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J Mol Diagn. 2017 Sep;19(5):651-658. doi: 10.1016/j.jmoldx.2017.06.001. Epub 2017 Jul 22.

A Method to Evaluate the Quality of Clinical Gene-Panel Sequencing Data for Single-Nucleotide Variant Detection.

Author information

1
Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
2
Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea.
3
Office of R&D Strategy and Planning, Samsung Medical Center, Seoul, Republic of Korea.
4
Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea; Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea.
5
Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea; Department of Bioinformatics and Life Science, Soongsil University, Seoul, Republic of Korea.
6
Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
7
Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea; Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea. Electronic address: woongyang.park@samsung.com.
8
Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea. Electronic address: ds3.son@samsung.com.

Abstract

Customized gene-panel tests, based on next-generation sequencing, have demonstrated their usefulness in a plethora of clinical settings. As with other clinical diagnostic techniques, gene-panel sequencing for clinical purposes requires precise quality control (QC) measures to ensure its reliability. Only detected variants are currently recorded in clinical reports; however, identifying whether a nondetected variant is a true or false negative is regarded essential in a clinical setting and, thus, a comprehensive QC measure is in demand. Conventional QC metrics, such as mean coverage and uniformity, are considered inadequate for such an evaluation. As such, a more specific measure focused on clinically important variants is herein proposed. In this study, we suggest a new scoring method for assessing the quality of clinical gene-panel sequencing data, specifically for the detection of a set of single-nucleotide variants. The performance of the method was analyzed using 2295 clinical samples (1012 formalin-fixed, paraffin-embedded and 1283 fresh-frozen tissues), and was shown to provide additional information that conventional methods do not show, such as mean depth and uniformity. Customized sequencing protocols, which include QC criteria, have been optimized by each genomic laboratory. The pass rate scoring method proposed in this study provides an appropriate QC response variable for the customized panel, which strengthens the reliability of calls on clinically relevant variants implicated in clinical reports.

PMID:
28743024
DOI:
10.1016/j.jmoldx.2017.06.001
[Indexed for MEDLINE]
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