An implementation of Bayesian survival models with graph-structured selection priors for sparse identification of omics features predictive of survival (Madjar et al., 2021 <doi:10.1186/s12859-021-04483-z>) and its extension to use a fixed graph via a Markov Random Field (MRF) prior for capturing known structure of omics features, e.g. disease-specific pathways from the Kyoto Encyclopedia of Genes and Genomes database (Hermansen et al., 2025 <doi:10.48550/arXiv.2503.13078>).
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | Rcpp,ggplot2,GGally,mvtnorm,survival,riskRegression, utils, stats, methods |
| LinkingTo: | Rcpp,RcppArmadillo,testthat |
| Suggests: | knitr,testthat,Matrix |
| Published: | 2025-03-25 |
| DOI: | 10.32614/CRAN.package.BayesSurvive |
| Author: | Zhi Zhao [aut, cre], Waldir Leoncio [aut], Katrin Madjar [aut], Tobias Østmo Hermansen [aut], Manuela Zucknick [ctb], Jörg Rahnenführer [ctb] |
| Maintainer: | Zhi Zhao <zhi.zhao at medisin.uio.no> |
| BugReports: | https://github.com/ocbe-uio/BayesSurvive/issues |
| License: | GPL-3 |
| URL: | https://github.com/ocbe-uio/BayesSurvive |
| NeedsCompilation: | yes |
| Citation: | BayesSurvive citation info |
| Materials: | README,NEWS |
| In views: | Survival |
| CRAN checks: | BayesSurvive results |