DeCGR: an interactive toolkit for deciphering complex genomic rearrangements from Hi-C data.

IF 3.7 2区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY BMC Genomics Pub Date : 2024-11-29 DOI:10.1186/s12864-024-11085-5
Junping Li, Minghui Sun, Yusen Ye, Lin Gao
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引用次数: 0

Abstract

Background: Complex genomic rearrangements (CGRs) drive the restructuring of chromatin architecture, resulting in significant interactions among rearranged fragments, visible as anomalous interaction blocks in chromatin contact maps generated by chromosome conformation capture technologies such as Hi-C. These blocks not only offer the orientation and genome coordinates of rearranged fragments but also filter out false positive CGRs, thereby facilitating CGR assembly. Despite this, there is a lack of interactive graphical software tailored for this purpose.

Results: We present DeCGR, a user-friendly Python toolbox specifically designed for deciphering CGRs in Hi-C data. DeCGR consists of four independent execution components. The Breakpoint Filtering module identifies and filters simple rearrangements, providing the coordinates of rearrangement breakpoints. The Fragment Assembly module automatically assembles CGRs and visualizes the assembly process, facilitating the direct association between anomalous interaction blocks and CGR events. The Validation CGRs module verifies the completeness and accuracy of CGRs by generating the Hi-C map with CGRs through a simulation process and examines the difference from the original Hi-C maps. This module displays both the original and the simulated Hi-C map with highlighted rearranged fragment boundaries for rapid review to assess the CGRs. Finally, the Reconstruct Hi-C Map module provides the reconstructed Hi-C map based on the determined CGRs, allowing users to directly observe the impact of rearrangements on chromatin structure.

Conclusions: DeCGR is designed specifically for biologists who aim to explore CGRs from Hi-C data. It provides a validation module to ensure the completeness and correctness of CGRs. Additionally, it allows users to generate CGR assembly results and reconstruct the Hi-C map with just one click. DeCGR provides intuitive visualization results for each module, allowing users to easily associate CGRs with Hi-C maps. DeCGR is operable through a user-friendly graphical interface. Source codes are freely available at https://github.com/GaoLabXDU/DeCGR .

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DeCGR:一个用于从Hi-C数据中破译复杂基因组重排的交互式工具包。
背景:复杂的基因组重排(cgr)驱动染色质结构的重组,导致重排片段之间的显著相互作用,在染色体构象捕获技术(如Hi-C)生成的染色质接触图中可见异常相互作用块。这些区块不仅提供了重排片段的方位和基因组坐标,还过滤掉了假阳性的CGR,从而促进了CGR的组装。尽管如此,目前还缺乏专门用于此目的的交互式图形软件。结果:我们提出DeCGR,一个用户友好的Python工具箱,专门设计用于破译Hi-C数据中的cgr。DeCGR由四个独立的执行组件组成。断点过滤模块识别并过滤简单的重排,提供重排断点的坐标。Fragment Assembly模块自动组装CGR并可视化组装过程,促进异常交互块与CGR事件之间的直接关联。Validation CGRs模块通过仿真过程,利用CGRs生成Hi-C地图,验证CGRs的完整性和准确性,并检验与原始Hi-C地图的差异。该模块显示原始和模拟的Hi-C地图,突出显示重排碎片边界,以便快速审查以评估cgr。最后,rebuild Hi-C Map模块根据确定的cgr提供重构的Hi-C图谱,使用户可以直接观察重排对染色质结构的影响。结论:DeCGR是专门为旨在从Hi-C数据中探索cgr的生物学家设计的。它提供了一个验证模块,以确保cgr的完整性和正确性。此外,它允许用户生成CGR组装结果和重建Hi-C地图只需点击一下。DeCGR为每个模块提供直观的可视化结果,允许用户轻松地将cgr与Hi-C地图相关联。DeCGR可通过用户友好的图形界面进行操作。源代码可在https://github.com/GaoLabXDU/DeCGR免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Genomics
BMC Genomics 生物-生物工程与应用微生物
CiteScore
7.40
自引率
4.50%
发文量
769
审稿时长
6.4 months
期刊介绍: BMC Genomics is an open access, peer-reviewed journal that considers articles on all aspects of genome-scale analysis, functional genomics, and proteomics. BMC Genomics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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