clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

Tianzhi Wu; Erqiang Hu; Shuangbin Xu; Meijun Chen; Pingfan Guo; Zehan Dai; Tingze Feng; Lang Zhou; Wenli Tang; Li Zhan; Xiaocong Fu; Shanshan Liu; Xiaochen Bo; Guangchuang Yu

doi:10.1016/j.xinn.2021.100141

clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

Innovation (Camb). 2021 Jul 1;2(3):100141. doi: 10.1016/j.xinn.2021.100141. eCollection 2021 Aug 28.

Authors

Tianzhi Wu¹, Erqiang Hu¹, Shuangbin Xu¹, Meijun Chen¹, Pingfan Guo¹, Zehan Dai¹, Tingze Feng¹, Lang Zhou¹, Wenli Tang¹, Li Zhan¹, Xiaocong Fu¹, Shanshan Liu¹, Xiaochen Bo², Guangchuang Yu^{1

3

4}

Affiliations

¹ Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
² Department of Biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China.
³ Guangdong Provincial Key Laboratory of Proteomics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
⁴ Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China.

Abstract

Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.

Keywords: biological knowledge mining; clusterProfiler; enrichment analysis; functional analysis; visualization.