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{"title":"R Tutorial: Detection of Differentially Interacting Chromatin Regions From Multiple Hi-C Datasets","authors":"John C. Stansfield, Duc Tran, Tin Nguyen, Mikhail G. Dozmorov","doi":"10.1002/cpbi.76","DOIUrl":null,"url":null,"abstract":"<p>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 <span>multiHiCcompare</span>, <span>diffHic</span>, and <span>FIND</span> 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.</p>","PeriodicalId":10958,"journal":{"name":"Current protocols in bioinformatics","volume":"66 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpbi.76","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current protocols in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpbi.76","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
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Abstract
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.
R教程:从多个Hi-C数据集检测差异相互作用的染色质区域
染色质的三维(3D)相互作用调节细胞类型特异性基因表达、重组、x染色体失活和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all-vs在全球范围内捕获染色质的结构。-所有的相互作用,可以为基因组调控提供新的见解。这里介绍的工作流程描述了如何分析和解释一个比较的Hi-C实验。我们描述了从公共存储库获取Hi-C数据的过程,并为打算分析自己的原始数据的用户提供预处理管道的建议。然后描述了数据归一化和比较分析过程。我们提出了三个协议,分别描述了使用multiHiCcompare、diffic和FIND R包来执行Hi-C实验的比较分析。最后,讨论了结果的可视化和差异相互作用区域的下游解释。本教程的大部分内容使用R编程环境,所描述的过程可以在大多数操作系统和一台计算机上执行。©2019 by John Wiley &儿子,Inc。
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