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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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| Published in: | Genome Biology 2020-03, Vol.21 (1), p.73-15, Article 73 |
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| Main Authors: | , , , , , , , , |
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| cited_by | cdi_FETCH-LOGICAL-c611t-9b1422371fac5606e56e0809a2344ddd02811e28a877264b0b742465ea785f663 |
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| cites | cdi_FETCH-LOGICAL-c611t-9b1422371fac5606e56e0809a2344ddd02811e28a877264b0b742465ea785f663 |
| container_end_page | 15 |
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| container_start_page | 73 |
| container_title | Genome Biology |
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| creator | Wang, Su Lee, Soohyun Chu, Chong Jain, Dhawal Kerpedjiev, Peter Nelson, Geoffrey M Walsh, Jennifer M Alver, Burak H Park, Peter J |
| 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. |
| doi_str_mv | 10.1186/s13059-020-01986-5 |
| format | article |
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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.</description><identifier>ISSN: 1474-760X</identifier><identifier>ISSN: 1474-7596</identifier><identifier>EISSN: 1474-760X</identifier><identifier>DOI: 10.1186/s13059-020-01986-5</identifier><identifier>PMID: 32293513</identifier><language>eng</language><publisher>England: BioMed Central</publisher><subject>Breakpoints ; Cancer ; Cell cycle ; Chromatin ; Chromosomal interactions ; Chromosome Breakpoints ; Chromosome translocations ; Computer applications ; Conformation ; Copy number ; DNA Copy Number Variations ; Gene loci ; Genomes ; Genomics - methods ; High-Throughput Nucleotide Sequencing ; Method ; Next-generation sequencing ; Repetitive region ; Repetitive Sequences, Nucleic Acid ; Sequence Analysis, DNA ; Structural variation ; Translocation, Genetic ; Variation ; Whole Genome Sequencing</subject><ispartof>Genome Biology, 2020-03, Vol.21 (1), p.73-15, Article 73</ispartof><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c611t-9b1422371fac5606e56e0809a2344ddd02811e28a877264b0b742465ea785f663</citedby><cites>FETCH-LOGICAL-c611t-9b1422371fac5606e56e0809a2344ddd02811e28a877264b0b742465ea785f663</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087379/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2391413494?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32293513$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Su</creatorcontrib><creatorcontrib>Lee, Soohyun</creatorcontrib><creatorcontrib>Chu, Chong</creatorcontrib><creatorcontrib>Jain, Dhawal</creatorcontrib><creatorcontrib>Kerpedjiev, Peter</creatorcontrib><creatorcontrib>Nelson, Geoffrey M</creatorcontrib><creatorcontrib>Walsh, Jennifer M</creatorcontrib><creatorcontrib>Alver, Burak H</creatorcontrib><creatorcontrib>Park, Peter J</creatorcontrib><title>HiNT: a computational method for detecting copy number variations and translocations from Hi-C data</title><title>Genome Biology</title><addtitle>Genome Biol</addtitle><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.</description><subject>Breakpoints</subject><subject>Cancer</subject><subject>Cell cycle</subject><subject>Chromatin</subject><subject>Chromosomal interactions</subject><subject>Chromosome Breakpoints</subject><subject>Chromosome translocations</subject><subject>Computer applications</subject><subject>Conformation</subject><subject>Copy number</subject><subject>DNA Copy Number Variations</subject><subject>Gene loci</subject><subject>Genomes</subject><subject>Genomics - methods</subject><subject>High-Throughput Nucleotide Sequencing</subject><subject>Method</subject><subject>Next-generation sequencing</subject><subject>Repetitive region</subject><subject>Repetitive Sequences, Nucleic Acid</subject><subject>Sequence Analysis, DNA</subject><subject>Structural variation</subject><subject>Translocation, Genetic</subject><subject>Variation</subject><subject>Whole Genome