methylFlow

methylFlow reconstructs cell-specific DNA methylation patterns from high-throughput bisulfite-converted DNA sequencing data to characterize epigenetic heterogeneity in tumor samples.

Key Features:

• Reconstruction of Heterogeneous Methylation Patterns: Assembles cell-specific methylation patterns from high-throughput bisulfite-converted sequencing reads to resolve methylation heterogeneity in heterogeneous tumor samples, including colon cancer.
• Analysis of Clonal and Population Heterogeneity: Analyzes clonal and population-level heterogeneity across high-coverage sequencing data from multiple samples to elucidate relationships between clonal structure and population diversity in tumors.
• Network Flow Problem Solving: Formulates and solves specific classes of minimum cost network flow problems to enable efficient and accurate reconstruction of methylation patterns across cell populations.

Scientific Applications:

• Cancer Research: Identifies genomic regions with differential methylation between tumor and normal tissue, applied to the colon cancer epigenome to study how methylation aberrations contribute to gene expression heterogeneity and tumor development.
• Epigenetic Studies: Dissects population-level DNA methylation dynamics and heterogeneity across various cancer types to support broader epigenomic analyses.

Methodology:

Processes high-throughput bisulfite-converted DNA sequencing data and reconstructs cell-specific methylation patterns by solving specific classes of minimum cost network flow problems.