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Differential analysis of RNA methylome with improved spatial resolution

机译:具有改进的空间分辨率的RNA甲基化组的差异分析

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Recent development of MeRIP-Seq enabled the global unbiased profiling of transcriptome-wide N6-Adenosine. With this technique, it is now possible to detect the RNA methylation sites under a specific condition or the differential methylation sites between two experimental conditions. However, as an affinity-based approach, MeRIP-Seq has yet provided base-pair resolution. A single methylation site reported by MeRIP-Seq data may actually contain one or a few methylated RNA residuals, which cannot be differentiated by existing differential analysis methods when the entire RNA methylation site is treated as a single feature. Within this paper, we propose a new approach `RHHMM' that combines Fisher's exact test and hidden Markov model (HMM) for the detection of differential methylation regions (DMRs) with improved spatial resolution. The results on both simulated and real data demonstrated that, with HMM incorporating local spatial dependency, it is possible to detect differential methylation sites with improved spatial resolution on affinity-based sequencing approach such as MeRIP-Seq. The proposed method is freely available as an open source R package.
机译:MeRIP-Seq的最新发展实现了转录组范围的N6-腺苷的全球无偏倚分析。利用这种技术,现在可以检测特定条件下的RNA甲基化位点或两个实验条件之间的差异甲基化位点。但是,作为基于亲和性的方法,MeRIP-Seq尚未提供碱基对解析。 MeRIP-Seq数据报告的单个甲基化位点实际上可能包含一个或几个甲基化的RNA残基,当将整个RNA甲基化位点视为一个特征时,现有的差异分析方法无法区分这些残基。在本文中,我们提出了一种新的方法“ RHHMM”,该方法结合了Fisher精确测试和隐马尔可夫模型(HMM)来检测具有改进的空间分辨率的差异甲基化区域(DMR)。在模拟和真实数据上的结果均表明,通过结合局部空间依赖性的HMM,可以在基于亲和力的测序方法(例如MeRIP-Seq)上以提高的空间分辨率检测差异甲基化位点。所提出的方法可以作为开源R包免费获得。

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