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) <arXiv:1710.11223>.

Version: 1.0.0
Depends: R (≥ 3.0.0), igraph
Published: 2018-03-06
Author: Beilun Wang [aut, cre], Yanjun Qi [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

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Reference manual: diffee.pdf
Package source: diffee_1.0.0.tar.gz
Windows binaries: r-devel: diffee_1.0.0.zip, r-release: diffee_1.0.0.zip, r-oldrel: diffee_1.0.0.zip
OS X binaries: r-release: diffee_1.0.0.tgz, r-oldrel: diffee_1.0.0.tgz

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