dbInDel

dbInDel catalogs enhancer-associated insertion and deletion (InDel) variants by integrating high-throughput chromatin immunoprecipitation sequencing (ChIP-Seq) data for H3K27ac to elucidate their regulatory roles in the human and murine cancer epigenome.


Key Features:

  • Comprehensive compilation: Assembles insertion and deletion (InDel) variants associated with enhancer regions to support analysis of non-coding genomic aberrations in cancer.
  • H3K27ac ChIP-Seq integration: Utilizes H3K27ac chromatin immunoprecipitation sequencing data to identify active enhancers and map InDels within those regions.
  • Transcription factor (TF) motif analysis: Identifies and visualizes upstream TF binding motifs present in enhancers containing InDels.
  • Downstream target prediction: Predicts downstream target genes affected by enhancer-associated InDels to link variants to potential gene regulatory consequences.
  • Support for functional studies: Provides compiled and annotated enhancer-associated InDels to facilitate prioritization for downstream functional validation.

Scientific Applications:

  • Cancer epigenomics: Investigation of how enhancer-associated InDels contribute to dysregulation of transcriptional programs in cancer.
  • Functional genomics: Identification and prioritization of non-coding InDels for experimental validation of regulatory impact on gene expression.
  • Transcription factor research: Analysis of how InDels alter TF binding motifs and potentially modify transcriptional regulation.

Methodology:

Integrates high-throughput H3K27ac ChIP-Seq data to identify active enhancers and map insertion and deletion variants within those regions in human and murine samples.

Topics

Details

Tool Type:
web application
Added:
1/9/2020
Last Updated:
12/17/2020

Operations

Publications

Huang M, Wang Y, Yang M, Yan J, Yang H, Zhuang W, Xu Y, Koeffler HP, Lin D, Chen X. dbInDel: a database of enhancer-associated insertion and deletion variants by analysis of H3K27ac ChIP-Seq. Bioinformatics. 2019;36(5):1649-1651. doi:10.1093/bioinformatics/btz770. PMID:31603498. PMCID:PMC7703781.

PMID: 31603498
PMCID: PMC7703781
Funding: - National Key R&D Program of China: 2018YFA0801100 - National Natural Science Foundation of China: 31971117, 81672873