CellWalkR: an R package for integrating and visualizing single-cell and bulk data to resolve regulatory elements.

Area of Science:

• Genomics
• Computational Biology
• Bioinformatics

Background:

• Single-cell epigenomic data analysis is crucial for understanding cellular heterogeneity.
• Identifying cell type-specific regulatory regions is challenging with current tools.
• Integrating multiple epigenetic datasets can improve regulatory element identification.

Purpose of the Study:

• To develop an efficient R package for analyzing single-cell open chromatin data.
• To enable the identification of cell type-specific regulatory regions.
• To provide a user-friendly tool for interactive epigenetic data exploration.

Main Methods:

• CellWalkR integrates single-cell open chromatin data with cell type labels and bulk epigenetic data.
• A Graphics Processing Unit (GPU) implementation and downsampling strategies accelerate analysis.
• The package offers an interactive interface for analysis and visualization.

Main Results:

• CellWalkR can process thousands of cells in seconds, enabling large-scale analyses.
• The package successfully identifies cell type-specific regulatory regions.
• Interactive visualizations aid in understanding cell labels and regulatory region mappings.

Conclusions:

• CellWalkR provides an efficient and user-friendly solution for single-cell epigenomic data analysis.
• The tool facilitates the discovery of cell type-specific regulatory elements.
• CellWalkR is a valuable addition to the bioinformatics toolkit for epigenetics research.