Biotechnology and Bioprocess Engineering 2019; 24(5): 793-798  
Benchmark Database for Process Optimization and Quality Control of Clinical Cancer Panel Sequencing
Donghyeong Seong1, Jongsuk Chung2,3, Ki-Wook Lee2,4, Sook-Young Kim2, Byung-Suk Kim2, Jung-Keun Song2, Sungwon Jung1, Taeseob Lee2,4, Donghyun Park2,6, Byoung-Kee Yi2,4,5, Woong-Yang Park1,3,6, and Dae-Soon Son2,7
1Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul 06351, Korea
2Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea
3Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon 16419, Korea
4Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul 06351, Korea
5Smart Healthcare & Device Research Center, Samsung Medical Center, Seoul 06351, Korea
6Donghyun Park, Woong-Yang Park GENINUS Inc., Seoul 05836, Korea
7School of Big Data Science, Data Science Convergence Research Center, Hallym University
Correspondence to: Byoung-Kee Yi
Smart Healthcare & Device Research Center, Samsung Medical Center, Seoul 06351, Korea
Tel: +82-2-3410-1944
E-mail: byoungkeeyi@gmail.com
Received: May 24, 2019; Revised: July 5, 2019; Accepted: July 6, 2019; Published online: October 31, 2019.
© The Korean Society for Biotechnology and Bioengineering. All rights reserved.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
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
Keywords: benchmark database, next generation sequencing, process optimization, quality control


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