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Cancer methylomes characterization enabled by Rocker-meth

Benelli, M.; Franceschini, G. M.; Magi, A.; Romagnoli, D.; Biagioni, C.; Migliaccio, I.; Malorni, L.; Di Leo, A.; Demichelis, F.

2020-10-09 cancer biology
10.1101/2020.10.09.332759 bioRxiv
Show abstract

Differentially DNA methylated regions (DMRs) inform on the role of epigenetic changes in cancer. We present Rocker-meth, a computational method exploiting a heterogeneous hidden Markov model to detect DMRs across multiple experimental platforms. Its application to more than 6,000 methylation profiles across 14 tumor types provides a comprehensive catalog of tumor type-specific and shared DMRs, also amenable to single-cell DNA-methylation data. 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.

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