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

Authors
 Junho Kim  ;  Dachan Kim  ;  Jae Seok Lim  ;  Ju Heon Maeng  ;  Hyeonju Son  ;  Hoon-Chul Kang  ;  Hojung Nam  ;  Jeong Ho Lee  ;  Sangwoo Kim 
Citation
 NATURE COMMUNICATIONS, Vol.10(1) : 1047, 2019 
Journal Title
 NATURE COMMUNICATIONS 
Issue Date
2019
MeSH
Algorithms ; Brain/pathology ; Computational Biology/methods* ; DNA Mutational Analysis/methods* ; Gene Frequency/genetics ; Genome, Human/genetics ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Models, Statistical* ; Neoplasms/genetics ; Neoplasms/pathology ; Polymorphism, Single Nucleotide/genetics ; Whole Genome Sequencing/methods*
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.
Files in This Item:
T201901518.pdf Download
DOI
10.1038/s41467-019-09026-y
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Pediatrics (소아청소년과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
Yonsei Authors
Kang, Hoon Chul(강훈철) ORCID logo https://orcid.org/0000-0002-3659-8847
Kim, Sangwoo(김상우) ORCID logo https://orcid.org/0000-0001-5356-0827
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/169911
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