iClusterVB: Fast Integrative Clustering and Feature Selection for HighDimensional Data
A variational Bayesian approach for fast integrative clustering and feature selection, facilitating the analysis of multi-view, mixed type, high-dimensional datasets with applications in fields like cancer research, genomics, and more.
| Version: | 0.1.4 |
| Depends: | R (≥ 4.0.0) |
| Imports: | cluster,clustMixType,cowplot,ggplot2, graphics, grDevices,mclust,MCMCpack,mvtnorm,pheatmap,poLCA,Rcpp (≥ 1.0.12), stats, utils,VarSelLCM |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | knitr,rmarkdown,survival,survminer |
| Published: | 2024-12-09 |
| DOI: | 10.32614/CRAN.package.iClusterVB |
| Author: | Abdalkarim Alnajjar [aut, cre, cph], Zihang Lu [aut] |
| Maintainer: | Abdalkarim Alnajjar <abdalkarim.alnajjar at queensu.ca> |
| BugReports: | https://github.com/AbdalkarimA/iClusterVB/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/AbdalkarimA/iClusterVB |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | iClusterVB results |
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