Package: survClust
Title: Identification Of Clinically Relevant Genomic Subtypes Using
        Outcome Weighted Learning
Version: 1.4.0
Date: 2024-04-16
Authors@R: 
    person("Arshi", "Arora", , "arshiaurora@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-4040-1787"))
Description: 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).
VignetteBuilder: knitr
License: MIT + file LICENSE
Imports: Rcpp, MultiAssayExperiment, pdist, survival
LinkingTo: Rcpp
URL: https://github.com/arorarshi/survClust
BugReports: https://support.bioconductor.org/t/survClust
biocViews: Software, Clustering, Survival, Classification
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
LazyData: true
Depends: R (>= 3.5.0)
Suggests: knitr, testthat (>= 3.0.0), gplots, htmltools, BiocParallel
Config/testthat/edition: 3
Config/pak/sysreqs: libicu-dev zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-10-29 15:30:24 UTC
RemoteUrl: https://github.com/bioc/survClust
RemoteRef: RELEASE_3_22
RemoteSha: b744e5d0ddbce85d1955a4d36a7681d659759951
NeedsCompilation: yes
Packaged: 2026-01-24 20:41:48 UTC; root
Author: Arshi Arora [aut, cre] (ORCID: <https://orcid.org/0000-0002-4040-1787>)
Maintainer: Arshi Arora <arshiaurora@gmail.com>
Built: R 4.5.2; x86_64-w64-mingw32; 2026-01-24 20:43:30 UTC; windows
Archs: x64
