Repitools

Repitools provides analysis of enrichment-based epigenomic data and quantification of regional DNA methylation from affinity-capture high-throughput sequencing, including the BayMeth empirical Bayes method.

Key Features:

• BayMeth empirical Bayes framework: Employs an empirical Bayes framework to estimate regional methylation levels from enrichment-based sequencing data.
• Fully methylated control calibration: Leverages a fully methylated control sample to calibrate observed read counts.
• Read-count-to-methylation conversion: Transforms observed read counts into regional methylation level estimates.
• Copy number variation modeling: Incorporates explicit modeling of copy number variation to aid interpretation in altered genomic regions.
• Analytical estimators: Provides computationally efficient analytical estimators for the mean and variance of methylation levels.
• Input data support: Operates on enrichment-based epigenomic data derived from affinity-capture combined with high-throughput sequencing.
• Cost–coverage trade-off: Addresses the trade-off between whole-genome bisulfite sequencing cost and methylation array coverage by enabling quantification from enrichment data.

Scientific Applications:

• Regional methylation quantification: Quantifies regional DNA methylation from affinity-capture sequencing experiments.
• Differential methylation detection: Identifies differentially methylated regions between conditions or samples.
• Epigenomic visualization: Supports visualization of epigenomic modifications across gene promoters within specific expression contexts.
• Capture efficiency assessment: Distinguishes inefficient capture events from genuinely low methylation levels.
• CNV-aware interpretation: Enables interpretation of methylation signals in regions affected by copy number variation.

Methodology:

BayMeth applies an empirical Bayes framework that uses a fully methylated control to convert observed read counts from affinity-capture high-throughput sequencing into regional methylation level estimates, includes explicit copy number variation modeling, and computes analytical mean and variance estimators.