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SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data

With the development and application of next-generation sequencing (NGS) and target capture technology, the demand for an effective analysis method to accurately detect gene fusion from high-throughput data is growing. Hence, we developed a novel fusion gene analyzing method called single-end gene f...

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Autores principales: Xu, Hai, Wu, Xiaojin, Sun, Dawei, Li, Shijun, Zhang, Siwen, Teng, Miao, Bu, Jianlong, Zhang, Xizhe, Meng, Bo, Wang, Weitao, Tian, Geng, Lin, Huixin, Yuan, Dawei, Lang, Jidong, Xu, Shidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070977/
https://www.ncbi.nlm.nih.gov/pubmed/30004447
http://dx.doi.org/10.3390/genes9070331
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author Xu, Hai
Wu, Xiaojin
Sun, Dawei
Li, Shijun
Zhang, Siwen
Teng, Miao
Bu, Jianlong
Zhang, Xizhe
Meng, Bo
Wang, Weitao
Tian, Geng
Lin, Huixin
Yuan, Dawei
Lang, Jidong
Xu, Shidong
author_facet Xu, Hai
Wu, Xiaojin
Sun, Dawei
Li, Shijun
Zhang, Siwen
Teng, Miao
Bu, Jianlong
Zhang, Xizhe
Meng, Bo
Wang, Weitao
Tian, Geng
Lin, Huixin
Yuan, Dawei
Lang, Jidong
Xu, Shidong
author_sort Xu, Hai
collection PubMed
description With the development and application of next-generation sequencing (NGS) and target capture technology, the demand for an effective analysis method to accurately detect gene fusion from high-throughput data is growing. Hence, we developed a novel fusion gene analyzing method called single-end gene fusion (SEGF) by starting with single-end DNA-seq data. This approach takes raw sequencing data as input, and integrates the commonly used alignment approach basic local alignment search tool (BLAST) and short oligonucleotide analysis package (SOAP) with stringent passing filters to achieve successful fusion gene detection. To evaluate SEGF, we compared it with four other fusion gene discovery analysis methods by analyzing sequencing results of 23 standard DNA samples and DNA extracted from 286 lung cancer formalin fixed paraffin embedded (FFPE) samples. The results generated by SEGF indicated that it not only detected the fusion genes from standard samples and clinical samples, but also had the highest accuracy and sensitivity among the five compared methods. In addition, SEGF was capable of detecting complex gene fusion types from single-end NGS sequencing data compared with other methods. By using SEGF to acquire gene fusion information at DNA level, more useful information can be retrieved from the DNA panel or other DNA sequencing methods without generating RNA sequencing information to benefit clinical diagnosis or medication instruction. It was a timely and cost-effective measure with regard to research or diagnosis. Considering all the above, SEGF is a straightforward method without manipulating complicated arguments, providing a useful approach for the precise detection of gene fusion variation.
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spelling pubmed-60709772018-08-09 SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data Xu, Hai Wu, Xiaojin Sun, Dawei Li, Shijun Zhang, Siwen Teng, Miao Bu, Jianlong Zhang, Xizhe Meng, Bo Wang, Weitao Tian, Geng Lin, Huixin Yuan, Dawei Lang, Jidong Xu, Shidong Genes (Basel) Article With the development and application of next-generation sequencing (NGS) and target capture technology, the demand for an effective analysis method to accurately detect gene fusion from high-throughput data is growing. Hence, we developed a novel fusion gene analyzing method called single-end gene fusion (SEGF) by starting with single-end DNA-seq data. This approach takes raw sequencing data as input, and integrates the commonly used alignment approach basic local alignment search tool (BLAST) and short oligonucleotide analysis package (SOAP) with stringent passing filters to achieve successful fusion gene detection. To evaluate SEGF, we compared it with four other fusion gene discovery analysis methods by analyzing sequencing results of 23 standard DNA samples and DNA extracted from 286 lung cancer formalin fixed paraffin embedded (FFPE) samples. The results generated by SEGF indicated that it not only detected the fusion genes from standard samples and clinical samples, but also had the highest accuracy and sensitivity among the five compared methods. In addition, SEGF was capable of detecting complex gene fusion types from single-end NGS sequencing data compared with other methods. By using SEGF to acquire gene fusion information at DNA level, more useful information can be retrieved from the DNA panel or other DNA sequencing methods without generating RNA sequencing information to benefit clinical diagnosis or medication instruction. It was a timely and cost-effective measure with regard to research or diagnosis. Considering all the above, SEGF is a straightforward method without manipulating complicated arguments, providing a useful approach for the precise detection of gene fusion variation. MDPI 2018-07-02 /pmc/articles/PMC6070977/ /pubmed/30004447 http://dx.doi.org/10.3390/genes9070331 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Hai
Wu, Xiaojin
Sun, Dawei
Li, Shijun
Zhang, Siwen
Teng, Miao
Bu, Jianlong
Zhang, Xizhe
Meng, Bo
Wang, Weitao
Tian, Geng
Lin, Huixin
Yuan, Dawei
Lang, Jidong
Xu, Shidong
SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data
title SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data
title_full SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data
title_fullStr SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data
title_full_unstemmed SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data
title_short SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data
title_sort segf: a novel method for gene fusion detection from single-end next-generation sequencing data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070977/
https://www.ncbi.nlm.nih.gov/pubmed/30004447
http://dx.doi.org/10.3390/genes9070331
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