Package: ConsensusClustering 1.5.0

ConsensusClustering: Consensus Clustering

Clustering, or cluster analysis, is a widely used technique in bioinformatics to identify groups of similar biological data points. Consensus clustering is an extension to clustering algorithms that aims to construct a robust result from those clustering features that are invariant under different sources of variation. For the reference, please cite the following paper: Yousefi, Melograna, et. al., (2023) <doi:10.3389/fmicb.2023.1170391>.

Authors:Behnam Yousefi [aut, cre, cph]

ConsensusClustering_1.5.0.tar.gz
ConsensusClustering_1.5.0.zip(r-4.7)ConsensusClustering_1.5.0.zip(r-4.6)ConsensusClustering_1.5.0.zip(r-4.5)
ConsensusClustering_1.5.0.tgz(r-4.6-any)ConsensusClustering_1.5.0.tgz(r-4.5-any)
ConsensusClustering_1.5.0.tar.gz(r-4.7-any)ConsensusClustering_1.5.0.tar.gz(r-4.6-any)
ConsensusClustering_1.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ConsensusClustering/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 5 scripts 230 downloads 30 exports 22 dependencies

Last updated from:5eed3d63e0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK132
source / vignettesOK159
linux-release-x86_64OK131
macos-release-arm64OK152
macos-oldrel-arm64OK137
windows-develOK109
windows-releaseOK81
windows-oldrelOK84
wasm-releaseOK99

Exports:adj_convadj_matcc_cluster_countcluster_relabelcoCluster_matrixconnectivity_matrixconsensus_matrixconsensus_matrix_data_prtrbconsensus_matrix_multiviewgaussian_clustersgaussian_clusters_with_paramgaussian_mixture_clustersgenerate_data_prtrbgenerate_gaussian_datagenerate_method_prtrbgenerate_multiviewhir_clust_from_adj_matindicator_matrixlabel_similarityLogitmajority_votingmulti_cluster_genmulti_kmeans_genmulti_pam_genmultiview_cluster_genmultiview_clustersmultiview_kmeans_genmultiview_pam_genpam_clust_from_adj_matspect_clust_from_adj_mat

Dependencies:assertthatcliclustercpp11dplyrgenericsglueigraphlatticelifecyclemagrittrMatrixmvtnormpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr

Readme and manuals

Help Manual

Help pageTopics
Convert adjacency function to the affinity matrixadj_conv
Covert data matrix to adjacency matrixadj_mat
Count the number of clusters based on stability score.cc_cluster_count
Relabeling clusters based on cluster similaritiescluster_relabel
Calculate the Co-cluster matrix for a given set of clustering results.coCluster_matrix
Build connectivity matrixconnectivity_matrix
Calculate consensus matrix for data perturbation consensus clusteringconsensus_matrix
Calculate consensus matrix for data perturbation consensus clusteringconsensus_matrix_data_prtrb
Calculate consensus matrix for multi-data consensus clusteringconsensus_matrix_multiview
Generate clusters of data points from Gaussian distribution with randomly generated parametersgaussian_clusters
Generate clusters of data points from Gaussian distribution with given parametersgaussian_clusters_with_param
Generate clusters of data points from Gaussian-mixture-model distributions with randomly generated parametersgaussian_mixture_clusters
Generation mechanism for data perturbation consensus clusteringgenerate_data_prtrb
Generate a set of data points from Gaussian distributiongenerate_gaussian_data
Multiple method generationgenerate_method_prtrb
Multiview generationgenerate_multiview
Hierarchical clustering from adjacency matrixhir_clust_from_adj_mat
Build indicator matrixindicator_matrix
Similarity between different clusterslabel_similarity
Logit functionLogit
Consensus mechanism based on majority votingmajority_voting
Multiple cluster generationmulti_cluster_gen
Multiple K-means generationmulti_kmeans_gen
Multiple PAM (K-medoids) generationmulti_pam_gen
Multiview cluster generationmultiview_cluster_gen
Generate multiview clusters from Gaussian distributions with randomly generated parametersmultiview_clusters
Multiview K-means generationmultiview_kmeans_gen
Multiview PAM (K-medoids) generationmultiview_pam_gen
PAM (k-medoids) clustering from adjacency matrixpam_clust_from_adj_mat
Spectral clustering from adjacency matrixspect_clust_from_adj_mat