bioc-issue-bot
commented
6 years ago Hi @averissimo
Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.
The DESCRIPTION file for this package is:
Package: glmSparseNet
Type: Package
Title: Network Centrality Metrics for Elastic-Net Regularized Models
Version: 0.1.8
Authors@R: c(person("André", "Veríssimo", email = "andre.verissimo@tecnico.ulisboa.pt", role = c("aut", "cre")),
person("Susana", "Vinga", email = "susanavinga@tecnico.ulisboa.pt", role = "aut"),
person("Eunice", "Carrasquinha", email = "eunice.trigueirao@tecnico.ulisboa.pt", role = "ctb"),
person("Marta", "Lopes", email = "marta.lopes@tecnico.ulisboa.pt", role = "ctb"))
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".
License: GPL (>=3)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
biocViews: Software,
StatisticalMethod,
DimensionReduction,
Regression,
Classification,
Survival,
Network,
GraphAndNetwork
Depends: R (>= 3.5), Matrix, MultiAssayExperiment, glmnet
Imports: SummarizedExperiment,
STRINGdb,
biomaRt,
futile.logger,
sparsebn,
sparsebnUtils,
forcats,
dplyr,
readr,
ggplot2,
ggfortify,
reshape2,
stats,
stringr,
rlang,
parallel,
methods,
digest
Suggests: testthat,
knitr,
rmarkdown,
survival,
survcomp,
pROC,
devtools,
roxygen2,
VennDiagram,
BiocStyle,
curatedTCGAData
VignetteBuilder: knitr
RoxygenNote: 6.1.0
BugReports: https://www.github.com/sysbiomed/glmSparseNet/issues
URL: https://www.github.com/sysbiomed/glmSparseNet
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averissimo
LiNk-NY
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