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This is an R implementation of "A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models" (FASJEM). The FASJEM 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 heterogonous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(fasjem) to learn the basic functions provided by this package. For more details, please see <http://proceedings.mlr.press/v54/wang17e/wang17e.pdf>.
| Version: | 1.1.2 |
| Depends: | R (≥ 3.0.0), igraph |
| Published: | 2017-08-01 |
| DOI: | 10.32614/CRAN.package.fasjem |
| Author: | Beilun Wang [aut, cre], Yanjun Qi [aut] |
| Maintainer: | Beilun Wang <bw4mw at virginia.edu> |
| BugReports: | https://github.com/QData/JEM |
| License: | GPL-2 |
| URL: | https://github.com/QData/JEM |
| NeedsCompilation: | no |
| CRAN checks: | fasjem results |
| Reference manual: | fasjem.pdf |
| Package source: | fasjem_1.1.2.tar.gz |
| Windows binaries: | r-devel: fasjem_1.1.2.zip, r-release: fasjem_1.1.2.zip, r-oldrel: fasjem_1.1.2.zip |
| macOS binaries: | r-release (arm64): fasjem_1.1.2.tgz, r-oldrel (arm64): fasjem_1.1.2.tgz, r-release (x86_64): fasjem_1.1.2.tgz, r-oldrel (x86_64): fasjem_1.1.2.tgz |
| Old sources: | fasjem archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.