epiTAD

epiTAD integrates chromosome conformation capture data with genomic annotations to visualize and compare three-dimensional genome organization at a genome-wide scale.


Key Features:

  • 3D genome visualization: Integrates chromosome conformation capture data to represent genomic three-dimensional organization.
  • Comparative genomic organization: Compares 3D genome architecture and genomic annotations across multiple public genomic databases.
  • Genome-wide integration: Performs integrative, genome-wide analyses linking three-dimensional organization with genetic annotations.
  • Data integration: Incorporates chromosome conformation capture data alongside diverse genomic annotations for joint analysis.
  • In silico discovery support: Enables identification of candidate regulatory elements and generation of hypotheses about spatially mediated gene regulation and disease mechanisms.

Scientific Applications:

  • Genetic epidemiology: Supports integrative analyses associating spatial genome architecture with genetic variants and disease risk.
  • Gene regulation: Facilitates investigation of how three-dimensional genome organization influences gene expression.
  • Disease mechanism investigation: Enables exploration of spatial relationships between regulatory elements and disease-associated loci.
  • Regulatory element discovery: Aids identification of potential regulatory elements through co-localization of 3D contacts and annotations.

Methodology:

Leverages public genomic databases and chromosome conformation capture data to integrate three-dimensional genome structure with genetic annotations for comparative, genome-wide analyses.

Topics

Details

License:
MIT
Maturity:
Mature
Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
8/9/2019
Last Updated:
11/24/2024

Operations

Publications

Creed JH, Aden-Buie G, Monteiro AN, Gerke TA. epiTAD: a web application for visualizing chromosome conformation capture data in the context of genetic epidemiology. Bioinformatics. 2019;35(21):4462-4464. doi:10.1093/bioinformatics/btz387. PMID:31099399. PMCID:PMC7963078.

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