ScEnhancer: A single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species

Tianshun Gao, Zilong Zheng, Yihang Pan, Chengming Zhu, Fuxin Wei, Jinqiu Yuan, Rui Sun, Shuo Fang, Nan Wang, Yang Zhou, Jiang Qian

Research output: Contribution to journalArticlepeer-review


Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populations. In recent years, single-cell sequencing technology has enabled the profiling of open chromatin accessibility at the single-cell level (scATAC-seq), which can be used to annotate the enhancers and promoters in specific cell types. A comprehensive resource is highly desirable for exploring how the enhancers regulate the target genes at the single-cell level. Hence, we designed a single-cell database scEnhancer (, covering 14 527 776 enhancers and 63 658 600 enhancer-gene interactions from 1 196 906 single cells across 775 tissue/cell types in three species. An unsupervised learning method was employed to sort and combine tens or hundreds of single cells in each tissue/cell type to obtain the consensus enhancers. In addition, we utilized a cis-regulatory network algorithm to identify the enhancer-gene connections. Finally, we provided a user-friendly platform with seven useful modules to search, visualize, and browse the enhancers/genes. This database will facilitate the research community towards a functional analysis of enhancers at the single-cell level.

Original languageEnglish (US)
Pages (from-to)D371-D379
JournalNucleic acids research
Issue numberD1
StatePublished - Jan 7 2022

ASJC Scopus subject areas

  • Genetics


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