Methpat

Methpat analyzes and visualizes clonal DNA methylation patterns from massively parallel bisulfite sequencing to characterize epiallelic heterogeneity at CpG sites and gene promoter regions.

Key Features:

• Clonal epiallele extraction: Extracts clonal DNA methylation (epiallele) patterns from massively parallel sequencing data.
• Alignment with Bismark: Aligns bisulfite sequencing reads using Bismark.
• Visualization of allelic distribution: Implements synoptic approaches for visualizing allelic distribution and epiallelic diversity.
• Support for multiplex bisulfite amplicon sequencing: Processes data from multiplex bisulfite amplicon sequencing across CpG island targets.
• Promoter-region resolution: Depicts clonal diversity of epialleles at specific gene promoter regions.
• Mitochondrial epialleles: Describes epiallelic methylation within mitochondrial genomes.
• Compact summary format: Produces a compact, interpretable format for summarizing and visualizing epiallelic DNA methylation results.
• Deep sequencing scalability: Handles the volume of information generated by deep and massively parallel sequencing technologies.

Scientific Applications:

• Epiallelic heterogeneity characterization: Characterizes allelic and cell-type-specific methylation patterns beyond per-CpG averages.
• Bisulfite amplicon studies: Applied to multiplex bisulfite amplicon sequencing analyses in human cell lines and primary tissues.
• Promoter methylation analysis: Resolves clonal methylation patterns at gene promoter regions to inform transcriptional regulation studies.
• Mitochondrial methylation profiling: Enables investigation of epiallelic methylation within mitochondrial genomes.
• Visualization for heterogeneity assessment: Visualizes epiallelic diversity to assess sample-level methylation heterogeneity.

Methodology:

Methpat aligns bisulfite sequencing reads with Bismark and extracts, analyzes, and visualizes clonal DNA methylation (epiallele) patterns from massively parallel or multiplex bisulfite amplicon sequencing data.