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scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.
Gao, Tianshun; Zheng, Zilong; Pan, Yihang; Zhu, Chengming; Wei, Fuxin; Yuan, Jinqiu; Sun, Rui; Fang, Shuo; Wang, Nan; Zhou, Yang; Qian, Jiang.
Afiliação
  • Gao T; Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Zheng Z; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Pan Y; Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Zhu C; Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Wei F; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Yuan J; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Sun R; Department of Orthopaedics, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Fang S; Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Wang N; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Zhou Y; Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
  • Qian J; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.
Nucleic Acids Res ; 50(D1): D371-D379, 2022 01 07.
Article em En | MEDLINE | ID: mdl-34761274
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Elementos Facilitadores Genéticos / Bases de Dados Genéticas / Análise de Célula Única / Aprendizado de Máquina não Supervisionado Limite: Animals / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Elementos Facilitadores Genéticos / Bases de Dados Genéticas / Análise de Célula Única / Aprendizado de Máquina não Supervisionado Limite: Animals / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article