Metheor

Metheor computes and analyzes DNA methylation heterogeneity from Bismark-aligned bisulfite sequencing reads by leveraging phased CpG methylation states to estimate epigenetic diversity and epigenomic instability across cells.

Key Features:

• Implementation: Implemented in Rust.
• Performance: Reduces execution time by up to 300-fold and memory usage by up to 60-fold compared to existing implementations.
• Comprehensive analysis: Applies multiple measures of DNA methylation heterogeneity by leveraging phased methylation states present in bisulfite sequencing reads rather than relying solely on average CpG methylation levels.
• Scalability: Demonstrated capability across three benchmarking scenarios using simulated bisulfite sequencing datasets to handle extensive genomic analyses.
• Large-scale profiling: Low computational burden enables computation of methylation heterogeneity profiles for large datasets (for example, 928 cancer cell lines) and supports exploration of associations with other omics features.

Scientific Applications:

• Epigenomic heterogeneity profiling: Quantifies diversity of DNA methylation states across or within cells to inform studies of cellular variability.
• Cancer epigenomics: Enables investigation of links between DNA methylation heterogeneity and cancer biology.
• Multi-omics association studies: Supports analysis of associations between methylation heterogeneity and other omics features.

Methodology:

Operates on Bismark-aligned bisulfite sequencing reads, analyzes pairs or groups of CpGs genome-wide using phased methylation states to assess methylation heterogeneity, is implemented in Rust, and was benchmarked using simulated bisulfite sequencing datasets across three scenarios.