Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, and classification.
Version: | 2.3.0 |
Imports: | heatmap.plus, ExPosition, alluvial |
Published: | 2018-04-24 |
Author: | Bo Wang, Aziz Mezlini, Feyyaz Demir, Marc Fiume, Zhuowen Tu, Michael Brudno, Benjamin Haibe-Kains, Anna Goldenberg |
Maintainer: | Daniel Cole <goldenberglab at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | SNFtool results |
Reference manual: | SNFtool.pdf |
Package source: | SNFtool_2.3.0.tar.gz |
Windows binaries: | r-devel: SNFtool_2.3.0.zip, r-release: SNFtool_2.3.0.zip, r-oldrel: SNFtool_2.3.0.zip |
macOS binaries: | r-release: SNFtool_2.3.0.tgz, r-oldrel: SNFtool_2.3.0.tgz |
Old sources: | SNFtool archive |
Reverse imports: | CancerSubtypes, CiteFuse, IntClust |
Reverse suggests: | ANF |
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