Package: gaga 2.53.0

David Rossell

gaga: GaGa hierarchical model for high-throughput data analysis

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).

Authors:David Rossell <[email protected]>.

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gaga.pdf |gaga.html✨
gaga/json (API)

# Install 'gaga' in R:
install.packages('gaga', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

On BioConductor:gaga-2.53.0(bioc 3.21)gaga-2.52.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncologyonechannelmassspectrometrymultiplecomparisondifferentialexpressionclassification

4.08 score 1 packages 9 scripts 303 downloads 2 mentions 24 exports 10 dependencies

Last updated 4 months agofrom:71fadde79f. Checks:1 OK, 1 NOTE, 9 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 29 2025
R-4.5-win-x86_64WARNINGJan 29 2025
R-4.5-mac-x86_64WARNINGJan 29 2025
R-4.5-mac-aarch64WARNINGJan 29 2025
R-4.5-linux-x86_64NOTEJan 29 2025
R-4.4-win-x86_64WARNINGJan 29 2025
R-4.4-mac-x86_64WARNINGJan 29 2025
R-4.4-mac-aarch64WARNINGJan 29 2025
R-4.3-win-x86_64WARNINGJan 29 2025
R-4.3-mac-x86_64WARNINGJan 29 2025
R-4.3-mac-aarch64WARNINGJan 29 2025

Exports:adjustfitNNbuildPatternscheckfitclasspreddcgammafindgenesfitGGfitNNfitNNSingleHypforwsimDiffExprgeneclusgetparmcgammaparestplotForwSimposmeansGGpowclasspredpowfindgenesrcgammaseqBoundariesGridsimGGsimLNNsimnewsamplessimNN

Dependencies:BiobaseBiocGenericsclustercodaEBarraysgenericslatticeMatrixmgcvnlme

Manual for the gaga library

Rendered fromgagamanual.Rnwusingutils::Sweaveon Jan 29 2025.

Last update: 2013-11-01
Started: 2013-11-01

Readme and manuals

Help Manual

Help pageTopics
Build a matrix with all possible patterns given a number of groups where samples may belong to.buildPatterns
Check goodness-of-fit of GaGa and MiGaGa modelscheckfit checkfit.gagafit
Predict the class that a new sample belongs to.classpred classpred.gagafit
Approximate gamma shape distributiondcgamma mcgamma rcgamma
Find differentially expressed genes after GaGa or Normal-Normal fit.findgenes findgenes.gagafit findgenes.nnfit
Fit GaGa hierarchical modeladjustfitNN fitGG fitNN fitNNSingleHyp
Forward simulation for differential expression.forwsimDiffExpr forwsimDiffExpr.gagafit forwsimDiffExpr.nnfit
Cluster genes into expression patterns.geneclus geneclus.gagafit
Extract hyper-parameter estimates from a gagafit or nnfit objectgetpar getpar.gagafit getpar.nnfit
Parameter estimates and posterior probabilities of differential expression for GaGa and MiGaGa modelparest parest.gagafit
Plot forward simulation trajectoriesplotForwSim
Gene-specific posterior meansposmeansGG posmeansGG.gagafit
Expected probability that a future sample is correctly classified.powclasspred powclasspred.gagafit
Power computations for differential expressionpowfindgenes
Print an object of class gagaclusprint.gagaclus
Print an object of class gagafit or nnfitprint.gagafit print.nnfit
Print an object of class gagahypprint.gagahyp
Evaluate expected utility for parametric sequential stopping boundaries.seqBoundariesGrid
Prior predictive simulationsimGG simLNN simNN
Posterior predictive simulationsimnewsamples simnewsamples.gagafit simnewsamples.nnfit