Package: ClueR 1.4.2

ClueR: Cluster Evaluation

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>.

Authors:Pengyi Yang

ClueR_1.4.2.tar.gz
ClueR_1.4.2.zip(r-4.5)ClueR_1.4.2.zip(r-4.4)ClueR_1.4.2.zip(r-4.3)
ClueR_1.4.2.tgz(r-4.4-any)ClueR_1.4.2.tgz(r-4.3-any)
ClueR_1.4.2.tar.gz(r-4.5-noble)ClueR_1.4.2.tar.gz(r-4.4-noble)
ClueR_1.4.2.tgz(r-4.4-emscripten)ClueR_1.4.2.tgz(r-4.3-emscripten)
ClueR.pdf |ClueR.html
ClueR/json (API)

# Install 'ClueR' in R:
install.packages('ClueR', repos = c('https://pyanglab.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/pyanglab/cluer/issues

Datasets:

On CRAN:

4.53 score 10 stars 17 scripts 289 downloads 6 exports 4 dependencies

Last updated 1 years agofrom:6dbfcaa079. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 11 2024
R-4.5-winOKNov 11 2024
R-4.5-linuxOKNov 11 2024
R-4.4-winOKNov 11 2024
R-4.4-macOKNov 11 2024
R-4.3-winOKNov 11 2024
R-4.3-macOKNov 11 2024

Exports:clustEnrichmentclustOptimalenrichmentTestfuzzPlotrunCluetemporalSimu

Dependencies:classe1071MASSproxy