A comprehensive review of bioinformatics tools for chromatin loop calling

Author:

Liu Li1ORCID,Han Kaiyuan2,Sun Huimin3,Han Lu3,Gao Dong2,Xi Qilemuge4,Zhang Lirong3,Lin Hao2ORCID

Affiliation:

1. University of Electronic Science and Technology of China Yangtze Delta Region Institute (Quzhou), , Quzhou 324003 , China

2. University of Electronic Science and Technology of China Center for Informational Biology, School of Life Science and Technology, , Chengdu 610054 , China

3. Inner Mongolia University School of Physical Science and Technology, , Hohhot 010021 , China

4. Inner Mongolia University State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, , Hohhot 010070 , China

Abstract

AbstractPrecisely 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.

Funder

Municipal Government of Quzhou

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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