False-negative errors in next-generation sequencing contribute substantially to inconsistency of mutation databases

Young Ho Kim, Yura Song, Jong Kwang Kim, Tae Min Kim, Hye Won Sim, Hyung Lae Kim, Hyonchol Jang, Young Woo Kim, Kyeong Man Hong

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Background More than 11,000 laboratories and companies developed their own next-generation sequencing (NGS) for screening and diagnosis of various diseases including cancer. Although inconsistencies of mutation calls as high as 43% in databases such as GDSC (Genomics of Drug Sensitivity in Cancer) and CCLE (Cancer Cell Line Encyclopedia) have been reported, not many studies on the reasons for the inconsistencies have been published. Methods: Targeted-NGS analysis of 151 genes in 35 cell lines common to GDSC and CCLE was performed, and the results were compared with those from GDSC and CCLE wherein whole-exome- or highly-multiplex NGS were employed. Results In the comparison, GDSC and CCLE had a high rate (40-45%) of false-negative (FN) errors which would lead to high rate of inconsistent mutation calls, suggesting that highly-multiplex NGS may have high rate of FN errors. We also posited the possibility that targeted NGS, especially for the detection of low-level cancer cells in cancer tissues might suffer significant FN errors. Conclusion FN errors may be the most important errors in NGS testing for cancer; their evaluation in laboratory- developed NGS tests is needed.

Original languageEnglish
Article numbere0222535
JournalPLoS ONE
Issue number9
StatePublished - 1 Sep 2019

Bibliographical note

Publisher Copyright:
© 2019 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Dive into the research topics of 'False-negative errors in next-generation sequencing contribute substantially to inconsistency of mutation databases'. Together they form a unique fingerprint.

Cite this