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In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data

Four popular somatic single nucleotide variant (SNV) calling methods (Varscan, SomaticSniper, Strelka and MuTect2) were carefully evaluated on the real whole exome sequencing (WES, depth of ~50X) and ultra-deep targeted sequencing (UDT-Seq, depth of ~370X) data. The four tools returned poor consensu...

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Autores principales: Cai, Lei, Yuan, Wei, Zhang, Zhou, He, Lin, Chou, Kuo-Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5118795/
https://www.ncbi.nlm.nih.gov/pubmed/27874022
http://dx.doi.org/10.1038/srep36540
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author Cai, Lei
Yuan, Wei
Zhang, Zhou
He, Lin
Chou, Kuo-Chen
author_facet Cai, Lei
Yuan, Wei
Zhang, Zhou
He, Lin
Chou, Kuo-Chen
author_sort Cai, Lei
collection PubMed
description Four popular somatic single nucleotide variant (SNV) calling methods (Varscan, SomaticSniper, Strelka and MuTect2) were carefully evaluated on the real whole exome sequencing (WES, depth of ~50X) and ultra-deep targeted sequencing (UDT-Seq, depth of ~370X) data. The four tools returned poor consensus on candidates (only 20% of calls were with multiple hits by the callers). For both WES and UDT-Seq, MuTect2 and Strelka obtained the largest proportion of COSMIC entries as well as the lowest rate of dbSNP presence and high-alternative-alleles-in-control calls, demonstrating their superior sensitivity and accuracy. Combining different callers does increase reliability of candidates, but narrows the list down to very limited range of tumor read depth and variant allele frequency. Calling SNV on UDT-Seq data, which were of much higher read-depth, discovered additional true-positive variations, despite an even more tremendous growth in false positive predictions. Our findings not only provide valuable benchmark for state-of-the-art SNV calling methods, but also shed light on the access to more accurate SNV identification in the future.
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spelling pubmed-51187952016-11-28 In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data Cai, Lei Yuan, Wei Zhang, Zhou He, Lin Chou, Kuo-Chen Sci Rep Article Four popular somatic single nucleotide variant (SNV) calling methods (Varscan, SomaticSniper, Strelka and MuTect2) were carefully evaluated on the real whole exome sequencing (WES, depth of ~50X) and ultra-deep targeted sequencing (UDT-Seq, depth of ~370X) data. The four tools returned poor consensus on candidates (only 20% of calls were with multiple hits by the callers). For both WES and UDT-Seq, MuTect2 and Strelka obtained the largest proportion of COSMIC entries as well as the lowest rate of dbSNP presence and high-alternative-alleles-in-control calls, demonstrating their superior sensitivity and accuracy. Combining different callers does increase reliability of candidates, but narrows the list down to very limited range of tumor read depth and variant allele frequency. Calling SNV on UDT-Seq data, which were of much higher read-depth, discovered additional true-positive variations, despite an even more tremendous growth in false positive predictions. Our findings not only provide valuable benchmark for state-of-the-art SNV calling methods, but also shed light on the access to more accurate SNV identification in the future. Nature Publishing Group 2016-11-22 /pmc/articles/PMC5118795/ /pubmed/27874022 http://dx.doi.org/10.1038/srep36540 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Cai, Lei
Yuan, Wei
Zhang, Zhou
He, Lin
Chou, Kuo-Chen
In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data
title In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data
title_full In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data
title_fullStr In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data
title_full_unstemmed In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data
title_short In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data
title_sort in-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5118795/
https://www.ncbi.nlm.nih.gov/pubmed/27874022
http://dx.doi.org/10.1038/srep36540
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