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SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads
As a common type of structural variation, an insertion refers to the addition of a DNA sequence into an individual genome and is usually associated with some inherited diseases. In recent years, many methods have been proposed for detecting insertions. However, the accurate calling of insertions is...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120196/ https://www.ncbi.nlm.nih.gov/pubmed/33995493 http://dx.doi.org/10.3389/fgene.2021.665812 |
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author | Yan, Chaokun He, Junyi Luo, Junwei Wang, Jianlin Zhang, Ge Luo, Huimin |
author_facet | Yan, Chaokun He, Junyi Luo, Junwei Wang, Jianlin Zhang, Ge Luo, Huimin |
author_sort | Yan, Chaokun |
collection | PubMed |
description | As a common type of structural variation, an insertion refers to the addition of a DNA sequence into an individual genome and is usually associated with some inherited diseases. In recent years, many methods have been proposed for detecting insertions. However, the accurate calling of insertions is also a challenging task. In this study, we propose a novel insertion detection approach based on soft-clipped reads, which is called SIns. First, based on the alignments between paired reads and the reference genome, SIns extracts breakpoints from soft-clipped reads and determines insertion locations. The insert size information about paired reads is then further clustered to determine the genotype, and SIns subsequently adopts Minia to assemble the insertion sequences. Experimental results show that SIns can achieve better performance than other methods in terms of the F-score value for simulated and true datasets. |
format | Online Article Text |
id | pubmed-8120196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81201962021-05-15 SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads Yan, Chaokun He, Junyi Luo, Junwei Wang, Jianlin Zhang, Ge Luo, Huimin Front Genet Genetics As a common type of structural variation, an insertion refers to the addition of a DNA sequence into an individual genome and is usually associated with some inherited diseases. In recent years, many methods have been proposed for detecting insertions. However, the accurate calling of insertions is also a challenging task. In this study, we propose a novel insertion detection approach based on soft-clipped reads, which is called SIns. First, based on the alignments between paired reads and the reference genome, SIns extracts breakpoints from soft-clipped reads and determines insertion locations. The insert size information about paired reads is then further clustered to determine the genotype, and SIns subsequently adopts Minia to assemble the insertion sequences. Experimental results show that SIns can achieve better performance than other methods in terms of the F-score value for simulated and true datasets. Frontiers Media S.A. 2021-04-30 /pmc/articles/PMC8120196/ /pubmed/33995493 http://dx.doi.org/10.3389/fgene.2021.665812 Text en Copyright © 2021 Yan, He, Luo, Wang, Zhang and Luo. https://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) and the copyright owner(s) 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 | Genetics Yan, Chaokun He, Junyi Luo, Junwei Wang, Jianlin Zhang, Ge Luo, Huimin SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads |
title | SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads |
title_full | SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads |
title_fullStr | SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads |
title_full_unstemmed | SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads |
title_short | SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads |
title_sort | sins: a novel insertion detection approach based on soft-clipped reads |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120196/ https://www.ncbi.nlm.nih.gov/pubmed/33995493 http://dx.doi.org/10.3389/fgene.2021.665812 |
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