Epilogos: information-theoretic navigation of multi-tissue functional genomic annotations.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Functional genomics data, including chromatin state maps, are crucial for understanding biological processes.
• Existing datasets are vast and challenging to navigate and interpret effectively.

Purpose of the Study:

• To present Epilogos, a novel framework for large-scale visualization, navigation, and interpretation of functional genomics annotations.
• To apply Epilogos to over 2,000 human and mouse genome-wide chromatin state maps.

Main Methods:

• Development of an information-theoretic framework for data analysis.
• Construction of intuitive visualizations for multi-tissue chromatin state maps.
• Implementation of algorithms for prioritizing genomic regions, identifying differential regions, and performing similarity searches.

Main Results:

• Epilogos enables intuitive visualization of complex chromatin state data.
• The framework successfully prioritizes salient genomic regions and identifies group-wise differential regions.
• Rapid similarity search functionality is provided for regions of interest.

Conclusions:

• Epilogos offers a user-friendly approach to interpreting large-scale functional genomics data.
• The associated web browser and open-source software promote accessibility and adoption by the scientific community.