glmSparseNet-package: glmSparseNet: Network Centrality Metrics for Elastic-Net...

In sysbiomed/glmSparseNet: Network Centrality Metrics for Elastic-Net Regularized Models

glmSparseNet: Network Centrality Metrics for Elastic-Net Regularized Models

Description

glmSparseNet is an R-package that generalizes sparse regression models when the features (e.g. genes) have a graph structure (e.g. protein-protein interactions), by including network-based regularizers. glmSparseNet uses the glmnet R-package, 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".

Author(s)

Maintainer: André Veríssimo [e-mail] (ORCID)

Authors:

• Susana Vinga [e-mail]

Other contributors:

• Eunice Carrasquinha [e-mail] [contributor]

• Marta Lopes [e-mail] [contributor]

See Also

Useful links:

• https://www.github.com/sysbiomed/glmSparseNet

• Report bugs at https://www.github.com/sysbiomed/glmSparseNet/issues

sysbiomed/glmSparseNet documentation built on Feb. 17, 2024, 1:38 p.m.