survClust
Identification Of Clinically Relevant Genomic Subtypes Using Outcome Weighted Learning
Bioconductor version: 3.23 · Package version: 1.6.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
survClust is an outcome weighted integrative clustering algorithm used to classify multi-omic samples on their available time to event information. The resulting clusters are cross-validated to avoid over overfitting and output classification of samples that are molecularly distinct and clinically meaningful. It takes in binary (mutation) as well as continuous data (other omic types).
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("survClust")Details
| Maintainer | Arshi Arora <arshiaurora@gmail.com> |
| Author | Arshi Arora [aut, cre] (ORCID: <https://orcid.org/0000-0002-4040-1787>) |
| License | MIT + file LICENSE |
| URL | https://github.com/arorarshi/survClust |
| Bug Reports | https://support.bioconductor.org/t/survClust |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Classification, Clustering, Software, Survival |
| Package Short Url | https://bioconductor.org/packages/survClust/ |
Citation
From within R, enter citation("survClust"):
Arshi Arora. survClust: Identification Of Clinically Relevant Genomic Subtypes Using Outcome Weighted Learning. doi:10.18129/B9.bioc.survClust, R package version 1.6.0, https://bioconductor.org/packages/survClust.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | survClust_1.6.0.tar.gz |
| Windows binary (x86_64) | survClust_1.6.0.zip |
| macOS binary (arm64) | survClust_1.6.0.tgz |
| macOS binary (x86_64) | survClust_1.6.0.tgz |
Dependencies
Depends: R (>= 3.5.0)
Imports: Rcpp, MultiAssayExperiment, pdist, survival
LinkingTo: Rcpp
Suggests: knitr, testthat (>= 3.0.0), gplots, htmltools, BiocParallel