qsea

qsea transforms MeDIP-seq and related quantitative sequencing read counts into absolute DNA methylation estimates using a Bayesian statistical model for quantitative enrichment analysis.

Key Features:

• Bayesian model: Transforms raw enrichment read counts into absolute levels of methylation.
• Supported data types: Processes MeDIP-seq, ChIP-seq, MBD-seq, CMS-seq and other quantitative sequencing datasets.
• Differential enrichment analysis: Performs differential enrichment analysis across diverse sample groups.
• Calibration strategies: Offers multiple strategies to calibrate critical model parameters using additional datasets or general assumptions.
• Validation against bisulfite sequencing: Shows improved methylation quantification when compared with bisulfite sequencing (BS) validation data.
• Integrative analysis: Applied to combined MeDIP-seq, Methyl-seq, and RNA-seq datasets to identify methylation markers that influence gene expression.

Scientific Applications:

• Quantitative DNA methylation estimation: Produces absolute methylation level estimates from MeDIP-seq and related assays.
• Differential methylation analysis: Detects differential enrichment between sample groups for comparative studies.
• Method benchmarking and validation: Enables assessment and improvement of MeDIP-seq quantification through comparison with bisulfite sequencing.
• Integrative cancer genomics: Identifies tumor-associated methylation markers linked to gene expression changes in non-small cell lung cancer using MeDIP-seq, Methyl-seq, and RNA-seq.

Methodology:

Uses a Bayesian statistical model to convert raw enrichment read counts into absolute methylation levels and employs calibration strategies for critical model parameters using additional datasets or general assumptions.