glmSparseNet

DOI: 10.18129/B9.bioc.glmSparseNet    

Network Centrality Metrics for Elastic-Net Regularized Models

Bioconductor version: Release (3.8)

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 and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("glmSparseNet", version = "3.8")

Documentation

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

browseVignettes("glmSparseNet")

 

HTML R Script 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
PDF   Reference Manual
Text   NEWS

Details

biocViews Classification, DimensionReduction, GraphAndNetwork, Network, Regression, Software, StatisticalMethod, Survival
Version 1.0.0
License GPL (>=3)
Depends R (>= 3.5), Matrix, MultiAssayExperiment, glmnet
Imports SummarizedExperiment, STRINGdb, biomaRt, futile.logger, sparsebn, sparsebnUtils, forcats, dplyr, readr, ggplot2, survminer, reshape2, stats, stringr, rlang, parallel, methods, loose.rock
LinkingTo
Suggests testthat, knitr, rmarkdown, survival, survcomp, pROC, VennDiagram, BiocStyle, curatedTCGAData, TCGAutils
SystemRequirements
Enhances
URL https://www.github.com/sysbiomed/glmSparseNet
BugReports https://www.github.com/sysbiomed/glmSparseNet/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package glmSparseNet_1.0.0.tar.gz
Windows Binary glmSparseNet_1.0.0.zip
Mac OS X 10.11 (El Capitan) glmSparseNet_1.0.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/glmSparseNet
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/glmSparseNet
Package Short Url http://bioconductor.org/packages/glmSparseNet/
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