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Using clusterProfiler to characterize multiomics data

Nature Protocols volume 19, pages 3292–3320 (2024)Cite this article

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Abstract

With the advent of multiomics, software capable of multidimensional enrichment analysis has become increasingly crucial for uncovering gene set variations in biological processes and disease pathways. This is essential for elucidating disease mechanisms and identifying potential therapeutic targets. clusterProfiler stands out for its comprehensive utilization of databases and advanced visualization features. Importantly, clusterProfiler supports various biological knowledge, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, through performing over-representation and gene set enrichment analyses. A key feature is that clusterProfiler allows users to choose from various graphical outputs to visualize results, enhancing interpretability. This protocol describes innovative ways in which clusterProfiler has been used for integrating metabolomics and metagenomics analyses, identifying and characterizing transcription factors under stress conditions, and annotating cells in single-cell studies. In all cases, the computational steps can be completed within ~2 min. clusterProfiler is released through the Bioconductor project and can be accessed via https://bioconductor.org/packages/clusterProfiler/.

Key points

  • clusterProfiler is a software package for characterizing and interpreting omics data. Functional enrichment can be achieved using either over-representation or gene set enrichment analyses; it supports the use of a variety of databases, e.g., Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.

  • Three procedures show specific R commands for example applications asking different research questions and having different graphical outputs. Advice is provided on how to modify the procedures for other applications.

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Fig. 1: Overview of the protocol.
Fig. 2: Comparing functional profiles among distinct subtypes of IBD.
Fig. 3: Characterization of the biological functions of transcription factors involved in the response to cold stress in bamboo.
Fig. 4: Identify cell type at single-cell level.

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Data availability

For the integrated analysis of metabolomics and metagenomics, the original metagenomic gene expression data and corresponding metadata, along with metabolomic metabolite expression profiles, were obtained from the supplementary materials of ref. 44. The data can be accessed through PubMed Central at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342642. For the transcriptomics analysis of PE, we obtained the raw FASTQ sequencing data from the CNGBdb database (https://db.cngb.org/search/project/CNP0002243/) and conducted alignment and quantification analyses to determine the expression levels of individual genes. In Procedure 3, we acquired Illumina NextSeq 500 sequencing data for 2,700 PBMCs from 10X Genomics (https://cf.10xgenomics.com/samples/cell/pbmc3k/pbmc3k_filtered_gene_bc_matrices.tar.gz). Source data are provided with this paper.

Code availability

The original data, processed data and source code, including those for processing the original data and demonstrated in the protocol, are all deposited in the GitHub repository, https://github.com/YuLab-SMU/clusterProfiler_protocol/.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (32270677). We appreciate the feedback and support from clusterProfiler users.

Author information

Author notes

  1. These authors contributed equally: Shuangbin Xu, Erqiang Hu, Yantong Cai, Zijing Xie, Xiao Luo.

Authors and Affiliations

  1. Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China

    Shuangbin Xu, Erqiang Hu, Yantong Cai, Zijing Xie, Xiao Luo, Li Zhan, Wenli Tang, Qianwen Wang, Bingdong Liu, Rui Wang, Wenqin Xie, Tianzhi Wu & Guangchuang Yu

  2. Division of Laboratory Medicine, Microbiome Center, Zhujiang Hospital, Southern Medical University, Guangzhou, China

    Shuangbin Xu & Guangchuang Yu

  3. Dermatology Hospital, Southern Medical University, Guangzhou, China

    Yantong Cai & Guangchuang Yu

  4. State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangdong Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China

    Bingdong Liu & Liwei Xie

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  1. Shuangbin Xu
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Contributions

S.X., E.H. and Y.C. wrote the main manuscript and discussed the cases. S.X. and E.H. improved the code. Z.X. and X.L. conducted the pipeline and analyzed the results. L.Z., W.T., Q.W. and B.L. edited the paper for improvement. R.W., W.X., T.W. and L.X. reviewed the paper. G.Y. supervised the project, conducted the analysis and wrote the manuscript.

Corresponding author

Correspondence to Guangchuang Yu.

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The authors declare no competing interests.

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Nature Protocols thanks Juri Reimand, Jianguo Xia and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

Key references using this protocol

Yu, G. et al. OMICS 16, 284–287 (2012): https://doi.org/10.1089/omi.2011.0118

Wu, T. et al. Innovation 2, 100141 (2021): https://doi.org/10.1016/j.xinn.2021.100141

Ne, M. et al. Nat. Commun. 12, 6479 (2021): https://doi.org/10.1038/s41467-021-26685-y

Alexandre, P. A. et al. Genome Biol. 22, 273 (2021): https://doi.org/10.1186/s13059-021-02489-7

Sankowski, R. et al. Nat. Med. 30, 186–198 (2024): https://doi.org/10.1038/s41591-023-02673-1

Supplementary information

Supplementary Information

Supplementary Notes 1 and 2.

Reporting Summary

Supplementary Table 1

Comparisons of clusterProfiler with other tools for enrichment analysis

Source data

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

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Xu, S., Hu, E., Cai, Y. et al. Using clusterProfiler to characterize multiomics data. Nat Protoc 19, 3292–3320 (2024). https://doi.org/10.1038/s41596-024-01020-z

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