EpiVar Browser: advanced exploration of epigenomics data under controlled access.

Area of Science:

• Genomics and Epigenomics
• Bioinformatics and Computational Biology

Background:

• Large-scale human epigenomic datasets are vital for understanding normal and disease chromatin states.
• Epigenetic data, like genetic data, contains potentially identifiable information, necessitating controlled access.
• Secure sharing of sensitive epigenomics data is essential for scientific advancement.

Purpose of the Study:

• To develop a method and tool for exploring epigenomics datasets while filtering out identifiable information.
• To enable genotype-chromatin phenotype relationship exploration within large epigenomic cohorts.
• To facilitate responsible access to sensitive epigenomics data, accelerating research.

Main Methods:

• Developed an approach guided by the Global Alliance for Genomics and Health (GA4GH) data sharing framework.
• Created the EpiVar Browser, a tool for navigating aggregated epigenomics dataset results.
• Implemented aggregation of individual genotypes and epigenetic signal tracks to prevent direct access.

Main Results:

• The EpiVar Browser allows dynamic genotype-epigenome interrogation without releasing identifiable data.
• Exploration of genotype-chromatin phenotype relationships is directly enabled through the portal.
• The approach successfully filters out identifiable information from epigenomics datasets.

Conclusions:

• The EpiVar Browser provides a secure and accessible platform for sensitive epigenomics data exploration.
• This approach accelerates research by bypassing lengthy approval processes for data access.
• The developed strategy offers a generalizable model for responsible sharing of epigenomics data.