Package: simplifyEnrichment 1.15.0

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:Zuguang Gu [aut, cre]

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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'))

Peer review:

Bug tracker:https://github.com/jokergoo/simplifyenrichment/issues

On BioConductor:simplifyEnrichment-1.15.0(bioc 3.20)simplifyEnrichment-1.14.0(bioc 3.19)

bioconductor-package

54 exports 0.82 score 69 dependencies 1 mentions

Last updated 2 months agofrom:ffc1a5a4cb

Exports:all_clustering_methodsanno_word_cloudanno_word_cloud_from_GOarea_above_ecdfbinary_cutcluster_by_apclustercluster_by_dynamicTreeCutcluster_by_hdbscancluster_by_igraphcluster_by_kmeanscluster_by_MCLcluster_by_mclustcluster_by_pamcluster_termscmp_make_clusterscmp_make_plotcompare_clustering_methodscount_wordsdend_node_applydifference_scoreDO_similarityedit_nodeexport_to_shiny_appGO_similarityguess_ontheightDetails.word_cloudht_clusterskeyword_enrichment_from_GOpartition_by_hclustpartition_by_kmeanspartition_by_kmeanspppartition_by_pamplot_binary_cutrandom_DOrandom_GOregister_clustering_methodsremove_clustering_methodsreset_clustering_methodsscale_fontsizese_optselect_cutoffsimplifyEnrichmentsimplifyGOsimplifyGOFromMultipleListssubset_enrichResultsummarizeGOterm_similarityterm_similarity_from_enrichResultterm_similarity_from_gmtterm_similarity_from_KEGGterm_similarity_from_MSigDBterm_similarity_from_ReactomewidthDetails.word_cloudword_cloud_grob

Dependencies:AnnotationDbiaskpassBHBiobaseBiocGenericsBiostringsbitbit64blobcachemcirclizecliclueclustercodetoolscolorspaceComplexHeatmapcpp11crayoncurlDBIdigestdoParallelfastmapforeachfsGenomeInfoDbGenomeInfoDbDataGetoptLongGlobalOptionsglueGO.dbGOSemSimhttrIRangesiteratorsjsonliteKEGGRESTlatticelifecycleMatrixmatrixStatsmemoisemimeNLPopensslorg.Hs.eg.dbpkgconfigplogrpngproxyCR6RColorBrewerRcppRcppArmadillorjsonrlangRSQLiteS4VectorsshapeslamsystmUCSC.utilsvctrsxml2XVectoryulab.utilszlibbioc

A Shiny app to interactively visualize clustering results

Zuguang Gu ([email protected])

Rendered frominteractive.Rmdusingknitr::rmarkdownon Jun 20 2024.

Last update: 2021-07-01
Started: 2021-03-26

Simplify Functional Enrichment Results

Zuguang Gu ([email protected])

Rendered fromsimplifyEnrichment.Rmdusingknitr::rmarkdownon Jun 20 2024.

Last update: 2022-09-02
Started: 2020-08-08

Word Cloud Annotation

Zuguang Gu ([email protected])

Rendered fromword_cloud_anno.Rmdusingknitr::rmarkdownon Jun 20 2024.

Last update: 2021-11-26
Started: 2020-12-29

Readme and manuals

Help Manual

Help pageTopics
All clustering methodsall_clustering_methods
Word cloud annotationsanno_word_cloud
Word cloud annotations from GOanno_word_cloud_from_GO
Area above the eCDF curvearea_above_ecdf
Cluster functional terms by recursively binary cutting the similarity matrixbinary_cut
Cluster similarity matrix by apclustercluster_by_apcluster
Cluster similarity matrix by dynamicTreeCutcluster_by_dynamicTreeCut
Cluster similarity matrix by hdbscancluster_by_hdbscan
Cluster similarity matrix by graph community detection methodscluster_by_igraph
Cluster similarity matrix by k-means clusteringcluster_by_kmeans
Cluster similarity matrix by MCLcluster_by_MCL
Cluster similarity matrix by mclustcluster_by_mclust
Cluster similarity matrix by pam clusteringcluster_by_pam
Cluster functional termscluster_terms
Apply various clustering methodscmp_make_clusters
Make plots for comparing clustering methodscmp_make_plot
Compare clustering methodscompare_clustering_methods
Calculate word frequencycount_words
Apply functions on every node in a dendrogramdend_node_apply
Difference scoredifference_score
Calculate Disease Ontology (DO) semantic similarity matrixDO_similarity
Modify nodes in a dendrogramedit_node
Interactively visualize the similarity heatmapexport_to_shiny_app
Calculate Gene Ontology (GO) semantic similarity matrixGO_similarity
Guess the ontology of the input GO IDsguess_ont
Height for word_cloud grobheightDetails.word_cloud
Visualize the similarity matrix and the clusteringht_clusters
Keyword enrichment for GO termskeyword_enrichment_from_GO
Partition by hclustpartition_by_hclust
Partition by kmeanspartition_by_kmeans
Partition by kmeans++partition_by_kmeanspp
Partition by PAMpartition_by_pam
Visualize the process of binary cutplot_binary_cut
Generate random Disease Ontology (DO) IDsrandom_DO
Generate random GO IDsrandom_GO
Register new clustering methodsregister_clustering_methods
Remove clustering methodsremove_clustering_methods
Reset to default clustering methodsreset_clustering_methods
Scale font sizescale_fontsize
Global parametersse_opt
Select the cutoff for binary cutselect_cutoff
Simplify functional enrichment resultssimplifyEnrichment
Simplify Gene Ontology (GO) enrichment resultssimplifyGO
Perform simplifyGO analysis with multiple lists of GO IDssimplifyGOFromMultipleLists
Subset method of the enrichResult classsubset_enrichResult
A simplified way to visualize enrichment in GO clusterssummarizeGO
Similarity between terms based on the overlap of genesterm_similarity
Similarity between terms in the enrichResult classterm_similarity_from_enrichResult
Similarity between terms from a gmt fileterm_similarity_from_gmt
Similarity between KEGG termsterm_similarity_from_KEGG
Similarity between MSigDB termsterm_similarity_from_MSigDB
Similarity between Reactome termsterm_similarity_from_Reactome
Width for word_cloud grobwidthDetails.word_cloud
A simple grob for the word cloudword_cloud_grob