Package: iBBiG 1.51.0
Aedin Culhane
iBBiG: Iterative Binary Biclustering of Genesets
iBBiG is a bi-clustering algorithm which is optimizes for binary data analysis. We apply it to meta-gene set analysis of large numbers of gene expression datasets. The iterative algorithm extracts groups of phenotypes from multiple studies that are associated with similar gene sets. iBBiG does not require prior knowledge of the number or scale of clusters and allows discovery of clusters with diverse sizes
Authors:
iBBiG_1.51.0.tar.gz
iBBiG_1.51.0.zip(r-4.5)iBBiG_1.51.0.zip(r-4.4)iBBiG_1.51.0.zip(r-4.3)
iBBiG_1.51.0.tgz(r-4.5-x86_64)iBBiG_1.51.0.tgz(r-4.5-arm64)iBBiG_1.51.0.tgz(r-4.4-x86_64)iBBiG_1.51.0.tgz(r-4.4-arm64)iBBiG_1.51.0.tgz(r-4.3-x86_64)iBBiG_1.51.0.tgz(r-4.3-arm64)
iBBiG_1.51.0.tar.gz(r-4.5-noble)iBBiG_1.51.0.tar.gz(r-4.4-noble)
iBBiG_1.51.0.tgz(r-4.4-emscripten)iBBiG_1.51.0.tgz(r-4.3-emscripten)
iBBiG.pdf |iBBiG.html✨
iBBiG/json (API)
| # Install 'iBBiG' in R: |
| install.packages('iBBiG', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:iBBiG-1.51.0(bioc 3.21)iBBiG-1.50.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
clusteringannotationgenesetenrichment
Last updated 4 months agofrom:370a007699. Checks:1 OK, 10 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 28 2025 |
| R-4.5-win-x86_64 | NOTE | Jan 28 2025 |
| R-4.5-mac-x86_64 | NOTE | Jan 28 2025 |
| R-4.5-mac-aarch64 | NOTE | Jan 28 2025 |
| R-4.5-linux-x86_64 | NOTE | Jan 28 2025 |
| R-4.4-win-x86_64 | NOTE | Jan 28 2025 |
| R-4.4-mac-x86_64 | NOTE | Jan 28 2025 |
| R-4.4-mac-aarch64 | NOTE | Jan 28 2025 |
| R-4.3-win-x86_64 | NOTE | Jan 28 2025 |
| R-4.3-mac-x86_64 | NOTE | Jan 28 2025 |
| R-4.3-mac-aarch64 | NOTE | Jan 28 2025 |
Exports:analyzeClustClusterscoresiBBiGinfoJIdistmakeArtificialmakeSimDesignMatNumberNumberxColParametersplotRowScorexNumberRowxNumberSeeddatashowsummary
Dependencies:additivityTestsade4biclustclassclicolorspacecpp11dplyrfansifarverflexclustgenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmodeltoolsmunsellnlmepillarpixmappkgconfigpurrrR6RColorBrewerRcppRcppArmadillorlangscalesspstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxtable
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| iBBiG performs bi-clustering of binary matrices | iBBiG-package |
| Iterative Binary Bi-Clustering for GeneSets | iBBiG |
| Class '"iBBiG"' | analyzeClust analyzeClust,Biclust,iBBiG-method analyzeClust,iBBiG,iBBiG-method analyzeClust,list,iBBiG-method Clusterscores Clusterscores,iBBiG-method Clusterscores<- iBBiG-class info info,iBBiG-method info<- JIdist JIdist,Biclust,Biclust-method JIdist,Biclust,iBBiG-method JIdist,iBBiG,iBBiG-method Number Number,iBBiG-method Number<- NumberxCol NumberxCol,iBBiG-method NumberxCol<- Parameters Parameters,iBBiG-method Parameters<- plot,iBBiG,ANY-method RowScorexNumber RowScorexNumber,iBBiG-method RowScorexNumber<- RowxNumber RowxNumber,iBBiG-method RowxNumber<- Seeddata Seeddata,iBBiG-method Seeddata<- show,iBBiG-method summary,iBBiG-method [,iBBiG-method |
| Create a 400x400 simulated binary matrix for testing iBBiG and other binary biclustering methods | addSignal makeArtificial makeSimDesignMat |
