Matteo Benelli, Gian Marco Franceschini, Alberto Magi, Dario Romagnoli, Chiara Biagioni, Ilenia Migliaccio, Luca Malorni, Francesca Demichelis
Communications biology 2021 Nov 02Differentially 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).
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
PMID: 34728774
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