COMMUNAL: Robust Selection of Cluster Number K

Facilitates optimal clustering of a data set. Provides a framework to run a wide range of clustering algorithms to determine the optimal number (k) of clusters in the data. Then analyzes the cluster assignments from each clustering algorithm to identify samples that repeatedly classify to the same group. We call these 'core clusters', providing a basis for later class discovery.

Install the latest version of this package by entering the following in R:
install.packages("COMMUNAL")
AuthorAlbert Chen [aut, cre], Timothy E Sweeney [aut], Olivier Gevaert [ths]
Date of publication2015-10-12 00:26:16
MaintainerAlbert Chen <acc2015@stanford.edu>
LicenseGPL-2
Version1.1.0

View on CRAN

Files

inst
inst/CITATION
inst/tests
inst/tests/unittest.R
inst/doc
inst/doc/COMMUNAL.Rnw
inst/doc/COMMUNAL.R
inst/doc/COMMUNAL.pdf
tests
tests/runTestSuite.R
NAMESPACE
data
data/BRCA.results.RData
data/BRCA.100.RData
R
R/extract_core.R R/plot_range_3d.R R/communal.R R/test_range.R
vignettes
vignettes/COMMUNAL.Rnw
vignettes/COMMUNAL-concordance.tex
vignettes/snapshot.png
vignettes/framed.sty
MD5
build
build/vignette.rds
DESCRIPTION
man
man/measureMonotonic.Rd man/COMMUNAL.Rd man/plotRange3D.Rd man/COMMUNAL-class.Rd man/clusterKeys.Rd man/clusterRange.Rd man/BRCA.results.Rd man/COMMUNAL-package.Rd man/testAlgsMinSize.Rd man/returnCore.Rd man/BRCA.100.Rd man/examineCounts.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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