MHiC, an integrated user-friendly tool for the identification and visualization of significant interactions in Hi-C data

Hamid Alinejad-Rokny,Saman Khakmardan,Ali Akbar Pouyan,Mohsen Rezvani,Mansoor Fateh

doi:10.1186/s12864-020-6636-7

Hamid Alinejad-Rokny, Saman Khakmardan + Show 3 more

Open Access

https://doi.org/10.1186/s12864-020-6636-7

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Journal: BMC Genomics	Publication Date: Mar 12, 2020
Citations: 9	License type: open-access

Affiliation: UNSW Sydney, University of Shahrood

Abstract

BackgroundHi-C is a molecular biology technique to understand the genome spatial structure. However, data obtained from Hi-C experiments is biased. Therefore, several methods have been developed to model Hi-C data and identify significant interactions. Each method receives its own Hi-C data structure and only work on specific operating systems.ResultsWe introduce MHiC (Multi-function Hi-C data analysis tool), a tool to identify and visualize statistically signifiant interactions from Hi-C data. The MHiC tool (i) works on different operating systems, (ii) accepts various Hi-C data structures from different Hi-C analysis tools such as HiCUP or HiC-Pro, (iii) identify significant Hi-C interactions with GOTHiC, HiCNorm and Fit-Hi-C methods and (iv) visualizes interactions in Arc or Heatmap diagram. MHiC is an open-source tool which is freely available for download on https://github.com/MHi-C.ConclusionsMHiC is an integrated tool for the analysis of high-throughput chromosome conformation capture (Hi-C) data.

Highlights

high-throughput chromosome conformation capture (Hi-C) is a molecular biology technique to understand the genome spatial structure
In order to address the above mentioned challenges in HiC tools, we have developed an integrated tool called “MHiC” (Multi-function Hi-C data analysis software), which uses GOTHiC, HiCNorm and Fit-Hi-C methods with a graphical user interface (GUI) to identify statistically significant interactions in Hi-C contact maps generated by different Hi-C analysis tool
To identify Hi-C significant interactions and visualize Hi-C contact maps, we have developed MHiC in two main modules

Summary

Introduction

Hi-C is a molecular biology technique to understand the genome spatial structure. data obtained from Hi-C experiments is biased. Chromosome conformation capture (3C) assays are the method of choice to study the role of DNA looping in transcriptional regulation. These assays directly identify genomic loci that are in close enough proximity to each other in living cells to be cross-linked. This new technology allows for the mapping of chromatin interactions on a whole genome level. The first study of 3C technology was developed by Dekker et al [1] This protocol captures interactions between a single pair of candidate regions.

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