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HBP: an integrative and flexible pipeline for the interaction analysis of Hi-C dataset

Chao He, Ping Li, Minglei Shi, Yan Zhang, Bingyu Ye, Dejian Xie, Wenlong Shen, Zhihu Zhao
doi: https://doi.org/10.1101/083576
Chao He
1Beijing Institute of Biotechnology, Beijing 100071, China.
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Ping Li
1Beijing Institute of Biotechnology, Beijing 100071, China.
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Minglei Shi
1Beijing Institute of Biotechnology, Beijing 100071, China.
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Yan Zhang
1Beijing Institute of Biotechnology, Beijing 100071, China.
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Bingyu Ye
1Beijing Institute of Biotechnology, Beijing 100071, China.
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Dejian Xie
1Beijing Institute of Biotechnology, Beijing 100071, China.
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Wenlong Shen
1Beijing Institute of Biotechnology, Beijing 100071, China.
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  • For correspondence: shenwl1988@gmail.com zhaozh@bmi.ac.cn
Zhihu Zhao
1Beijing Institute of Biotechnology, Beijing 100071, China.
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  • For correspondence: shenwl1988@gmail.com zhaozh@bmi.ac.cn
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Abstract

Background The spatial organization of interphase chromatin in the nucleus play an important role in gene expression regulation and function. With the rapid development of revolutionized chromosome conformation capture technology and its genome-wide derivatives such as Hi-C, investigation of the genome folding becomes more efficient and convenient. How to robustly deal with these massive datasets and infer accurate 3D model and within-nucleus compartmentalization of chromosomes becomes a new challenge.

Result The implemented pipeline HBP (Hi-C BED file analysis Pipeline) integrates existing pipelines focusing on individual steps of Hi-C data processing into an all-in-one package with adjustable parameters to infer the consensus 3D structure of genome from raw Hi-C sequencing data. What’s more, HBP could assign statistical confidence estimation for chromatin interactions, and clustering interaction loci according to enrichment tracks or topological structure automatically.

Conclusion The freely available HBP is an optimized and flexible pipeline for analyzing the folding of whole chromosome and interactions between some specific sites from the Hi-C raw sequencing reads to the partially processed datasets. The other complex genetic and epigenetic datasets from public sources such as GWAS, ENCODE consortiums etc. will also easily be integrated into HBP, hence the final output results of HBP could provide a comprehensive in-depth understanding for the specific chromatin interactions, potential molecular mechanisms and biological significance. We believe that HBP is a reliable tool for the rapidly analysis of Hi-C data and will be very useful for a wide range of researchers, particularly those who lack of background in computational biology. HBP is freely accessible at https://github.com/hechao0407/HBP/blob/master/HBP_1.0.tar.gz.

Footnotes

  • Email address: Chao He: hechao2010{at}tsinghua.org.cn, Ping Li: lipingtry{at}163.com, Minglei Shi: shiml79{at}126.com, Yan Zhang: zany1983{at}163.com, Bingyu Ye: bby0804{at}gmail.com, Dejian Xie: ncuskxiedejian{at}163.com, Wenlong Shen: shenwl1988{at}gmail.com, Zhihu Zhao: zhaozh{at}bmi.ac.cn

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted October 26, 2016.
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HBP: an integrative and flexible pipeline for the interaction analysis of Hi-C dataset
Chao He, Ping Li, Minglei Shi, Yan Zhang, Bingyu Ye, Dejian Xie, Wenlong Shen, Zhihu Zhao
bioRxiv 083576; doi: https://doi.org/10.1101/083576
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HBP: an integrative and flexible pipeline for the interaction analysis of Hi-C dataset
Chao He, Ping Li, Minglei Shi, Yan Zhang, Bingyu Ye, Dejian Xie, Wenlong Shen, Zhihu Zhao
bioRxiv 083576; doi: https://doi.org/10.1101/083576

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