WashU Epigenome Browser

WashU Epigenome Browser visualizes and analyzes epigenomic datasets through a web-based platform with expanded support for long-read and single-cell methylation data.

Key Features:

• Codebase rewrite: The browser uses a completely rewritten codebase that minimizes external libraries, resulting in smaller code bundle size after production compilation.
• Performance improvements: Reduced code size improves loading efficiency and boosts scripting, graphics rendering, and painting performance.
• Modular design: The codebase features a new modular design enabling the browser to be exported as stand-alone modules for use in other web applications.
• Long-read methylation tracks: Novel track types for long-read methylation data visualization have been added.
• Single-cell methylation tracks: Novel track types for single-cell methylation data visualization have been added.
• Comparative genomics track function: The browser supports systematic comparison of genomic data mapped to different genome assemblies, with a data hub comparing hg38 and the first human T2T genome chm13.
• Data hub hosting: The browser hosts and continues to expand data hubs for major consortia.
• Platform foundation: The browser serves as a foundation for other genomics platforms including the WashU Virus Genome Browser for SARS-COV-2 research, the WashU Comparative Epigenome Browser, and the WashU Repeat Browser.

Scientific Applications:

• Epigenomic data exploration: Investigators interact with extensive genomic data for visualization, investigation, and analysis of epigenomic datasets.
• Long-read methylation analysis: Visualization and analysis of methylation data generated from long-read sequencing technologies.
• Single-cell methylation analysis: Visualization and analysis of methylation data at single-cell resolution.
• Comparative genomics: Systematic comparison of genomic data mapped to different genome assemblies, such as hg38 and chm13.
• Virus genomics research: The underlying platform supports specialized browsers for SARS-COV-2 research.
• Comparative epigenomics: The underlying platform supports cross-species epigenomic comparisons.
• Repeat element analysis: The underlying platform supports specialized browsers for repeat genome analysis.

Methodology:

The browser minimizes use of external JavaScript libraries to reduce production code bundle size, implements modular architecture for component export, and uses a comparative genomics track function to align and display data across different genome assemblies.