protected]>
LicenseGPL (>= 2)
Version2.23.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("Bioconductor-mirror/gaga")
Bioconductor-mirror/gaga documentation built on June 1, 2017, 9:36 a.m.