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


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.

SUBMITTER: Wang S 

PROVIDER: S-EPMC7087379 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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

Wang Su S   Lee Soohyun S   Chu Chong C   Jain Dhawal D   Kerpedjiev Peter P   Nelson Geoffrey M GM   Walsh Jennifer M JM   Alver Burak H BH   Park Peter J PJ  

Genome biology 20200323 1


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-pa  ...[more]

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2010-12-31 | GSE21387 | GEO