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.
Documentation
Downloads
- Source codehttps://github.com/GerkeLab/epiTAD/releases
Links
Repository
https://github.com/GerkeLab/epiTADIssue tracker
https://github.com/GerkeLab/epiTAD/issues