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 (SV) 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 inter-chromosomal 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 SV detection by locating breakpoints in repetitive regions.
List of abbreviations
- HiNT
- Hi-C for copy Number variation and Translocation detection;
- CNV
- copy number variation;
- SV
- structural variation;
- GAM
- generalized additive model;
- WGS
- whole genome sequencing;
- 1D
- 1-dimensional;
- ROC
- receiver operating characteristic;
- TADs
- topologically associated domains;
- TP
- true positive;
- TN
- true negative;
- FP
- false positive;
- FN
- false negative;
- RP
- rank product.
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Posted June 03, 2019.
HiNT: a computational method for detecting copy number variations and translocations from Hi-C data
