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.
- Version0.0.2
- R version≥ 4.0
- LicenseGPL-3
- Needs compilation?Yes
- Last release06/04/2024
Documentation
Team
Zhi Zhao
Manuela Zucknick
Show author detailsRolesContributorKatrin Madjar
Show author detailsRolesAuthorTobias Østmo Hermansen
Show author detailsRolesAuthorJörg Rahnenführer
Show author detailsRolesContributor
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- Imports6 packages
- Suggests1 package
- Linking To2 packages