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Computational tools for Hi-C data analysis

摘要Background:In eukaryotic genome,chromatin is not randomly distributed in cell nuclei,but instead is organized into higher-order structures.Emerging evidence indicates that these higher-order chromatin structures play important roles in regulating genome functions such as transcription and DNA replication.With the advancement in 3C (chromosome conformation capture) based technologies,Hi-C has been widely used to investigate genome-wide longrange chromatin interactions during cellular differentiation and oncogenesis.Since the first publication of Hi-C assay in 2009,lots of bioinformatic tools have been implemented for processing Hi-C data from mapping raw reads to normalizing contact matrix and high interpretation,either providing a whole workflow pipeline or focusing on a particular process.Results:This article reviews the general Hi-C data processing workflow and the currently popular Hi-C data processing tools.We highlight on how these tools are used for a full interpretation of Hi-C results.Conclusions:Hi-C assay is a powerful tool to investigate the higher-order chromatin structure.Continued development of novel methods for Hi-C data analysis will be necessary for better understanding the regulatory function of genome organization.

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作者单位 CAS Key Laboratory of Computational Biology,Collaborative Innovation Center for Genetics and Developmental Biology,CAS-MPG Partner Institute for Computational Biology,Shanghai Institutes for Biological Sciences,Chinese Academy of Sciences,Shanghai 200031,China;University of Chinese Academy of Sciences,Beijing 100049,China [1] CAS Key Laboratory of Computational Biology,Collaborative Innovation Center for Genetics and Developmental Biology,CAS-MPG Partner Institute for Computational Biology,Shanghai Institutes for Biological Sciences,Chinese Academy of Sciences,Shanghai 200031,China [2]
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DOI 10.1007/s40484-017-0113-6
发布时间 2017-12-18(万方平台首次上网日期,不代表论文的发表时间)
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