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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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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 |
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author | Wang, Su Lee, Soohyun Chu, Chong Jain, Dhawal Kerpedjiev, Peter Nelson, Geoffrey M. Walsh, Jennifer M. Alver, Burak H. Park, Peter J. |
author_facet | Wang, Su Lee, Soohyun Chu, Chong Jain, Dhawal Kerpedjiev, Peter Nelson, Geoffrey M. Walsh, Jennifer M. Alver, Burak H. Park, Peter J. |
author_sort | Wang, Su |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7087379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70873792020-03-24 HiNT: a computational method for detecting copy number variations and translocations from Hi-C data Wang, Su Lee, Soohyun Chu, Chong Jain, Dhawal Kerpedjiev, Peter Nelson, Geoffrey M. Walsh, Jennifer M. Alver, Burak H. Park, Peter J. Genome Biol Method 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. BioMed Central 2020-03-23 /pmc/articles/PMC7087379/ /pubmed/32293513 http://dx.doi.org/10.1186/s13059-020-01986-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Method Wang, Su Lee, Soohyun Chu, Chong Jain, Dhawal Kerpedjiev, Peter Nelson, Geoffrey M. Walsh, Jennifer M. Alver, Burak H. Park, Peter J. HiNT: a computational method for detecting copy number variations and translocations from Hi-C data |
title | HiNT: a computational method for detecting copy number variations and translocations from Hi-C data |
title_full | HiNT: a computational method for detecting copy number variations and translocations from Hi-C data |
title_fullStr | HiNT: a computational method for detecting copy number variations and translocations from Hi-C data |
title_full_unstemmed | HiNT: a computational method for detecting copy number variations and translocations from Hi-C data |
title_short | HiNT: a computational method for detecting copy number variations and translocations from Hi-C data |
title_sort | hint: a computational method for detecting copy number variations and translocations from hi-c data |
topic | Method |
url | 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 |
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