Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, Berlin, 14195, Germany.
Sorbonne Universités, UPMC Univ Paris 06, CNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), 4 place Jussieu, Paris, 75005, France.
Genome Biol. 2017 Dec 28;18(1):240. doi: 10.1186/s13059-017-1364-2.
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.
iCLIP 和 eCLIP 技术基于交联位点的诊断事件,以高分辨率促进蛋白质-RNA 相互作用位点的检测。然而,以前的方法并没有明确地模拟 iCLIP 和 eCLIP 截断模式和可能的偏差。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,它同时进行峰调用和单个交联位点检测。它明确地包含了非特异性背景信号,并首次包含了非特异性序列偏差。在模拟和真实数据上,PureCLIP 在调用交联位点方面比其他最先进的方法更准确,并且在复制之间具有更高的一致性。