Sequencing</subject><issn>1474-760X</issn><issn>1474-7596</issn><issn>1474-760X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdksFu1DAQhiMEoqXwAhyQJS5cAh7bsR0OSGgFbKUKLkXiZk1sZ-tVEi-2U6lvT9gsVcvJ1vibTzPyX1Wvgb4H0PJDBk6btqaM1hRaLevmSXUOQolaSfrr6YP7WfUi5z1dKMHk8-qMM9byBvh5Zbfh-_VHgsTG8TAXLCFOOJDRl5voSB8Tcb54W8K0W5DDHZnmsfOJ3GIKRzgTnBwpCac8RHsq9SmOZBvqDXFY8GX1rMch-1en86L6-fXL9WZbX_34drn5fFVbCVDqtgPBGFfQo20klb6RnmraIuNCOOco0wCeadRKMSk62inBhGw8Kt30UvKL6nL1uoh7c0hhxHRnIgZzLMS0M5hKsIM3rhFaa4k9SC2g89p1FMB53nKkmsHi-rS6DnM3emf9tKw4PJI-fpnCjdnFW6OoVly1i-DdSZDi79nnYsaQrR8GnHycs2G8pSCVaMWCvv0P3cc5Ld9wpEAAXym2UjbFnJPv74cBav7mwax5MEsezDEPplma3jxc477lXwD4H0mAr8U</recordid><startdate>20200323</startdate><enddate>20200323</enddate><creator>Wang, Su</creator><creator>Lee, Soohyun</creator><creator>Chu, Chong</creator><creator>Jain, Dhawal</creator><creator>Kerpedjiev, Peter</creator><creator>Nelson, Geoffrey M</creator><creator>Walsh, Jennifer M</creator><creator>Alver, Burak H</creator><creator>Park, Peter J</creator><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20200323</creationdate><title>HiNT: a computational method for detecting copy number variations and translocations from Hi-C data</title><author>Wang, Su ; Lee, Soohyun ; Chu, Chong ; Jain, Dhawal ; Kerpedjiev, Peter ; Nelson, Geoffrey M ; Walsh, Jennifer M ; Alver, Burak H ; Park, Peter J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c611t-9b1422371fac5606e56e0809a2344ddd02811e28a877264b0b742465ea785f663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Breakpoints</topic><topic>Cancer</topic><topic>Cell cycle</topic><topic>Chromatin</topic><topic>Chromosomal interactions</topic><topic>Chromosome Breakpoints</topic><topic>Chromosome translocations</topic><topic>Computer applications</topic><topic>Conformation</topic><topic>Copy number</topic><topic>DNA Copy Number Variations</topic><topic>Gene loci</topic><topic>Genomes</topic><topic>Genomics - methods</topic><topic>High-Throughput Nucleotide Sequencing</topic><topic>Method</topic><topic>Next-generation sequencing</topic><topic>Repetitive region</topic><topic>Repetitive Sequences, Nucleic Acid</topic><topic>Sequence Analysis, DNA</topic><topic>Structural variation</topic><topic>Translocation, Genetic</topic><topic>Variation</topic><topic>Whole Genome Sequencing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Su</creatorcontrib><creatorcontrib>Lee, Soohyun</creatorcontrib><creatorcontrib>Chu, Chong</creatorcontrib><creatorcontrib>Jain, Dhawal</creatorcontrib><creatorcontrib>Kerpedjiev, Peter</creatorcontrib><creatorcontrib>Nelson, Geoffrey M</creatorcontrib><creatorcontrib>Walsh, Jennifer M</creatorcontrib><creatorcontrib>Alver, Burak H</creatorcontrib><creatorcontrib>Park, Peter J</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection (Proquest)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>ProQuest Biological Science Journals</collection><collection>ProQuest Publicly Available Content database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Genome Biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Su</au><au>Lee, Soohyun</au><au>Chu, Chong</au><au>Jain, Dhawal</au><au>Kerpedjiev, Peter</au><au>Nelson, Geoffrey M</au><au>Walsh, Jennifer M</au><au>Alver, Burak H</au><au>Park, Peter J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>HiNT: a computational method for detecting copy number variations and translocations from Hi-C data</atitle><jtitle>Genome Biology</jtitle><addtitle>Genome Biol</addtitle><date>2020-03-23</date><risdate>2020</risdate><volume>21</volume><issue>1</issue><spage>73</spage><epage>15</epage><pages>73-15</pages><artnum>73</artnum><issn>1474-760X</issn><issn>1474-7596</issn><eissn>1474-760X</eissn><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. 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| ispartof | Genome Biology, 2020-03, Vol.21 (1), p.73-15, Article 73 |
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| language | eng |
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| source | PubMed (Medline); ProQuest Publicly Available Content database |
| subjects | Breakpoints Cancer Cell cycle Chromatin Chromosomal interactions Chromosome Breakpoints Chromosome translocations Computer applications Conformation Copy number DNA Copy Number Variations Gene loci Genomes Genomics - methods High-Throughput Nucleotide Sequencing Method Next-generation sequencing Repetitive region Repetitive Sequences, Nucleic Acid Sequence Analysis, DNA Structural variation Translocation, Genetic Variation Whole Genome Sequencing |
| title | HiNT: a computational method for detecting copy number variations and translocations from Hi-C data |
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