clusterProfiler 4.0: A universal enrichment tool for interpreting omics data.

Gene ontology enrichment analysisThe original result (A) and a simplified version (B) were visualized as enrichment map networks. Each node represents a gene set (i.e., a GO term) and each edge represents the overlap between two gene sets.

KEGG pathway enrichment analysisIn GSEA enrichment plot (A), the curves represent the running sum of the enrichment scores, the middle part of the graph shows the position of genes that are related to certain pathways, and the bottom part of the graph displays how the metric (e.g., fold change) is distributed along with the list. The UpSet plot (B) visualizes the metric distribution of core enrichment genes. It differentiates genes that uniquely belong to a pathway or are associated with two or more pathways.

Functional enrichment analysis of genomic regions of interestGenomic regions are linked to coding genes, which are then used to identify transcript cofactors by testing significant overlap of target genes.

Comparing functional profiles among different levels of conditionsThe compareCluster function performed enrichment analysis simultaneously for eight lists of DEGs. The results were visualized as a dot plot with an x axis representing one level of conditions (time course) and a facet panel indicating another level of conditions (drug treatments).

Visualizing enrichment results using ggplot2A lollipop chart to visualize the rich factors from ORA (A) and a bar chart to visualize normalized enrichment scores from GSEA (B).

A package suite for mining biological knowledgeclusterProfiler is an essential core for functional analysis, the functionalities of which are enhanced by several companion packages.