TY - JOUR
T1 - ScEnhancer
T2 - A single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species
AU - Gao, Tianshun
AU - Zheng, Zilong
AU - Pan, Yihang
AU - Zhu, Chengming
AU - Wei, Fuxin
AU - Yuan, Jinqiu
AU - Sun, Rui
AU - Fang, Shuo
AU - Wang, Nan
AU - Zhou, Yang
AU - Qian, Jiang
N1 - Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.
PY - 2022/1/7
Y1 - 2022/1/7
N2 - 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 (http://enhanceratlas.net/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.
AB - 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 (http://enhanceratlas.net/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.
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U2 - 10.1093/nar/gkab1032
DO - 10.1093/nar/gkab1032
M3 - Article
C2 - 34761274
AN - SCOPUS:85123389214
SN - 1362-4962
VL - 50
SP - D371-D379
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - D1
ER -