计算机科学
染色质
循环(图论)
完备性(序理论)
数据科学
计算生物学
数据挖掘
生物信息学
生物
基因
遗传学
数学
组合数学
数学分析
作者
Li Liu,Kaiyuan Han,Hongqi Sun,Lu Han,Dong Gao,Qilemuge Xi,Lirong Zhang,Hao Lin
摘要
Abstract Precisely calling chromatin loops has profound implications for further analysis of gene regulation and disease mechanisms. Technological advances in chromatin conformation capture (3C) assays make it possible to identify chromatin loops in the genome. However, a variety of experimental protocols have resulted in different levels of biases, which require distinct methods to call true loops from the background. Although many bioinformatics tools have been developed to address this problem, there is still a lack of special introduction to loop-calling algorithms. This review provides an overview of the loop-calling tools for various 3C-based techniques. We first discuss the background biases produced by different experimental techniques and the denoising algorithms. Then, the completeness and priority of each tool are categorized and summarized according to the data source of application. The summary of these works can help researchers select the most appropriate method to call loops and further perform downstream analysis. In addition, this survey is also useful for bioinformatics scientists aiming to develop new loop-calling algorithms.
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