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

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 computationa...

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Detalles Bibliográficos
Autores principales: Wang, Su, Lee, Soohyun, Chu, Chong, Jain, Dhawal, Kerpedjiev, Peter, Nelson, Geoffrey M., Walsh, Jennifer M., Alver, Burak H., Park, Peter J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087379/
https://www.ncbi.nlm.nih.gov/pubmed/32293513
http://dx.doi.org/10.1186/s13059-020-01986-5
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-020-01986-5) contains supplementary material, which is available to authorized users.