scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.
Tianshun GaoZilong ZhengYihang PanChengming ZhuFuxin WeiJinqiu YuanRui SunShuo FangNan WangYang ZhouJiang QianPublished in: Nucleic acids research (2021)
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.
Keyphrases
- single cell
- rna seq
- high throughput
- genome wide
- induced apoptosis
- transcription factor
- genome wide identification
- cell cycle arrest
- machine learning
- healthcare
- copy number
- endoplasmic reticulum stress
- mental health
- stem cells
- gene expression
- dna methylation
- minimally invasive
- genome wide analysis
- genetic diversity
- deep learning
- cell proliferation
- adverse drug
- electronic health record