BEAT

BEAT performs model-based analysis of single-cell DNA methylation data to characterize cell-to-cell variability in methylation patterns and support epigenetic and genomic studies.

Key Features:

• Model-Based Analysis: Constructs and applies statistical models to interpret single-cell methylation patterns.
• Single-Cell Resolution: Analyzes methylation at single-cell granularity to capture cell-to-cell heterogeneity.
• Bioconductor and R integration: Operates within the Bioconductor ecosystem and integrates with R for interoperability with genomic analysis packages.

Scientific Applications:

• Epigenetic Research: Enables investigation of DNA methylation changes and their roles in gene regulation at single-cell resolution.
• Cancer Genomics: Supports analysis of tumor heterogeneity and identification of methylation markers associated with cancer progression.
• Developmental Biology: Facilitates study of methylation dynamics underlying cell differentiation and developmental processes.

Methodology:

Applies a model-based statistical approach that constructs models to interpret complex single-cell methylation data and account for inherent cell-to-cell variability.