BioMethyl

BioMethyl performs biological interpretation of DNA methylation datasets from The Cancer Genome Atlas (TCGA) by integrating DNA methylation and gene expression profiles to enable gene set–level pathway enrichment analyses in cancer research.

Key Features:

• Comprehensive Data Utilization: Leverages complete DNA methylation datasets for specific TCGA cancer types to reflect corresponding gene expression profiles and reduce bias from gene length variability.
• Pathway Enrichment Analysis: Performs pathway enrichment analyses from DNA methylation data and shows high concordance with RNA sequencing (RNA-seq) results in breast cancer, achieving a Jaccard score of 0.8 for estrogen receptor (ER) positive samples.
• Identification of Hidden Pathways: Identifies biological pathways from methylation data when gene expression profiles are unavailable or incomplete.
• Gene-set-level Interpretation: Interprets bulk tissue DNA methylation at the gene set level rather than focusing on individual differentially methylated CpG sites or regions.

Scientific Applications:

• Cancer epigenetic characterization: Characterizing epigenetic modifications across TCGA cancer subtypes to inform diagnostic and therapeutic research.
• Pathway discovery: Revealing pathways implicated in cancer progression and response to treatment through methylation-based pathway enrichment.
• Integrative validation with RNA-seq: Comparing methylation-derived pathway results with RNA-seq to assess concordance and validate epigenetic signals.

Methodology:

Computational models integrate DNA methylation data with gene expression profiles to perform gene set–level biological interpretation and pathway enrichment analyses, mitigating biases from analyses that focus on individual CpG sites, regions, or gene length variability.