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Detection of Genomic Structural Variants from Next-Generation Sequencing Data
Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479793/ https://www.ncbi.nlm.nih.gov/pubmed/26161383 http://dx.doi.org/10.3389/fbioe.2015.00092 |
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author | Tattini, Lorenzo D’Aurizio, Romina Magi, Alberto |
author_facet | Tattini, Lorenzo D’Aurizio, Romina Magi, Alberto |
author_sort | Tattini, Lorenzo |
collection | PubMed |
description | Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools – and their underlying algorithms – designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication – with particular emphasis on human genetics and copy number variants – for researchers involved in the investigation of these genomic events. |
format | Online Article Text |
id | pubmed-4479793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-44797932015-07-09 Detection of Genomic Structural Variants from Next-Generation Sequencing Data Tattini, Lorenzo D’Aurizio, Romina Magi, Alberto Front Bioeng Biotechnol Bioengineering and Biotechnology Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools – and their underlying algorithms – designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication – with particular emphasis on human genetics and copy number variants – for researchers involved in the investigation of these genomic events. Frontiers Media S.A. 2015-06-25 /pmc/articles/PMC4479793/ /pubmed/26161383 http://dx.doi.org/10.3389/fbioe.2015.00092 Text en Copyright © 2015 Tattini, D’Aurizio and Magi. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Tattini, Lorenzo D’Aurizio, Romina Magi, Alberto Detection of Genomic Structural Variants from Next-Generation Sequencing Data |
title | Detection of Genomic Structural Variants from Next-Generation Sequencing Data |
title_full | Detection of Genomic Structural Variants from Next-Generation Sequencing Data |
title_fullStr | Detection of Genomic Structural Variants from Next-Generation Sequencing Data |
title_full_unstemmed | Detection of Genomic Structural Variants from Next-Generation Sequencing Data |
title_short | Detection of Genomic Structural Variants from Next-Generation Sequencing Data |
title_sort | detection of genomic structural variants from next-generation sequencing data |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479793/ https://www.ncbi.nlm.nih.gov/pubmed/26161383 http://dx.doi.org/10.3389/fbioe.2015.00092 |
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