Package: clusterCons 1.2

Dr. T. Ian Simpson

clusterCons: Consensus Clustering using Multiple Algorithms and Parameters

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) <doi:10.1186/1471-2105-11-590> and Monti, S., Tamayo, P., Mesirov, J. & Golub, T. (2003) <doi:10.1023/a:1023949509487>.

Authors:Dr. T. Ian Simpson [aut, cre, cph]

clusterCons_1.2.tar.gz
clusterCons_1.2.zip(r-4.5)clusterCons_1.2.zip(r-4.4)clusterCons_1.2.zip(r-4.3)
clusterCons_1.2.tgz(r-4.4-any)clusterCons_1.2.tgz(r-4.3-any)
clusterCons_1.2.tar.gz(r-4.5-noble)clusterCons_1.2.tar.gz(r-4.4-noble)
clusterCons_1.2.tgz(r-4.4-emscripten)clusterCons_1.2.tgz(r-4.3-emscripten)
clusterCons.pdf |clusterCons.html✨
clusterCons/json (API)

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

Peer review:

Bug tracker:https://github.com/biomedicalinformaticsgroup/clustercons/issues

Datasets:
  • golub - Data sets for the clusterCons package
  • sim_class - Data sets for the clusterCons package
  • sim_profile - Data sets for the clusterCons package
  • testcmr - Data sets for the clusterCons package

On CRAN:

clustering

25 exports 1 stars 1.03 score 6 dependencies 1 dependents 12 scripts 310 downloads

Last updated 3 years agofrom:114dc338d8. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-winNOTESep 13 2024
R-4.5-linuxNOTESep 13 2024
R-4.4-winOKSep 13 2024
R-4.4-macOKSep 13 2024
R-4.3-winOKSep 13 2024
R-4.3-macOKSep 13 2024

Exports:.requireCachedGenericsagnes_clmemapcluster_clmemaucaucplotaucsclrobcluscompdata_checkdeltakdiana_clmemdkplotexpressionPlotexpSetProcesshclust_clmemkmeans_clmemmembBoxPlotmemrobpam_clmemvalidAUCObjectvalidConsMatrixObjectvalidDkObjectvalidMemRobListObjectvalidMemRobMatrixObjectvalidMergeMatrixObject

Dependencies:apclusterclusterlatticeMatrixRColorBrewerRcpp

Readme and manuals

Help Manual

Help pageTopics
Calculate consensus clustering results from re-sampled clustering experiments with the option of using multiple algorithms and parametersclusterCons-package clusterCons
Calculate area under the curve statisticsauc aucs
Class "auc"auc-class
Generate an area under the curve plot using lattice graphicsaucplot
Functions to check the integrity of various objectschecks data_check validAUCObject validConsMatrixObject validDkObject validMemRobListObject validMemRobMatrixObject validMergeMatrixObject
Calculate the cluster robustness from consensus clustering resultsclrob
Perform consensus clustering with the option of using multiple algorithms and parameters and mergingcluscomp
Class "consmatrix"consmatrix consmatrix-class
Data sets for the clusterCons packagegolub sim_class sim_profile testcmr
Function to calculate the change in the area under the curve (AUC) across a range of cluster number valuesdeltak
Class "dk"dk-class
Generate a delta-K plot from area under the curve (AUC) values across multiple cluster numbers.dkplot
Generate a profile plot for the data partitioned by cluster membership.expressionPlot
Internal function to extract the data from an expressionSet class object from the affy package for use with cluscompexpSetProcess
Generate a box and whisker plot of membership robustness for all clustersmembBoxPlot
Calculate the membership robustness from consensus clustering resultsmemrob
Class "memroblist"memroblist memroblist-class
Class "memrobmatrix"memrobmatrix memrobmatrix-class
Class "mergematrix"mergematrix mergematrix-class
Functions to wrap command calls to clustering functionsagnes_clmem apcluster_clmem diana_clmem hclust_clmem kmeans_clmem pam_clmem wrappers