| name | bioconductor-clusterprofiler |
| description | This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources |
| when_to_use | Use when: Performing Over-Representation Analysis or Gene Set Enrichment Analysis.; Comparing biological themes among gene clusters.; Visualizing functional profiles of genomic coordinates (supported by ChIPseeker), genes, and gene clusters.; Querying Gene Ontology annotations online via AnnotationHub or KEGG Pathway and Module data.. Not for: For purely interactive web-based enrichment without an R environment (use web portals like DAVID directly).; When analyzing species not supported by online databases (unless providing customized user annotations). |
| user-invocable | false |
clusterProfiler
Dependencies & Environment
Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
- Version: 4.20.0 · Bioconductor: 3.23 · R: ≥ 4.6
- Imports: aisdk, AnnotationDbi, dplyr, enrichit, enrichplot, ggplot2, GO.db, GOSemSim, gson, httr, igraph, jsonlite, magrittr, plyr, qvalue, rlang, tidyr, yulab.utils
- Install:
BiocManager::install("clusterProfiler")
When to Use
- Performing Over-Representation Analysis or Gene Set Enrichment Analysis.
- Comparing biological themes among gene clusters.
- Visualizing functional profiles of genomic coordinates (supported by ChIPseeker), genes, and gene clusters.
- Querying Gene Ontology annotations online via AnnotationHub or KEGG Pathway and Module data.
When NOT to Use
- For purely interactive web-based enrichment without an R environment (use web portals like DAVID directly).
- When analyzing species not supported by online databases (unless providing customized user annotations).
Data Requirements
- Genomic coordinates, gene lists, or gene clusters.
- Annotations from supported ontologies/pathways (e.g., Disease Ontology, DisGeNET, Gene Ontology, KEGG, Reactome, Molecular Signatures Database) or customized user ontologies.
Key Parameters
- No specific parameters are detailed in the provided vignette text.
Best Practices
- Utilize the package's built-in visualization functions such as
barplot, cnetplot, dotplot, emapplot, gseaplot, goplot, and upsetplot to interpret enrichment results.
- When querying Gene Ontology, use AnnotationHub to support many species with online annotation queries.
- Provide a reproducible example when posting bugs to the GitHub issue tracker.
Common Pitfalls
- Failing to find answers to common problems because the user did not visit the clusterProfiler homepage documentation first.
- Posting questions to the Bioconductor support site without tagging the post with
clusterProfiler, leading to delayed responses.
- Attempting to analyze unsupported species without supplying a customized ontology or user annotation.
Alternatives
DOSE: Specifically focused on Disease Ontology and Network of Cancer Gene enrichment.
ReactomePA: Specifically tailored for Reactome Pathway analysis.
goseq: Alternative for GO enrichment that explicitly corrects for RNA-seq transcript length bias.
Citations
- G Yu, LG Wang, Y Han, QY He. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS: A Journal of Integrative Biology 2012, 16(5):284-287. doi: 10.1089/omi.2011.0118.
References
Run this on BioMate
This skill is the knowledge layer — when, why, and how to use clusterprofiler. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.
▶ Open clusterprofiler on BioMate →