Package: ClustAssess 1.2.0

Andi Munteanu

ClustAssess: Tools for Assessing Clustering

A set of tools for evaluating clustering robustness using proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014) <doi:10.1038/srep06207>), as well as similarity across methods and method stability using element-centric clustering comparison (Gates et al. (2019) <doi:10.1038/s41598-019-44892-y>). Additionally, this package enables stability-based parameter assessment for graph-based clustering pipelines typical in single-cell data analysis.

Authors:Andi Munteanu [aut, cre], Arash Shahsavari [aut], Rafael Kollyfas [ctb], Miguel Larraz Lopez de Novales [aut], Liviu Ciortuz [ctb], Irina Mohorianu [aut]

ClustAssess_1.2.0.tar.gz
ClustAssess_1.2.0.zip(r-4.7-x86_64)ClustAssess_1.2.0.zip(r-4.7-arm64)ClustAssess_1.2.0.zip(r-4.6-x86_64)ClustAssess_1.2.0.zip(r-4.6-arm64)ClustAssess_1.2.0.zip(r-4.5-x86_64)
ClustAssess_1.2.0.tgz(r-4.6-x86_64)ClustAssess_1.2.0.tgz(r-4.6-arm64)ClustAssess_1.2.0.tgz(r-4.5-x86_64)ClustAssess_1.2.0.tgz(r-4.5-arm64)
ClustAssess_1.2.0.tar.gz(r-4.7-arm64)ClustAssess_1.2.0.tar.gz(r-4.7-x86_64)ClustAssess_1.2.0.tar.gz(r-4.6-arm64)ClustAssess_1.2.0.tar.gz(r-4.6-x86_64)
ClustAssess_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ClustAssess/json (API)

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

Bug tracker:https://github.com/core-bioinformatics/clustassess/issues

Pkgdown/docs site:https://core-bioinformatics.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

softwaresinglecellrnaseqatacseqnormalizationpreprocessingdimensionreductionvisualizationqualitycontrolclusteringclassificationannotationgeneexpressiondifferentialexpressionbioinformaticsgenomicsmachine-learningparameter-optimizationrobustnesssingle-cellunsupervised-learningcpp

4.68 score 34 stars 14 scripts 608 downloads 57 exports 176 dependencies

Last updated from:142d534c12. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK299
linux-devel-x86_64OK374
source / vignettesOK322
linux-release-arm64OK311
linux-release-x86_64OK365
macos-release-arm64OK335
macos-release-x86_64OK587
macos-oldrel-arm64OK289
macos-oldrel-x86_64OK585
windows-devel-arm64OK521
windows-devel-x86_64OK329
windows-release-arm64OK532
windows-release-x86_64OK311
windows-oldrel-x86_64OK282
wasm-releaseOK197

Exports:add_metadataassess_clustering_stabilityassess_feature_stabilityassess_nn_stabilityautomatic_stability_assessmentcalculate_markerscalculate_markers_shinychoose_stable_clustersconsensus_clustercreate_monocle_defaultcreate_monocle_from_clustassesscreate_monocle_from_clustassess_appcreate_seurat_object_defaultcreate_seurat_object_from_clustassess_appelement_agreementelement_consistencyelement_simelement_sim_elscoreelement_sim_matrixget_clusters_from_clustassess_objectget_highest_prune_paramget_highest_prune_param_embeddingget_nn_conn_compsgetNNmatrixmarker_overlapmerge_partitionspac_convergencepac_landscapeplot_clust_hierarchicalplot_clustering_overall_stabilityplot_clustering_per_value_stabilityplot_connected_comps_evolutionplot_feature_overall_stability_boxplotplot_feature_overall_stability_incrementalplot_feature_per_resolution_stability_boxplotplot_feature_per_resolution_stability_incrementalplot_feature_stability_ecs_facetplot_feature_stability_mb_facetplot_k_n_partitionsplot_k_resolution_correspplot_n_neigh_ecsplot_n_neigh_k_correspondenceserver_comparisonsserver_dimensionality_reductionserver_graph_clusteringserver_graph_constructionserver_landing_pageserver_sandboxui_comparisonsui_dimensionality_reductionui_graph_clusteringui_graph_constructionui_landing_pageui_sandboxweighted_element_consistencywrite_objectswrite_shiny_app

