The use of technical replication for detection of low-level somatic mutations in next-generation sequencing

Junho Kim; Dachan Kim; Jae Seok Lim; Ju Heon Maeng; Hyeonju Son; Hoon Chul Kang; Hojung Nam; Jeong Ho Lee; Sangwoo Kim

doi:10.1038/s41467-019-09026-y

The use of technical replication for detection of low-level somatic mutations in next-generation sequencing

Junho Kim, Dachan Kim, Jae Seok Lim, Ju Heon Maeng, Hyeonju Son, Hoon Chul Kang, Hojung Nam, Jeong Ho Lee, Sangwoo Kim

Department of Pediatrics

Research output: Contribution to journal › Article › peer-review

34 Citations (Scopus)

Abstract

Accurate genome-wide detection of somatic mutations with low variant allele frequency (VAF, <1%) has proven difficult, for which generalized, scalable methods are lacking. Herein, we describe a new computational method, called RePlow, that we developed to detect low-VAF somatic mutations based on simple, library-level replicates for next-generation sequencing on any platform. Through joint analysis of replicates, RePlow is able to remove prevailing background errors in next-generation sequencing analysis, facilitating remarkable improvement in the detection accuracy for low-VAF somatic mutations (up to ~99% reduction in false positives). The method is validated in independent cancer panel and brain tissue sequencing data. Our study suggests a new paradigm with which to exploit an overwhelming abundance of sequencing data for accurate variant detection.

Original language	English
Article number	1047
Journal	Nature communications
Volume	10
Issue number	1
DOIs	https://doi.org/10.1038/s41467-019-09026-y
Publication status	Published - 2019 Dec 1

Bibliographical note

Funding Information:
This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant nos. HI15C1601 and HI14C1324 to S.K., and H16C0415 to J.H.L.).

Publisher Copyright:
© 2019, The Author(s).

All Science Journal Classification (ASJC) codes

Chemistry(all)
Biochemistry, Genetics and Molecular Biology(all)
Physics and Astronomy(all)

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10.1038/s41467-019-09026-y

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abstract = "Accurate genome-wide detection of somatic mutations with low variant allele frequency (VAF, <1%) has proven difficult, for which generalized, scalable methods are lacking. Herein, we describe a new computational method, called RePlow, that we developed to detect low-VAF somatic mutations based on simple, library-level replicates for next-generation sequencing on any platform. Through joint analysis of replicates, RePlow is able to remove prevailing background errors in next-generation sequencing analysis, facilitating remarkable improvement in the detection accuracy for low-VAF somatic mutations (up to ~99% reduction in false positives). The method is validated in independent cancer panel and brain tissue sequencing data. Our study suggests a new paradigm with which to exploit an overwhelming abundance of sequencing data for accurate variant detection.",

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AU - Kang, Hoon Chul

AU - Nam, Hojung

AU - Lee, Jeong Ho

AU - Kim, Sangwoo

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The use of technical replication for detection of low-level somatic mutations in next-generation sequencing

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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