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CLUster Evaluation (CLUE) is a computational method for identifying optimal number of clusters in a given time-course dataset clustered by cmeans or kmeans algorithms and subsequently identify key kinases or pathways from each cluster. Its implementation in R is called ClueR. See README on <https://github.com/PYangLab/ClueR> for more details. P Yang et al. (2015) <doi:10.1371/journal.pcbi.1004403>.
| Version: | 1.4.2 |
| Depends: | R (≥ 2.10.0) |
| Imports: | e1071, parallel, stats, graphics, grDevices |
| Published: | 2023-11-15 |
| DOI: | 10.32614/CRAN.package.ClueR |
| Author: | Pengyi Yang |
| Maintainer: | Pengyi Yang <yangpy7 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | ClueR results |
| Reference manual: | ClueR.pdf |
| Package source: | ClueR_1.4.2.tar.gz |
| Windows binaries: | r-devel: ClueR_1.4.2.zip, r-release: ClueR_1.4.2.zip, r-oldrel: ClueR_1.4.2.zip |
| macOS binaries: | r-release (arm64): ClueR_1.4.2.tgz, r-oldrel (arm64): ClueR_1.4.2.tgz, r-release (x86_64): ClueR_1.4.2.tgz, r-oldrel (x86_64): ClueR_1.4.2.tgz |
| Old sources: | ClueR archive |
| Reverse suggests: | PhosR |
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These binaries (installable software) and packages are in development.
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