glmSparseNet is an Rpackage that generalizes sparse regression models when the features (e.g. genes) have a graph structure (e.g. proteinprotein interactions), by including networkbased regularizers. glmSparseNet uses the glmnet Rpackage, by including centrality measures of the network as penalty weights in the regularization. The current version implements regularization based on node degree, i.e. the strength and/or number of its associated edges, either by promoting hubs in the solution or orphan genes in the solution. All the glmnet distribution families are supported, namely "gaussian", "poisson", "binomial", "multinomial", "cox", and "mgaussian".
Package details 


Author  André Veríssimo [aut, cre], Susana Vinga [aut], Eunice Carrasquinha [ctb], Marta Lopes [ctb] 
Bioconductor views  Classification DimensionReduction GraphAndNetwork Network Regression Software StatisticalMethod Survival 
Maintainer  André Veríssimo <[email protected]> 
License  GPL (>=3) 
Version  1.2.0 
URL  https://www.github.com/sysbiomed/glmSparseNet 
Package repository  View on Bioconductor 
Installation 
Install the latest version of this package by entering the following in R:

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