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glmSparseNet

This is the development version of glmSparseNet; for the stable release version, see glmSparseNet.

Network Centrality Metrics for Elastic-Net Regularized Models


Bioconductor version: Development (3.19)

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: André Veríssimo [aut, cre] , Susana Vinga [aut], Eunice Carrasquinha [ctb], Marta Lopes [ctb]

Maintainer: André Veríssimo <andre.verissimo at tecnico.ulisboa.pt>

Citation (from within R, enter citation("glmSparseNet")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("glmSparseNet")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("glmSparseNet")
Breast survival dataset using network from STRING DB HTML R Script
Example for Classification -- Breast Invasive Carcinoma HTML R Script
Example for Survival Data -- Breast Invasive Carcinoma HTML R Script
Example for Survival Data -- Prostate Adenocarcinoma HTML R Script
Example for Survival Data -- Skin Melanoma HTML R Script
Separate 2 groups in Cox regression HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, DimensionReduction, GraphAndNetwork, Network, Regression, Software, StatisticalMethod, Survival
Version 1.21.2
In Bioconductor since BioC 3.8 (R-3.5) (5.5 years)
License GPL-3
Depends R (>= 4.3.0)
Imports biomaRt, checkmate, dplyr, forcats, futile.logger, ggplot2, glue, httr, lifecycle, methods, parallel, readr, rlang, glmnet, Matrix, MultiAssayExperiment, SummarizedExperiment, survminer, TCGAutils, utils
System Requirements
URL https://www.github.com/sysbiomed/glmSparseNet
Bug Reports https://www.github.com/sysbiomed/glmSparseNet/issues
See More
Suggests BiocStyle, curatedTCGAData, knitr, magrittr, reshape2, pROC, rmarkdown, survival, testthat, VennDiagram, withr
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package glmSparseNet_1.21.2.tar.gz
Windows Binary glmSparseNet_1.21.2.zip (64-bit only)
macOS Binary (x86_64) glmSparseNet_1.21.2.tgz
macOS Binary (arm64) glmSparseNet_1.21.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/glmSparseNet
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/glmSparseNet
Bioc Package Browser https://code.bioconductor.org/browse/glmSparseNet/
Package Short Url https://bioconductor.org/packages/glmSparseNet/
Package Downloads Report Download Stats