EnhancerAtlas: A resource for enhancer annotation and analysis in 105 human cell/tissue types

Tianshun Gao, Bing He, Sheng Liu, Heng Zhu, Kai Tan, Jiang Qian

Research output: Contribution to journalArticle

Abstract

Motivation: Multiple high-throughput approaches have recently been developed and allowed the discovery of enhancers on a genome scale in a single experiment. However, the datasets generated from these approaches are not fully utilized by the research community due to technical challenges such as lack of consensus enhancer annotation and integrative analytic tools. Results: We developed an interactive database, EnhancerAtlas, which contains an atlas of 2,534,123 enhancers for 105 cell/tissue types. A consensus enhancer annotation was obtained for each cell by summation of independent experimental datasets with the relative weights derived from a cross-validation approach. Moreover, EnhancerAtlas provides a set of useful analytic tools that allow users to query and compare enhancers in a particular genomic region or associated with a gene of interest, and assign enhancers and their target genes from a custom dataset.

Original languageEnglish (US)
Pages (from-to)3543-3551
Number of pages9
JournalBioinformatics
Volume32
Issue number23
DOIs
StatePublished - 2016

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ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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