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covNorm: An R package for coverage based normalization of Hi-C and capture Hi-C data

机译:Covnorm:用于覆盖的基于Hi-C标准化的R包,并捕获Hi-C数据

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Hi-C and capture Hi-C have greatly advanced our understanding of the principles of higher-order chromatin structure. In line with the evolution of the Hi-C protocols, there is a demand for an advanced computational method that can be applied to the various forms of Hi-C protocols and effectively remove innate biases. To resolve this issue, we developed an implicit normalization method named “covNorm” and implemented it as an R package. The proposed method can perform a complete procedure of data processing for Hi-C and its variants. Starting from the negative binomial model-based normalization for DNA fragment coverages, removal of genomic distance-dependent background and calling of the significant interactions can be applied sequentially. The performance evaluation of covNorm showed enhanced or similar reproducibility in terms of HiC-spector score, correlation of compartment A/B profiles, and detection of reproducible significant long-range chromatin contacts compared to baseline methods in the benchmark datasets. The developed method is powerful in terms of effective normalization of Hi-C and capture Hi-C data, detection of long-range chromatin contacts, and readily extendibility to the other derivative Hi-C protocols. The covNorm R package is freely available at GitHub: https://github.com/kaistcbfg/covNormRpkg .
机译:HI-C和捕获HI-C大大提升了我们对高阶染色质结构原理的理解。根据高C协议的演变,需要一种可以应用于各种形式的HI-C协议的高级计算方法,并有效地除去先天偏差。要解决此问题,我们开发了一个名为“Covnorm”的隐式归一化方法,并将其实现为R包。所提出的方法可以执行HI-C及其变体的数据处理的完整过程。从基于负二氯模型的基于DNA片段覆盖的标准化开始,可以顺序地施加基因组距离依赖背景和呼叫显着相互作用的呼叫。 Covnorm的性能评估在HIC - Spector评分方面显示出增强或相似的再现性,室间A / B谱的相关性,以及与基准数据集中的基线方法相比,检测可再现的显着的远程染色质触点。开发方法在HI-C的有效标准化方面是强大的,并捕获HI-C数据,远程染色质触点检测,以及易于与其他衍生物的HI-C协议的可扩展性。 Covnorm R包在Github上可以免费提供:https://github.com/kaistcbfg/covnormrpkg。

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