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BayesSurvive: Bayesian Survival Models for High-Dimensional Data
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>).
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Package details |
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| 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@medisin.uio.no> |
| License | GPL-3 |
| Version | 0.1.0 |
| URL | https://github.com/ocbe-uio/BayesSurvive |
| Package repository | View on CRAN |
| Installation |
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