RT Journal Article SR Electronic T1 HBP: an integrative and flexible pipeline for the interaction analysis of Hi-C dataset JF bioRxiv FD Cold Spring Harbor Laboratory SP 083576 DO 10.1101/083576 A1 He, Chao A1 Li, Ping A1 Shi, Minglei A1 Zhang, Yan A1 Ye, Bingyu A1 Xie, Dejian A1 Shen, Wenlong A1 Zhao, Zhihu YR 2016 UL http://biorxiv.org/content/early/2016/10/26/083576.abstract AB 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.