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HiNT: a computational method for detecting copy number variations and translocations from Hi-C data

Authors :
Su Wang
Soohyun Lee
Chong Chu
Dhawal Jain
Peter Kerpedjiev
Geoffrey M. Nelson
Jennifer M. Walsh
Burak H. Alver
Peter J. Park
Source :
Genome Biology, Vol 21, Iss 1, Pp 1-15 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract The three-dimensional conformation of a genome can be profiled using Hi-C, a technique that combines chromatin conformation capture with high-throughput sequencing. However, structural variations often yield features that can be mistaken for chromosomal interactions. Here, we describe a computational method HiNT (Hi-C for copy Number variation and Translocation detection), which detects copy number variations and interchromosomal translocations within Hi-C data with breakpoints at single base-pair resolution. We demonstrate that HiNT outperforms existing methods on both simulated and real data. We also show that Hi-C can supplement whole-genome sequencing in structure variant detection by locating breakpoints in repetitive regions.

Details

Language :
English
ISSN :
1474760X
Volume :
21
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.548886af16841be8db011de393a0821
Document Type :
article
Full Text :
https://doi.org/10.1186/s13059-020-01986-5