Cargando…

Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers

The development and innovation of next generation sequencing (NGS) and the subsequent analysis tools have gain popularity in scientific researches and clinical diagnostic applications. Hence, a systematic comparison of the sequencing platforms and variant calling pipelines could provide significant...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Jiayun, Li, Xingsong, Zhong, Hongbin, Meng, Yuhuan, Du, Hongli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6597787/
https://www.ncbi.nlm.nih.gov/pubmed/31249349
http://dx.doi.org/10.1038/s41598-019-45835-3
_version_ 1783430651002748928
author Chen, Jiayun
Li, Xingsong
Zhong, Hongbin
Meng, Yuhuan
Du, Hongli
author_facet Chen, Jiayun
Li, Xingsong
Zhong, Hongbin
Meng, Yuhuan
Du, Hongli
author_sort Chen, Jiayun
collection PubMed
description The development and innovation of next generation sequencing (NGS) and the subsequent analysis tools have gain popularity in scientific researches and clinical diagnostic applications. Hence, a systematic comparison of the sequencing platforms and variant calling pipelines could provide significant guidance to NGS-based scientific and clinical genomics. In this study, we compared the performance, concordance and operating efficiency of 27 combinations of sequencing platforms and variant calling pipelines, testing three variant calling pipelines—Genome Analysis Tool Kit HaplotypeCaller, Strelka2 and Samtools-Varscan2 for nine data sets for the NA12878 genome sequenced by different platforms including BGISEQ500, MGISEQ2000, HiSeq4000, NovaSeq and HiSeq Xten. For the variants calling performance of 12 combinations in WES datasets, all combinations displayed good performance in calling SNPs, with their F-scores entirely higher than 0.96, and their performance in calling INDELs varies from 0.75 to 0.91. And all 15 combinations in WGS datasets also manifested good performance, with F-scores in calling SNPs were entirely higher than 0.975 and their performance in calling INDELs varies from 0.71 to 0.93. All of these combinations manifested high concordance in variant identification, while the divergence of variants identification in WGS datasets were larger than that in WES datasets. We also down-sampled the original WES and WGS datasets at a series of gradient coverage across multiple platforms, then the variants calling period consumed by the three pipelines at each coverage were counted, respectively. For the GIAB datasets on both BGI and Illumina platforms, Strelka2 manifested its ultra-performance in detecting accuracy and processing efficiency compared with other two pipelines on each sequencing platform, which was recommended in the further promotion and application of next generation sequencing technology. The results of our researches will provide useful and comprehensive guidelines for personal or organizational researchers in reliable and consistent variants identification.
format Online
Article
Text
id pubmed-6597787
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-65977872019-07-09 Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers Chen, Jiayun Li, Xingsong Zhong, Hongbin Meng, Yuhuan Du, Hongli Sci Rep Article The development and innovation of next generation sequencing (NGS) and the subsequent analysis tools have gain popularity in scientific researches and clinical diagnostic applications. Hence, a systematic comparison of the sequencing platforms and variant calling pipelines could provide significant guidance to NGS-based scientific and clinical genomics. In this study, we compared the performance, concordance and operating efficiency of 27 combinations of sequencing platforms and variant calling pipelines, testing three variant calling pipelines—Genome Analysis Tool Kit HaplotypeCaller, Strelka2 and Samtools-Varscan2 for nine data sets for the NA12878 genome sequenced by different platforms including BGISEQ500, MGISEQ2000, HiSeq4000, NovaSeq and HiSeq Xten. For the variants calling performance of 12 combinations in WES datasets, all combinations displayed good performance in calling SNPs, with their F-scores entirely higher than 0.96, and their performance in calling INDELs varies from 0.75 to 0.91. And all 15 combinations in WGS datasets also manifested good performance, with F-scores in calling SNPs were entirely higher than 0.975 and their performance in calling INDELs varies from 0.71 to 0.93. All of these combinations manifested high concordance in variant identification, while the divergence of variants identification in WGS datasets were larger than that in WES datasets. We also down-sampled the original WES and WGS datasets at a series of gradient coverage across multiple platforms, then the variants calling period consumed by the three pipelines at each coverage were counted, respectively. For the GIAB datasets on both BGI and Illumina platforms, Strelka2 manifested its ultra-performance in detecting accuracy and processing efficiency compared with other two pipelines on each sequencing platform, which was recommended in the further promotion and application of next generation sequencing technology. The results of our researches will provide useful and comprehensive guidelines for personal or organizational researchers in reliable and consistent variants identification. Nature Publishing Group UK 2019-06-27 /pmc/articles/PMC6597787/ /pubmed/31249349 http://dx.doi.org/10.1038/s41598-019-45835-3 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Chen, Jiayun
Li, Xingsong
Zhong, Hongbin
Meng, Yuhuan
Du, Hongli
Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers
title Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers
title_full Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers
title_fullStr Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers
title_full_unstemmed Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers
title_short Systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers
title_sort systematic comparison of germline variant calling pipelines cross multiple next-generation sequencers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6597787/
https://www.ncbi.nlm.nih.gov/pubmed/31249349
http://dx.doi.org/10.1038/s41598-019-45835-3
work_keys_str_mv AT chenjiayun systematiccomparisonofgermlinevariantcallingpipelinescrossmultiplenextgenerationsequencers
AT lixingsong systematiccomparisonofgermlinevariantcallingpipelinescrossmultiplenextgenerationsequencers
AT zhonghongbin systematiccomparisonofgermlinevariantcallingpipelinescrossmultiplenextgenerationsequencers
AT mengyuhuan systematiccomparisonofgermlinevariantcallingpipelinescrossmultiplenextgenerationsequencers
AT duhongli systematiccomparisonofgermlinevariantcallingpipelinescrossmultiplenextgenerationsequencers