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CMEnt is a comprehensive tool for identifying Differentially Methylated Regions (DMRs) from genomic seeds, commonly Differentially Methylated Positions (DMPs). The package uses a correlation-based approach to expand regions around significant seeds, considering both statistical significance and biological relevance of methylation changes.

Main Functions

Input Data

The package accepts multiple types of methylation data input:

  • Beta value files: Tab-separated files containing methylation beta values

  • Tabix files: Indexed bed.gz files for efficient access to large datasets

  • BED files: Custom methylation BED files (automatically converted to tabix)

  • Beta matrices: In-memory beta value matrices

Platform Support

The package supports methylation data from multiple platforms:

  • Human arrays: 450K, EPIC (850k), EPICv2, 27K on hg19, hg38, or hs1

  • Mouse arrays: mm10, mm39 genomes

  • NGS data: Via tabix-indexed files

  • Custom platforms: Via BED file input

Workflow

  1. Start with genomic seeds (e.g., DMPs) from any differential analysis

  2. Provide methylation data (multiple formats supported)

  3. Define parameters for region expansion and connectivity

  4. Get DMRs as a GRanges object with comprehensive statistics

  5. Optionally extract motifs and compute DMR interactions

  6. Visualize with structure plots, heatmaps, and circos plots

Author

Maintainer: Vasileios Lemonidis vasileios.lemonidis@uantwerpen.be (ORCID) [copyright holder]

Authors:

Other contributors:

  • Center for Oncological Research, University of Antwerp [copyright holder, funder]

  • Stichting Tegen Kanker [funder]