differential-methylation

You can identify differential methylation regions from WGBS data by processing per-sample BED or BedGraph methylation tracks through a Metilene workflow to output DMRs and DMCs. The process standardizes inputs into per-sample methylation tables, merges them into a matrix, and executes Metilene to detect differential sites across experimental conditions.

Calling DMRs and DMCs across experimental conditions is best handled by standardizing heterogeneous BED inputs into a merged methylation matrix and running Metilene with tunable parameters. This approach filters results and generates visualizations such as Δmethylation vs –log10(q) plots and length histograms for interpretation.

Yes, you need per-sample BED or BedGraph methylation files to run methylation analysis with Metilene. The workflow standardizes these heterogeneous inputs into per-sample four-column Metilene tables containing chromosome, start, end, and methylation fraction before merging them for analysis.

You can visualize methylation differences after detecting DMRs through generated plots including Δmethylation vs –log10(q) scatter plots and length histograms. These visualizations are produced automatically alongside filtered DMR and DMC results to aid interpretation of differential methylation patterns.

This differential methylation workflow works for both genome-wide and targeted methylation analyses. It accepts BED and BedGraph inputs from WGBS methylation tracks and applies Metilene to detect DMRs and DMCs across the specified genomic regions for case versus control comparisons.

Metilene analysis requires a merged methylation matrix because the tool needs standardized per-sample inputs combined into a single structure to compare methylation fractions across experimental conditions. The workflow builds this matrix from individual four-column Metilene tables before executing the differential methylation detection.