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 <[email protected]>, Putri W. Novianti <[email protected]>
Bioconductor views Bayesian Classification GO GeneExpression GenePrediction GeneSetEnrichment GraphAndNetwork KEGG Pathways RNASeq Regression Survival
MaintainerMark A. van de Wiel <[email protected]>
LicenseGPL-3
Version1.6.0
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("GRridge")

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GRridge documentation built on Nov. 1, 2018, 3:37 a.m.