JGL: Performs the Joint Graphical Lasso for sparse inverse covariance estimation on multiple classes
Version 2.3

The Joint Graphical Lasso is a generalized method for estimating Gaussian graphical models/ sparse inverse covariance matrices/ biological networks on multiple classes of data. We solve JGL under two penalty functions: The Fused Graphical Lasso (FGL), which employs a fused penalty to encourage inverse covariance matrices to be similar across classes, and the Group Graphical Lasso (GGL), which encourages similar network structure between classes. FGL is recommended over GGL for most applications.

AuthorPatrick Danaher
Date of publication2013-04-16 21:27:09
MaintainerPatrick Danaher <pdanaher@uw.edu>
LicenseGPL-2
Version2.3
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("JGL")

Getting started

Package overview

Popular man pages

crit: Calculate the critical value of the FGL objective funciton.
example.data: Toy two-class gene expression dataset.
JGL: Joint Graphical Lasso
net.degree: List the degree of every node in all classes.
net.edges: List the edges in a network
net.hubs: Get degrees of most connected nodes.
screen.fgl: Quickly identify connected features in the solution to FGL
See all...

All man pages Function index File listing

Man pages

crit: Calculate the critical value of the FGL objective funciton.
example.data: Toy two-class gene expression dataset.
gcrit: Calculate the critical value of the GGL objective funciton.
JGL: Joint Graphical Lasso
JGL-internal: Internal JGL functions
JGL-package: Joint Graphical Lasso
net.degree: List the degree of every node in all classes.
net.edges: List the edges in a network
net.hubs: Get degrees of most connected nodes.
net.neighbors: Get network neighbors of a node
screen.fgl: Quickly identify connected features in the solution to FGL
screen.ggl: Quickly identify connected features in the solution to GGL
subnetworks: Identify subnetwork membership

Functions

JGL Man page Source code
JGL-package Man page
admm.iters Source code
admm.iters.unconnected Source code
crit Man page Source code
dsgl Source code
example.data Man page
flsa.general Source code
flsa2 Source code
gcrit Man page Source code
make.adj.matrix Source code
net.degree Man page Source code
net.edges Man page Source code
net.hubs Man page Source code
net.neighbors Man page Source code
penalty.as.matrix Source code
plot.jgl Man page Source code
print.jgl Man page Source code
screen.fgl Man page Source code
screen.ggl Man page Source code
soft Source code
subnetworks Man page Source code

Files

MD5
data
data/example.data.rda
man
man/crit.Rd
man/screen.ggl.Rd
man/JGL-internal.Rd
man/net.degree.Rd
man/gcrit.Rd
man/example.data.Rd
man/JGL.Rd
man/net.hubs.Rd
man/screen.fgl.Rd
man/subnetworks.Rd
man/net.neighbors.Rd
man/JGL-package.Rd
man/net.edges.Rd
R
R/admm.iters.r
R/net.edges.R
R/screen.fgl.R
R/make.adj.matrix.R
R/penalty.as.matrix.R
R/gcrit.R
R/admm.iters.unconnected.r
R/subnetworks.R
R/flsa2.R
R/crit.R
R/screen.ggl.R
R/soft.R
R/net.degree.R
R/flsa.general.R
R/JGL.r
R/net.neighbors.R
R/net.hubs.R
R/dsgl.R
DESCRIPTION
NAMESPACE
JGL documentation built on May 19, 2017, 7:25 p.m.

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