Genome Biology (Mar 2020)

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

  • Su Wang,
  • Soohyun Lee,
  • Chong Chu,
  • Dhawal Jain,
  • Peter Kerpedjiev,
  • Geoffrey M. Nelson,
  • Jennifer M. Walsh,
  • Burak H. Alver,
  • Peter J. Park

DOI
https://doi.org/10.1186/s13059-020-01986-5
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 15

Abstract

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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.

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