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Comparison of somatic mutation calling methods in amplicon and whole exome sequence data

BACKGROUND: High-throughput sequencing is rapidly becoming common practice in clinical diagnosis and cancer research. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal DNA sequencing. Although numerous studies have compared the performa...

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Autores principales: Xu, Huilei, DiCarlo, John, Satya, Ravi Vijaya, Peng, Quan, Wang, Yexun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986649/
https://www.ncbi.nlm.nih.gov/pubmed/24678773
http://dx.doi.org/10.1186/1471-2164-15-244
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author Xu, Huilei
DiCarlo, John
Satya, Ravi Vijaya
Peng, Quan
Wang, Yexun
author_facet Xu, Huilei
DiCarlo, John
Satya, Ravi Vijaya
Peng, Quan
Wang, Yexun
author_sort Xu, Huilei
collection PubMed
description BACKGROUND: High-throughput sequencing is rapidly becoming common practice in clinical diagnosis and cancer research. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal DNA sequencing. Although numerous studies have compared the performance of various algorithms on exome data, there has not yet been a systematic evaluation using PCR-enriched amplicon data with a range of variant allele fractions. The recently developed gold standard variant set for the reference individual NA12878 by the NIST-led “Genome in a Bottle” Consortium (NIST-GIAB) provides a good resource to evaluate admixtures with various SNV fractions. RESULTS: Using the NIST-GIAB gold standard, we compared the performance of five popular somatic SNV calling algorithms (GATK UnifiedGenotyper followed by simple subtraction, MuTect, Strelka, SomaticSniper and VarScan2) for matched tumor-normal amplicon and exome sequencing data. CONCLUSIONS: We demonstrated that the five commonly used somatic SNV calling methods are applicable to both targeted amplicon and exome sequencing data. However, the sensitivities of these methods vary based on the allelic fraction of the mutation in the tumor sample. Our analysis can assist researchers in choosing a somatic SNV calling method suitable for their specific needs.
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spelling pubmed-39866492014-04-30 Comparison of somatic mutation calling methods in amplicon and whole exome sequence data Xu, Huilei DiCarlo, John Satya, Ravi Vijaya Peng, Quan Wang, Yexun BMC Genomics Research Article BACKGROUND: High-throughput sequencing is rapidly becoming common practice in clinical diagnosis and cancer research. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal DNA sequencing. Although numerous studies have compared the performance of various algorithms on exome data, there has not yet been a systematic evaluation using PCR-enriched amplicon data with a range of variant allele fractions. The recently developed gold standard variant set for the reference individual NA12878 by the NIST-led “Genome in a Bottle” Consortium (NIST-GIAB) provides a good resource to evaluate admixtures with various SNV fractions. RESULTS: Using the NIST-GIAB gold standard, we compared the performance of five popular somatic SNV calling algorithms (GATK UnifiedGenotyper followed by simple subtraction, MuTect, Strelka, SomaticSniper and VarScan2) for matched tumor-normal amplicon and exome sequencing data. CONCLUSIONS: We demonstrated that the five commonly used somatic SNV calling methods are applicable to both targeted amplicon and exome sequencing data. However, the sensitivities of these methods vary based on the allelic fraction of the mutation in the tumor sample. Our analysis can assist researchers in choosing a somatic SNV calling method suitable for their specific needs. BioMed Central 2014-03-28 /pmc/articles/PMC3986649/ /pubmed/24678773 http://dx.doi.org/10.1186/1471-2164-15-244 Text en Copyright © 2014 Xu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Xu, Huilei
DiCarlo, John
Satya, Ravi Vijaya
Peng, Quan
Wang, Yexun
Comparison of somatic mutation calling methods in amplicon and whole exome sequence data
title Comparison of somatic mutation calling methods in amplicon and whole exome sequence data
title_full Comparison of somatic mutation calling methods in amplicon and whole exome sequence data
title_fullStr Comparison of somatic mutation calling methods in amplicon and whole exome sequence data
title_full_unstemmed Comparison of somatic mutation calling methods in amplicon and whole exome sequence data
title_short Comparison of somatic mutation calling methods in amplicon and whole exome sequence data
title_sort comparison of somatic mutation calling methods in amplicon and whole exome sequence data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986649/
https://www.ncbi.nlm.nih.gov/pubmed/24678773
http://dx.doi.org/10.1186/1471-2164-15-244
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