GRridge: Better prediction by use of co-data: Adaptive group-regularized ridge regression

This package allows the use of multiple sources of co-data (e.g. external p-values, gene lists, annotation) to improve prediction of binary, continuous and survival response using (logistic, linear or Cox) group-regularized ridge regression. It also facilitates post-hoc variable selection and prediction diagnostics by cross-validation using ROC curves and AUC.

Package details

AuthorMark A. van de Wiel <>, Putri W. Novianti <>
Bioconductor views Bayesian Classification GO GeneExpression GenePrediction GeneSetEnrichment GraphAndNetwork ImmunoOncology KEGG Pathways RNASeq Regression Survival
MaintainerMark A. van de Wiel <>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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GRridge documentation built on Nov. 8, 2020, 5:47 p.m.