simule: A Constrained L1 Minimization Approach for Estimating Multiple Sparse Gaussian or Nonparanormal Graphical Models

This is an R implementation of a constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models (SIMULE). The SIMULE algorithm can be used to estimate multiple related precision matrices. For instance, it can identify context-specific gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogenous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(simule) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Ritambhara Singh, Yanjun Qi (2017) <doi:10.1007/s10994-017-5635-7>.

Version: 1.1.1
Depends: R (≥ 3.0.0), lpSolve, pcaPP, igraph
Suggests: parallel
Published: 2017-07-12
Author: Beilun Wang [aut, cre], Yanjun Qi [aut]
Maintainer: Beilun Wang <bw4mw at virginia.edu>
BugReports: https://github.com/QData/SIMULE
License: GPL-2
URL: https://github.com/QData/SIMULE
NeedsCompilation: no
CRAN checks: simule results

Downloads:

Reference manual: simule.pdf
Package source: simule_1.1.1.tar.gz
Windows binaries: r-devel: simule_1.1.1.zip, r-release: simule_1.1.1.zip, r-oldrel: simule_1.1.1.zip
OS X El Capitan binaries: r-release: simule_1.1.1.tgz
OS X Mavericks binaries: r-oldrel: simule_1.1.1.tgz
Old sources: simule archive

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