MethGET

MethGET performs correlation analysis between genome-wide DNA methylation (CG, CHG, CHH) from whole-genome bisulfite sequencing and gene expression to investigate epigenetic regulation.

Key Features:

• User-provided data: Accepts DNA methylation and gene expression datasets from any genome.
• Cytosine contexts supported: Analyzes CG, CHG, and CHH methylation derived from whole-genome bisulfite sequencing.
• Correlation methods: Computes Pearson correlations and ordinal association methods to assess relationships between methylation and expression.
• Single-methylome analysis: Groups genes by expression level and visualizes methylation distribution at specific genomic regions.
• Multiple-methylome analysis: Performs comparative assessments between sample groups and generates heatmap representations to highlight differences.
• Genomic location-specific insights: Correlates different methylation types with gene expression across genomic locations to infer regulatory roles.
• Applied example: Has been applied to rice regeneration data, revealing potential roles for CHH methylation in tissue culture processes.

Scientific Applications:

• Epigenetic regulation studies: Investigates the interplay between DNA methylation and gene expression to elucidate regulatory mechanisms.
• Comparative epigenomics: Compares methylation-expression relationships across sample groups, species, and environmental conditions.
• Organism-specific applications: Supports analyses in plant biology (e.g., rice regeneration) and can be applied to questions relevant to human health.

Methodology:

Uses whole-genome bisulfite sequencing-derived methylation data and gene expression data, computes Pearson correlations and ordinal association methods, groups genes by expression level, and produces methylation distribution plots and heatmaps for comparative analysis.