diffee: Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure

This is an R implementation of Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure (DIFFEE). The DIFFEE algorithm can be used to fast estimate the differential network between two related datasets. For instance, it can identify differential gene network from datasets of case and control. By performing data-driven network inference from two high-dimensional data sets, this tool can help users effectively translate two aggregated data blocks into knowledge of the changes among entities between two Gaussian Graphical Model. Please run demo(diffeeDemo) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi (2018) <doi:10.48550/arXiv.1710.11223>.

Version:	1.1.0
Depends:	R (≥ 3.0.0), igraph, pcaPP
Published:	2018-07-03
DOI:	10.32614/CRAN.package.diffee
Author:	Beilun Wang [aut, cre], Yanjun Qi [aut], Zhaoyang Wang [aut]
Maintainer:	Beilun Wang <bw4mw at virginia.edu>
BugReports:	https://github.com/QData/DIFFEE
License:	GPL-2
URL:	https://github.com/QData/DIFFEE
NeedsCompilation:	no
CRAN checks:	diffee results

Documentation:

Reference manual:

diffee.pdf

Downloads:

Package source:	diffee_1.1.0.tar.gz
Windows binaries:	r-devel: diffee_1.1.0.zip, r-release: diffee_1.1.0.zip, r-oldrel: diffee_1.1.0.zip
macOS binaries:	r-release (arm64): diffee_1.1.0.tgz, r-oldrel (arm64): diffee_1.1.0.tgz, r-release (x86_64): diffee_1.1.0.tgz, r-oldrel (x86_64): diffee_1.1.0.tgz
Old sources:	diffee archive

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