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KMID : 1094720190240050793
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Biotechnology and Bioprocess Engineering
2019 Volume.24 No. 5 p.793 ~ p.798
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Benchmark Database for Process Optimization and Quality Control of Clinical Cancer Panel Sequencing
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Seong Dong-Hyeong
Chung Jong-Suk
Lee Ki-Wook
Kim Sook-Young
Kim Byung-Suk
Song Jung-Keun
Jung Sung-Won
Lee Tae-Seob
Park Dong-Hyun
Yi Byoung-Kee
Park Woong-Yang
Son Dae-Soon
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Abstract
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With advances in Next Generation Sequencing (NGS) technology, individual institutes and research consortia have publicly released large-scale accumulated genomic data obtained in various projects. NGS technology has also been rapidly adopted in clinical practice, and many governments and research organizations have established a regulatory framework and guidelines to ensure the accuracy and reliability of NGS-based testing. These guidelines are essential for the safe use of NGS-based testing, but do not provide enough details that can be specifically applied to the various applications of NGS. In the clinical setting of NGS technology, clinical laboratories should optimize the NGS workflow for their specific uses and performance should be thoroughly evaluated through numerous experiments. However, process optimization and performance evaluation are a great burden to the laboratory in terms of cost and time because of the technical characteristics of NGS technology. The Samsung Medical Center (SMC) has developed and utilized cancer panel sequencing, namely CancerSCAN, which is approved for clinical use by the Ministry of Food and Drug Safety (MFDS) in Korea. SMC has performed various experiments to optimize and evaluate the process of CancerSCAN. In this study, we developed a benchmark database for integrating and sharing these data for process optimization of cancer panel sequencing. This benchmark database contains information on data production and provides functionalities for searching, browsing, and downloading experimental data and raw data files. This benchmark database will be beneficial to researchers, laboratory staff, or potential stakeholders. Database URL: http://129.150.178.10:8080/qms/nqbp/nqbp_home.do
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KEYWORD
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benchmark database, next generation sequencing, process optimization, quality control
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