Literature DB >> 34415534

Analysis of Hi-C Data for Discovery of Structural Variations in Cancer.

Fan Song1,2, Jie Xu1, Jesse Dixon3, Feng Yue4,5.   

Abstract

Structural variations (SVs) are large genomic rearrangements that can be challenging to identify with current short read sequencing technology due to various confounding factors such as existence of genomic repeats and complex SV structures. Hi-C breakfinder is the first computational tool that utilizes the technology of high-throughput chromatin conformation capture assay (Hi-C) to systematically identify SVs, without being interfered by regular confounding factors. SVs change the spatial distance of genomic regions and cause discontinuous signals in Hi-C, which are difficult to analyze by routine informatics practice. Here we provide step-by-step guidance for how to identify SVs using Hi-C data and how to reconstruct Hi-C maps in the presence of SVs.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  3D genome organization; Cancer genomics; Chromatin conformation; Hi-C; Structural variation

Mesh:

Substances:

Year:  2022        PMID: 34415534     DOI: 10.1007/978-1-0716-1390-0_7

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  26 in total

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3.  Transcriptional consequences of genomic structural aberrations in breast cancer.

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