MethReg

MethReg evaluates, prioritizes and annotates CpG sites with high regulatory potential by integrative modeling of DNA methylation, target gene expression and transcription factor binding sites data.

Key Features:

• Integrative Modeling: Analyzes matched DNA methylation and gene expression data together with external transcription factor binding information.
• TF-Target Interaction Integration: Utilizes external TF-target interaction databases based on manual curation, ChIP-seq experiments or gene regulatory network analysis.
• Conditional Association Detection: Identifies TF-target gene associations that are only present in subsets of samples with high or low methylation levels, which can be missed by analyses using all samples.
• Systematic Ranking: Systematically identifies and ranks functional CpG methylations from large sets of differentially methylated regions and CpGs detected by epigenome-wide association studies.

Scientific Applications:

• Epigenome-Wide Association Study Prioritization: Prioritizes significant CpG sites from EWAS that are located in distal regulatory regions or non-coding regions by assessing their functional impact on gene transcription.
• Complex Disease Research: Enhances understanding of the regulatory roles of DNA methylation in complex diseases, as demonstrated in colorectal cancer and Alzheimer's disease datasets.
• Transcriptional Regulation Analysis: Investigates CpG methylation-dependent transcriptional regulation, a widespread phenomenon in gene expression control.

Methodology:

MethReg performs integrative modeling of DNA methylation, target gene expression and transcription factor binding sites data, using external TF-target interaction databases based on manual curation, ChIP-seq experiments or gene regulatory network analysis.