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Erratum to: DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning

机译:勘误至:DeepCpG:使用深度学习准确预测单细胞DNA甲基化状态

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The iCLIP and eCLIP techniques facilitate the detection of protein–RNA interaction sites at high resolution, based on diagnostic events at crosslink sites. However, previous methods do not explicitly model the specifics of iCLIP and eCLIP truncation patterns and possible biases. We developed PureCLIP (https://github.com/skrakau/PureCLIP), a hidden Markov model based approach, which simultaneously performs peak-calling and individual crosslink site detection. It explicitly incorporates a non-specific background signal and, for the first time, non-specific sequence biases. On both simulated and real data, PureCLIP is more accurate in calling crosslink sites than other state-of-the-art methods and has a higher agreement across replicates.
机译:基于交联位点的诊断事件,iCLIP和eCLIP技术有助于高分辨率检测蛋白质-RNA相互作用位点。但是,以前的方法没有明确地建模iCLIP和eCLIP截断模式的细节以及可能的偏差。我们开发了PureCLIP(https://github.com/skrakau/PureCLIP),这是一种基于隐马尔可夫模型的方法,可同时执行峰调用和单个交联站点检测。它明确纳入了非特异性背景信号,并且首次引入了非特异性序列偏倚。在模拟数据和实际数据上,PureCLIP在调用交叉链接站点方面都比其他最新技术更为准确,并且在复制中具有更高的一致性。

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