ArticleBMC genomics2024
DeCGR: an interactive toolkit for deciphering complex genomic rearrangements from Hi-C data.
Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundComplex 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.
resultsWe 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.
conclusionsDeCGR 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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