Charting differentially methylated regions in cancer with Rocker-meth.

Differentially DNA methylated regions (DMRs) inform on the role of epigenetic changes in cancer. We present Rocker-meth, a new computational method exploiting a heterogeneous hidden Markov model to detect DMRs across multiple experimental platforms. Through an extensive comparative study, we first demonstrate Rocker-meth excellent performance on synthetic data. Its application to more than 6,000 methylation profiles across 14 tumor types provides a comprehensive catalog of tumor type-specific and shared DMRs, and agnostically identifies cancer-related partially methylated domains (PMD). In depth integrative analysis including orthogonal omics shows the enhanced ability of Rocker-meth in recapitulating known associations, further uncovering the pan-cancer relationship between DNA hypermethylation and transcription factor deregulation depending on the baseline chromatin state. Finally, we demonstrate the utility of the catalog for the study of colorectal cancer single-cell DNA-methylation data. © 2021. The Author(s).

Citation

Matteo Benelli, Gian Marco Franceschini, Alberto Magi, Dario Romagnoli, Chiara Biagioni, Ilenia Migliaccio, Luca Malorni, Francesca Demichelis. Charting differentially methylated regions in cancer with Rocker-meth. Communications biology. 2021 Nov 02;4(1):1249

Mesh Tags

PMID: 34728774

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