iClusterVB: Fast Integrative Clustering and Feature Selection for High
Dimensional 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 + file LICENSE |
| URL: |
https://github.com/AbdalkarimA/iClusterVB |
| NeedsCompilation: |
yes |
| Materials: |
README |
| CRAN checks: |
iClusterVB results |
Documentation:
Downloads:
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