Computational tools for Hi-C data analysis

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. 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. 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.