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gaga

GaGa hierarchical model for high-throughput data analysis

Bioconductor version: 3.23 · Package version: 2.58.0

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).

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("gaga")

Details

MaintainerDavid Rossell <rosselldavid@gmail.com>
AuthorDavid Rossell <rosselldavid@gmail.com>.
LicenseGPL (>= 2)
Downloads rank616
Source branchRELEASE_3_23
biocViewsClassification, DifferentialExpression, ImmunoOncology, MassSpectrometry, MultipleComparison, OneChannel, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagegaga_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
Dependencies

Depends: R (>= 2.8.0), Biobase, coda, EBarrays, mgcv

Enhances: parallel

Reverse dependencies

Imports Me (1): casper