# Simplify Functional Enrichment Results

## Documentation for package ‘simplifyEnrichment’ version 1.6.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

all_clustering_methods | All clustering methods
anno_word_cloud | Word cloud annotations
anno_word_cloud_from_GO | Word cloud annotations from GO
area_above_ecdf | Area above the eCDF curve
binary_cut | Cluster functional terms by recursively binary cutting the similarity matrix
cluster_by_apcluster | Cluster similarity matrix by apcluster
cluster_by_dynamicTreeCut | Cluster similarity matrix by dynamicTreeCut
cluster_by_hdbscan | Cluster similarity matrix by hdbscan
cluster_by_igraph | Cluster similarity matrix by graph community detection methods
cluster_by_kmeans | Cluster similarity matrix by k-means clustering
cluster_by_MCL | Cluster similarity matrix by MCL
cluster_by_mclust | Cluster similarity matrix by mclust
cluster_by_pam | Cluster similarity matrix by pam clustering
cluster_terms | Cluster functional terms
cmp_make_clusters | Apply various clustering methods
cmp_make_plot | Make plots for comparing clustering methods
compare_clustering_methods | Compare clustering methods
count_words | Calculate word frequency
dend_node_apply | Apply functions on every node in a dendrogram
difference_score | Difference score
DO_similarity | Calculate Disease Ontology (DO) semantic similarity matrix
edit_node | Modify nodes in a dendrogram
export_to_shiny_app | Interactively visualize the similarity heatmap
GO_similarity | Calculate Gene Ontology (GO) semantic similarity matrix
guess_ont | Guess the ontology of the input GO IDs
heightDetails.word_cloud | Height for word_cloud grob
ht_clusters | Visualize the similarity matrix and the clustering
keyword_enrichment_from_GO | Keyword enrichment for GO terms
partition_by_hclust | Partition by hclust
partition_by_kmeans | Partition by kmeans
partition_by_kmeanspp | Partition by kmeans++
partition_by_pam | Partition by PAM
plot_binary_cut | Visualize the process of binary cut
random_DO | Generate random Disease Ontology (DO) IDs
random_GO | Generate random GO IDs
register_clustering_methods | Register new clustering methods
remove_clustering_methods | Remove clustering methods
reset_clustering_methods | Reset to default clustering methods
scale_fontsize | Scale font size
select_cutoff | Select the cutoff for binary cut
se_opt | Global parameters
simplifyEnrichment | Simplify functional enrichment results
simplifyGO | Simplify Gene Ontology (GO) enrichment results
simplifyGOFromMultipleLists | Perform simplifyGO analysis with multiple lists of GO IDs
subset_enrichResult | Subset method of the enrichResult class
term_similarity | Similarity between terms based on the overlap of genes
term_similarity_from_enrichResult | Similarity between terms in the enrichResult class
term_similarity_from_gmt | Similarity between terms from a gmt file
term_similarity_from_KEGG | Similarity between KEGG terms
term_similarity_from_MSigDB | Similarity between MSigDB terms
term_similarity_from_Reactome | Similarity between Reactome terms
widthDetails.word_cloud | Width for word_cloud grob
word_cloud_grob | A simple grob for the word cloud