Literature DB >> 31125519

R Tutorial: Detection of Differentially Interacting Chromatin Regions From Multiple Hi-C Datasets.

John C Stansfield1, Duc Tran2, Tin Nguyen2, Mikhail G Dozmorov1.   

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. © 2019 John Wiley & Sons, Inc.

Entities:  

Keywords:  Hi-C; HiCcompare; chromosome conformation capture; comparison; differential analysis; multiHiCcompare; normalization

Mesh:

Substances:

Year:  2019        PMID: 31125519      PMCID: PMC6588411          DOI: 10.1002/cpbi.76

Source DB:  PubMed          Journal:  Curr Protoc Bioinformatics        ISSN: 1934-3396


  30 in total

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8.  Three-dimensional disorganization of the cancer genome occurs coincident with long-range genetic and epigenetic alterations.

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9.  HiCcompare: an R-package for joint normalization and comparison of HI-C datasets.

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  2 in total

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2.  Methods for the Differential Analysis of Hi-C Data.

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Journal:  Methods Mol Biol       Date:  2022
  2 in total

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