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.

中文翻译：

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Rocker-meth使癌症甲基化组表征成为可能

DNA甲基化差异区（DMR）告知表观遗传变化在癌症中的作用。我们提出了Rocker-meth，一种利用异构隐马尔可夫模型检测跨多个实验平台的DMR的计算方法。它在14种肿瘤类型的6,000多种甲基化谱图中的应用提供了肿瘤类型特异性和共享DMR的全面目录，也适用于单细胞DNA甲基化数据。包括正交组学在内的深度综合分析表明，Rocker-meth在概括已知关联方面的能力得到了增强，进一步揭示了DNA超甲基化与转录因子失调之间的泛癌关系（取决于基线染色质状态）。