Stansfield John C, Tran Duc, Nguyen Tin, Dozmorov Mikhail G
Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia.
Department of Computer Science & Engineering, University of Nevada, Reno, Nevada.
Curr Protoc Bioinformatics. 2019 Jun;66(1):e76. doi: 10.1002/cpbi.76. Epub 2019 May 24.
The three-dimensional (3D) interactions of chromatin regulate cell-type-specific gene expression, recombination, X-chromosome inactivation, and many other genomic processes. High-throughput chromatin conformation capture (Hi-C) technologies capture the structure of the chromatin on a global scale by measuring all-vs.-all interactions and can provide new insights into genomic regulation. The workflow presented here describes how to analyze and interpret a comparative Hi-C experiment. We describe the process of obtaining Hi-C data from public repositories and give suggestions for pre-processing pipelines for users who intend to analyze their own raw data. We then describe the data normalization and comparative analysis process. We present three protocols describing the use of the multiHiCcompare, diffHic, and FIND R packages, respectively, to perform a comparative analysis of Hi-C experiments. Finally, visualization of the results and downstream interpretation of the differentially interacting regions are discussed. The bulk of this tutorial uses the R programming environment, and the processes described can be performed with most operating systems and a single computer. © 2019 by John Wiley & Sons, Inc.
染色质的三维(3D)相互作用调控细胞类型特异性基因表达、重组、X染色体失活以及许多其他基因组过程。高通量染色质构象捕获(Hi-C)技术通过测量全基因组范围内的相互作用来捕获染色质结构,并能为基因组调控提供新的见解。本文介绍的工作流程描述了如何分析和解读比较性Hi-C实验。我们阐述了从公共数据库获取Hi-C数据的过程,并为打算分析自身原始数据的用户提供预处理流程建议。接着,我们描述了数据归一化和比较分析过程。我们分别介绍了三个方案,描述了如何使用multiHiCcompare、diffHic和FIND R软件包对Hi-C实验进行比较分析。最后,讨论了结果的可视化以及差异相互作用区域的下游解读。本教程主要使用R编程环境,所述过程在大多数操作系统和单台计算机上均可执行。© 2019约翰威立国际出版公司