CRAN/E | SILGGM

SILGGM

Statistical Inference of Large-Scale Gaussian Graphical Model in Gene Networks

Installation

About

Provides a general framework to perform statistical inference of each gene pair and global inference of whole-scale gene pairs in gene networks using the well known Gaussian graphical model (GGM) in a time-efficient manner. We focus on the high-dimensional settings where p (the number of genes) is allowed to be far larger than n (the number of subjects). Four main approaches are supported in this package: (1) the bivariate nodewise scaled Lasso (Ren et al (2015) doi:10.1214/14-AOS1286) (2) the de-sparsified nodewise scaled Lasso (Jankova and van de Geer (2017) doi:10.1007/s11749-016-0503-5) (3) the de-sparsified graphical Lasso (Jankova and van de Geer (2015) doi:10.1214/15-EJS1031) (4) the GGM estimation with false discovery rate control (FDR) using scaled Lasso or Lasso (Liu (2013) doi:10.1214/13-AOS1169). Windows users should install 'Rtools' before the installation of this package.

Key Metrics

Version 1.0.0
R ≥ 3.0.0
Published 2017-10-16 2432 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks SILGGM results

Downloads

Yesterday 0
Last 7 days 14 -62%
Last 30 days 119 -34%
Last 90 days 424 -23%
Last 365 days 1.721 -26%

Maintainer

Maintainer

Rong Zhang

Authors

Rong Zhang
Zhao Ren
Wei Chen

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.0.0
Rcpp

Imports

glasso
MASS
reshape
utils

LinkingTo

Rcpp

Reverse Suggests

SEMgraph