The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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 |
| Reference manual: | diffee.pdf |
| 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 |
Please use the canonical form https://CRAN.R-project.org/package=diffee to link to this page.
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.
Health stats visible at Monitor.