Dependencies:abindaskpassbase64encbeeswarmBHbitopsbslibcachemCairocaToolscliclustercodetoolscommonmarkcowplotcpp11crayoncrosstalkcurldata.tabledeldirDEoptimRdigestdotCall64dplyrdqrngDTevaluatefarverfastclusterfastDummiesfastmapfitdistrplusFNNfontawesomeforeachfsfuturefuture.applygenericsggbeeswarmggnewscaleggplot2ggrastrggrepelggridgesglobalsglueGmediangoftestgplotsgprofiler2gridExtragtablegtoolsherehighrhmshtmltoolshtmlwidgetshttpuvhttricaigraphirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleidenlifecyclelistenvlmtestmagrittrMASSMatrixmatrixStatsmemoisemimeminiUInlmeopensslotelpaletteerparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprettyunitsprismaticprogressprogressrpromisespurrrqualpalrR6raggRANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLRCurlrematch2reshape2reticulaterlangrmarkdownrobustbaseROCRrprojrootRSpectrarstudioapiRtsneS7sassscalesscattermoresctransformSeuratSeuratObjectshinyshinyjsshinyLPshinyWidgetssitmosmsourcetoolsspspamspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsyssystemfontstensortextshapingtibbletidyrtidyselecttinytexutf8uwotvctrsvioplotviporviridisLitewithrxfunxtableyamlzipzoo

Readme and manuals

Help Manual

Help pageTopics
Add metadata to ClustAssess ShinyAppadd_metadata
Assessment of Stability for Graph Clusteringassess_clustering_stability
Assess the stability for configurations of feature types and sizesassess_feature_stability
Assess the stability for Graph Building Parametersassess_nn_stability
Assessment of Stability for Graph Clusteringautomatic_stability_assessment
Calculate markerscalculate_markers
Calculate markers - Shinycalculate_markers_shiny
Choose stable clusters based on ECC and frequencychoose_stable_clusters
Consensus Clustering and Proportion of Ambiguously Clustered Pairsconsensus_cluster
Create monocle objectcreate_monocle_default
Create monocle object from a ClustAssess objectcreate_monocle_from_clustassess
Create monocle object from a ClustAssess shiny appcreate_monocle_from_clustassess_app
Create Seurat objectcreate_seurat_object_default
Create Seurat object from a ClustAssess shiny appcreate_seurat_object_from_clustassess_app
Element-Wise Average Agreement Between a Set of Clusteringselement_agreement
Element-Wise Consistency Between a Set of Clusteringselement_consistency
The Element-Centric Clustering Similarityelement_sim
The Element-Centric Clustering Similarity for each Elementelement_sim_elscore
Pairwise Comparison of Clusteringselement_sim_matrix
Extract config-specific clusters from a ClustAssess objectget_clusters_from_clustassess_object
Get the vector of colours from a paletteget_colour_vector_from_palette
Calculate the highest pruning parameter for the SNN graph given NN matrixget_highest_prune_param
Calculate the highest pruning parameter for the SNN graph given Embeddingget_highest_prune_param_embedding
Relationship Between Nearest Neighbours and Connected Componentsget_nn_conn_comps
Computes the NN adjacency matrix given the neighboursgetNNmatrix
Cell-Wise Marker Gene Overlapmarker_overlap
Merge Partitionsmerge_partitions
Merge Partitions from different Resolutionsmerge_resolutions
PAC Convergence Plotpac_convergence
PAC Landscape Plotpac_landscape
Hierarchical relationship between partitions with different number of clustersplot_clust_hierarchical
Clustering Method Stability Facet Plotplot_clustering_difference_facet
Clustering Method Overall Stability Boxplotplot_clustering_overall_stability
Clustering Method per value Stability Boxplotplot_clustering_per_value_stability
Relationship Between Number of Nearest Neighbours and Graph Connectivityplot_connected_comps_evolution
Overall Feature Stability Boxplotplot_feature_overall_stability_boxplot
Overall Feature Stability Incremental Boxplotplot_feature_overall_stability_incremental
Per resolution Feature Stability Boxplotplot_feature_per_resolution_stability_boxplot
Per resolution - Feature Stability Incremental Boxplotplot_feature_per_resolution_stability_incremental
Feature Stability - EC Consistency Facet Plotplot_feature_stability_ecs_facet
Feature Stability - Cluster Membership Facet Plotplot_feature_stability_mb_facet
Relationship Between the Number of Clusters and the Number of Unique Partitionsplot_k_n_partitions
Correspondence Between Resolution and the Number of Clustersplot_k_resolution_corresp
Graph construction parameters - ECC facetplot_n_neigh_ecs
Relationship Between Number of Nearest Neighbours and Number of Clustersplot_n_neigh_k_correspondence
Server - Comparison moduleserver_comparisons
Server - Dimensionality reduction moduleserver_dimensionality_reduction
Server - Graph clustering moduleserver_graph_clustering
Server - Graph construction moduleserver_graph_construction
Server - Landing page moduleserver_landing_page
Server - Sandbox moduleserver_sandbox
UI - Comparison moduleui_comparisons
UI - Dimensionality reduction moduleui_dimensionality_reduction
UI - Graph clustering moduleui_graph_clustering
UI - Graph construction moduleui_graph_construction
UI - Landing page moduleui_landing_page
UI - Sandbox moduleui_sandbox
Weighted Element-Centric Consistencyweighted_element_consistency
Write the objects for the ClustAssess ShinyAppwrite_objects
Create the ClustAssess ShinyAppwrite_shiny_app write_shiny_app.default write_shiny_app.Seurat