Package: fabia 2.59.0

Andreas Mitterecker

fabia: FABIA: Factor Analysis for Bicluster Acquisition

Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C.

Authors:Sepp Hochreiter <[email protected]>

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manual.pdf |manual.html✨
card.svg |card.png
fabia/json (API)
NEWS

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

On BioConductor:fabia-2.59.0(bioc 3.24)fabia-2.58.0(bioc 3.23)

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

statisticalmethodmicroarraydifferentialexpressionmultiplecomparisonclusteringvisualization

5.50 score 2 packages 44 scripts 587 downloads 6 mentions 66 exports 3 dependencies

Last updated from:13fa2a6383. Checks:1 ERROR, 11 WARNING, 2 OK. Indexed: yes.

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source / vignettesOK174
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Exports:aviniavini<-centercenter<-estimateModeextractBicextractPlotfabifabiafabiaDemofabiapfabiasfabiaspfabiaVersioniniini<-lLl<-L<-laplalapla<-LZLZ<-MM<-makeFabiaDatamakeFabiaDataBlocksmakeFabiaDataBlocksPosmakeFabiaDataPosmatrixImagePlotmfscnn<-nmfdivnmfeunmfscp1p1<-p2p2<-parametersparameters<-plotplotBiclusterprojFuncprojFuncPosPsiPsi<-readSamplesSpfabiareadSpfabiaResultsamplesPerFeaturescaleDatascaleData<-showshowSelectedspfabiasummaryUU<-XX<-xavinixavini<-ZZ<-

Dependencies:BiobaseBiocGenericsgenerics

FABIA: Manual for the R package

Rendered fromfabia.Rnwusingutils::Sweaveon May 30 2026.

Last update: 2019-01-23
Started: 2012-03-27

Readme and manuals

Help Manual

Help pageTopics
Estimation of the modes of the rows of a matrixestimateMode
Extraction of BiclustersextractBic
Plotting of Biclustering ResultsextractPlot
Factor Analysis for Bicluster Acquisition: Laplace Prior (FABI)fabi
Factor Analysis for Bicluster Acquisition: Laplace Prior (FABIA)fabia
Demos for fabiafabiaDemo
Factor Analysis for Bicluster Acquisition: Post-Projection (FABIAP)fabiap
Factor Analysis for Bicluster Acquisition: Sparseness Projection (FABIAS)fabias
Factor Analysis for Bicluster Acquisition: Sparseness Projection (FABIASP)fabiasp
Display version info for package and for FABIAfabiaVersion
Factorization instancesavini avini,Factorization-method avini<- avini<-,Factorization,numeric-method avini<-,Factorization,vector-method center center,Factorization-method center<- center<-,Factorization,numeric-method center<-,Factorization,vector-method Factorization Factorization,ANY-method Factorization,list-method,numeric-method,vector-method,matrix-method,ANY-method Factorization-class Factorization-method ini ini,Factorization-method ini<- ini<-,Factorization,matrix-method L l L,Factorization-method l,Factorization-method L<- l<- L<-,Factorization,matrix-method l<-,Factorization,numeric-method lapla lapla,Factorization-method lapla<- lapla<-,Factorization,matrix-method LZ LZ,Factorization-method LZ<- LZ<-,Factorization,matrix-method M M,Factorization-method M<- M<-,Factorization,matrix-method n n,Factorization-method n<- n<-,Factorization,numeric-method p1 p1,Factorization-method p1<- p1<-,Factorization,numeric-method p2 p2,Factorization-method p2<- p2<-,Factorization,numeric-method parameters parameters,Factorization-method parameters<- parameters<-,Factorization,list-method plot,Factorization,missing-method plot,Factorization-method Psi Psi,Factorization-method Psi<- Psi<-,Factorization,numeric-method Psi<-,Factorization,vector-method scaleData scaleData,Factorization-method scaleData<- scaleData<-,Factorization,numeric-method scaleData<-,Factorization,vector-method show,Factorization-method showSelected showSelected,Factorization,numeric-method showSelected,Factorization-method summary,Factorization-method U U,Factorization-method U<- U<-,Factorization,matrix-method X X,Factorization-method X<- X<-,Factorization,matrix-method xavini xavini,Factorization-method xavini<- xavini<-,Factorization,numeric-method xavini<-,Factorization,vector-method Z Z,Factorization-method Z<- Z<-,Factorization,matrix-method
Generation of Bicluster DatamakeFabiaData
Generation of Bicluster Data with Bicluster BlocksmakeFabiaDataBlocks
Generation of Bicluster Data with Bicluster BlocksmakeFabiaDataBlocksPos
Generation of Bicluster DatamakeFabiaDataPos
Plotting of a MatrixmatrixImagePlot
Sparse Matrix Factorization for Bicluster Analysis (MFSC)mfsc
Non-negative Matrix Factorization: Kullback-Leibler Divergencenmfdiv
Non-negative Matrix Factorization: Euclidean Distancenmfeu
Non-negative Sparse Matrix Factorizationnmfsc
Plotting of a biclusterplotBicluster
Projection of a Vector to a Sparse VectorprojFunc
Projection of a Vector to a Non-negative Sparse VectorprojFuncPos
Factor Analysis for Bicluster Acquisition: Read Sparse Matrix SamplesreadSamplesSpfabia
Factor Analysis for Bicluster Acquisition: Read Results of SpFabiareadSpfabiaResult
Factor Analysis for Bicluster Acquisition: Supplies samples per featuresamplesPerFeature
Factor Analysis for Bicluster Acquisition: SPARSE FABIAspfabia