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clusterCons
View on CRAN: Click
here
Download and install clusterCons package within the R console
Install from CRAN:
install.packages("clusterCons")
Install from Github:
library("remotes")
install_github("cran/clusterCons")
Install by package version:
library("remotes")
install_version("clusterCons", "1.2")
Attach the package and use:
library("clusterCons")
Maintained by
Dr. T. Ian Simpson
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2010-03-09
Latest Update: 2022-02-22
Description:
Functions for calculation of robustness measures for clusters and cluster membership based on generating consensus matrices from bootstrapped clustering experiments in which a random proportion of rows of the data set are used in each individual clustering. This allows the user to prioritise clusters and the members of clusters based on their consistency in this regime. The functions allow the user to select several algorithms to use in the re-sampling scheme and with any of the parameters that the algorithm would normally take. See Simpson, T. I., Armstrong, J. D. & Jarman, A. P. (2010) and Monti, S., Tamayo, P., Mesirov, J. & Golub, T. (2003) .
How to cite:
Dr. T. Ian Simpson (2010). clusterCons: Consensus Clustering using Multiple Algorithms and Parameters. R package version 1.2, https://cran.r-project.org/web/packages/clusterCons. Accessed 30 Jan. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for clusterCons
Functions, R codes and Examples using
the clusterCons R package
Some associated functions: auc-class . auc . aucplot . checks . clrob . cluscomp . clusterCons-package . consmatrix-class . data . deltak . dk-class . dkplot . expSetProcess . expressionPlot . membBoxPlot . memrob . memroblist-class . memrobmatrix-class . mergematrix-class . wrappers .
Some associated R codes: algorithms.R . functions.R . Full clusterCons package functions and examples
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