Package: simplifyEnrichment 2.1.0
Zuguang Gu
simplifyEnrichment: Simplify Functional Enrichment Results
A new clustering algorithm, "binary cut", for clustering similarity matrices of functional terms is implemeted in this package. It also provides functions for visualizing, summarizing and comparing the clusterings.
Authors:
simplifyEnrichment_2.1.0.tar.gz
simplifyEnrichment_2.1.0.zip(r-4.5)simplifyEnrichment_2.1.0.zip(r-4.4)simplifyEnrichment_2.1.0.zip(r-4.3)
simplifyEnrichment_2.1.0.tgz(r-4.4-any)simplifyEnrichment_2.1.0.tgz(r-4.3-any)
simplifyEnrichment_2.1.0.tar.gz(r-4.5-noble)simplifyEnrichment_2.1.0.tar.gz(r-4.4-noble)
simplifyEnrichment_2.1.0.tgz(r-4.4-emscripten)simplifyEnrichment_2.1.0.tgz(r-4.3-emscripten)
simplifyEnrichment.pdf |simplifyEnrichment.html✨
simplifyEnrichment/json (API)
NEWS
| # Install 'simplifyEnrichment' in R: |
| install.packages('simplifyEnrichment', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jokergoo/simplifyenrichment/issues
On BioConductor:simplifyEnrichment-2.1.0(bioc 3.21)simplifyEnrichment-2.0.0(bioc 3.20)
softwarevisualizationgoclusteringgenesetenrichment
Last updated 15 days agofrom:5590aab5a3. Checks:OK: 4 WARNING: 3. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | WARNING | Oct 31 2024 |
| R-4.5-linux | OK | Oct 31 2024 |
| R-4.4-win | WARNING | Oct 31 2024 |
| R-4.4-mac | OK | Oct 31 2024 |
| R-4.3-win | WARNING | Oct 31 2024 |
| R-4.3-mac | OK | Oct 31 2024 |
Exports:all_clustering_methodsanno_word_cloudanno_word_cloud_from_GObinary_cutcluster_by_apclustercluster_by_dynamicTreeCutcluster_by_fast_greedycluster_by_hdbscancluster_by_kmeanscluster_by_leading_eigencluster_by_louvaincluster_by_MCLcluster_by_mclustcluster_by_pamcluster_by_walktrapcluster_termscmp_make_clusterscmp_make_plotcompare_clustering_methodscount_wordsdend_node_applydifference_scoreexport_to_shiny_appGO_similarityguess_ontht_clusterskeyword_enrichment_from_GOpartition_by_hclustpartition_by_kmeanspartition_by_kmeanspppartition_by_pamplot_binary_cutrandom_GOregister_clustering_methodsremove_clustering_methodsreset_clustering_methodsscale_fontsizese_optselect_cutoffsimplifyEnrichmentsimplifyGOsimplifyGOFromMultipleListssummarizeGOword_cloud_grob
Dependencies:AnnotationDbiaskpassbase64encBHBiobaseBiocGenericsBiostringsbitbit64blobbslibcachemcirclizecliclueclustercodetoolscolorspacecommonmarkComplexHeatmapcpp11crayoncurlDBIdigestdoParallelfastmapfontawesomeforeachfsGenomeInfoDbGenomeInfoDbDataGetoptLongGlobalOptionsglueGO.dbhtmltoolshttpuvhttrigraphIRangesiteratorsjquerylibjsonliteKEGGRESTlaterlatticelifecyclemagrittrMatrixmatrixStatsmemoisemimeNLPopensslpkgconfigplogrpngPolychromepromisesR6rappdirsRColorBrewerRcpprjsonrlangRSQLiteS4Vectorssassscatterplot3dshapeshinysimonaslamsourcetoolssystmUCSC.utilsvctrswithrxml2xtableXVectorzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Word cloud annotations | anno_word_cloud |
| Word cloud annotations from GO | anno_word_cloud_from_GO |
| Area above the eCDF curve | area_above_ecdf |
| Cluster terms based on their similarity matrix | cluster_by_apcluster cluster_by_dynamicTreeCut cluster_by_fast_greedy cluster_by_hdbscan cluster_by_kmeans cluster_by_leading_eigen cluster_by_louvain cluster_by_MCL cluster_by_mclust cluster_by_pam cluster_by_walktrap cluster_terms |
| Compare clustering methods | cmp_make_clusters cmp_make_plot compare_clustering_methods |
| Calculate word frequency | count_words |
| Apply functions on every node in a dendrogram | dend_node_apply edit_node |
| Difference score | difference_score |
| Interactively visualize the similarity heatmap | export_to_shiny_app |
| Calculate Gene Ontology (GO) semantic similarity matrix | GO_similarity guess_ont random_GO |
| Visualize the similarity matrix and the clustering | ht_clusters |
| Keyword enrichment for GO terms | keyword_enrichment_from_GO |
| Partition the matrix | partition_by_hclust partition_by_kmeans partition_by_kmeanspp partition_by_pam |
| Cluster functional terms by recursively binary cutting the similarity matrix | binary_cut plot_binary_cut |
| Configure clustering methods | all_clustering_methods register_clustering_methods remove_clustering_methods reset_clustering_methods |
| Scale font size | scale_fontsize |
| Global parameters | se_opt |
| Select the cutoff for binary cut | select_cutoff |
| Simplify Gene Ontology (GO) enrichment results | simplifyEnrichment simplifyGO |
| Perform simplifyGO analysis with multiple lists of GO IDs | simplifyGOFromMultipleLists |
| A simplified way to visualize enrichment in GO clusters | summarizeGO |
| A simple grob for the word cloud | heightDetails.word_cloud widthDetails.word_cloud word_cloud_grob |
