clusterProfiler 4.0 is an updated version of a popular Bioconductor package designed for functional enrichment analysis in high-throughput omics data. This tool has been significantly enhanced to support a universal interface for functional enrichment analysis in thousands of organisms, using internally supported ontologies and pathways, as well as user-provided or online-derived annotations. Key features include gene set enrichment analysis, comparison of enrichment results from multiple gene lists, and integration with the dplyr and ggplot2 packages for data manipulation and visualization. The package supports GO and KEGG annotations, with the ability to query GO annotations for non-model organisms via the AnnotationHub package. It also includes a simplify function to eliminate redundant GO terms and a seq2gene function to associate genomic regions with coding genes. The clusterProfiler library is widely used and integrated into over 30 CRAN and Bioconductor packages, pipelines, and online platforms, making it a valuable resource for interpreting omics data and uncovering biological mechanisms.clusterProfiler 4.0 is an updated version of a popular Bioconductor package designed for functional enrichment analysis in high-throughput omics data. This tool has been significantly enhanced to support a universal interface for functional enrichment analysis in thousands of organisms, using internally supported ontologies and pathways, as well as user-provided or online-derived annotations. Key features include gene set enrichment analysis, comparison of enrichment results from multiple gene lists, and integration with the dplyr and ggplot2 packages for data manipulation and visualization. The package supports GO and KEGG annotations, with the ability to query GO annotations for non-model organisms via the AnnotationHub package. It also includes a simplify function to eliminate redundant GO terms and a seq2gene function to associate genomic regions with coding genes. The clusterProfiler library is widely used and integrated into over 30 CRAN and Bioconductor packages, pipelines, and online platforms, making it a valuable resource for interpreting omics data and uncovering biological mechanisms.