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Performance evaluation method for read mapping tool in clinical panel sequencing
In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This s...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Genetics Society of Korea
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846869/ https://www.ncbi.nlm.nih.gov/pubmed/29568413 http://dx.doi.org/10.1007/s13258-017-0621-9 |
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author | Lee, Hojun Lee, Ki-Wook Lee, Taeseob Park, Donghyun Chung, Jongsuk Lee, Chung Park, Woong-Yang Son, Dae-Soon |
author_facet | Lee, Hojun Lee, Ki-Wook Lee, Taeseob Park, Donghyun Chung, Jongsuk Lee, Chung Park, Woong-Yang Son, Dae-Soon |
author_sort | Lee, Hojun |
collection | PubMed |
description | In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recently. With the accumulated panel sequencing data, detected variant lists were cataloged and inserted into simulated reads produced from the reference genome (h19). The amount of unmapped reads and misaligned reads, mapping quality distribution, and runtime were measured as standards for comparison. As the most widely used tools, Bowtie2 and BWA–MEM each showed explicit performance with AUC of 0.9984 and 0.9970 respectively. Kart, maintaining superior runtime and less number of misaligned read, also similarly possessed high level of AUC (0.9723). Such selection and optimization method of tools appropriate for panel sequencing can be utilized for fields requiring error minimization, such as clinical application and liquid biopsy studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13258-017-0621-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5846869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Genetics Society of Korea |
record_format | MEDLINE/PubMed |
spelling | pubmed-58468692018-03-20 Performance evaluation method for read mapping tool in clinical panel sequencing Lee, Hojun Lee, Ki-Wook Lee, Taeseob Park, Donghyun Chung, Jongsuk Lee, Chung Park, Woong-Yang Son, Dae-Soon Genes Genomics Research Article In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recently. With the accumulated panel sequencing data, detected variant lists were cataloged and inserted into simulated reads produced from the reference genome (h19). The amount of unmapped reads and misaligned reads, mapping quality distribution, and runtime were measured as standards for comparison. As the most widely used tools, Bowtie2 and BWA–MEM each showed explicit performance with AUC of 0.9984 and 0.9970 respectively. Kart, maintaining superior runtime and less number of misaligned read, also similarly possessed high level of AUC (0.9723). Such selection and optimization method of tools appropriate for panel sequencing can be utilized for fields requiring error minimization, such as clinical application and liquid biopsy studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13258-017-0621-9) contains supplementary material, which is available to authorized users. The Genetics Society of Korea 2017-11-09 2018 /pmc/articles/PMC5846869/ /pubmed/29568413 http://dx.doi.org/10.1007/s13258-017-0621-9 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Article Lee, Hojun Lee, Ki-Wook Lee, Taeseob Park, Donghyun Chung, Jongsuk Lee, Chung Park, Woong-Yang Son, Dae-Soon Performance evaluation method for read mapping tool in clinical panel sequencing |
title | Performance evaluation method for read mapping tool in clinical panel sequencing |
title_full | Performance evaluation method for read mapping tool in clinical panel sequencing |
title_fullStr | Performance evaluation method for read mapping tool in clinical panel sequencing |
title_full_unstemmed | Performance evaluation method for read mapping tool in clinical panel sequencing |
title_short | Performance evaluation method for read mapping tool in clinical panel sequencing |
title_sort | performance evaluation method for read mapping tool in clinical panel sequencing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846869/ https://www.ncbi.nlm.nih.gov/pubmed/29568413 http://dx.doi.org/10.1007/s13258-017-0621-9 |
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