Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform
Abstract Background ‘Next-generation’ (NGS) sequencing has wide application in medical genetics, including the detection of somatic variation in cancer. The Ion Torrent-based (IONT) platform is among NGS technologies employed in clinical, research and diagnostic settings. However, identifying mutati...
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doaj-7d8bd67ef3354177b42a64157d1a7b2a2020-11-25T00:51:38ZengBMCBMC Bioinformatics1471-21052018-01-0119111010.1186/s12859-017-1991-3Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platformAditya Deshpande0Wenhua Lang1Tina McDowell2Smruthy Sivakumar3Jiexin Zhang4Jing Wang5F. Anthony San Lucas6Jerry Fowler7Humam Kadara8Paul Scheet9Departments of Epidemiology, University of Texas MD Anderson Cancer CenterTranslational Molecular Pathology, University of Texas MD Anderson Cancer CenterTranslational Molecular Pathology, University of Texas MD Anderson Cancer CenterDepartments of Epidemiology, University of Texas MD Anderson Cancer CenterBioinformatics and Computational Biology, University of Texas MD Anderson Cancer CenterBioinformatics and Computational Biology, University of Texas MD Anderson Cancer CenterDepartments of Epidemiology, University of Texas MD Anderson Cancer CenterDepartments of Epidemiology, University of Texas MD Anderson Cancer CenterDepartment of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of BeirutDepartments of Epidemiology, University of Texas MD Anderson Cancer CenterAbstract Background ‘Next-generation’ (NGS) sequencing has wide application in medical genetics, including the detection of somatic variation in cancer. The Ion Torrent-based (IONT) platform is among NGS technologies employed in clinical, research and diagnostic settings. However, identifying mutations from IONT deep sequencing with high confidence has remained a challenge. We compared various computational variant-calling methods to derive a variant identification pipeline that may improve the molecular diagnostic and research utility of IONT. Results Using IONT, we surveyed variants from the 409-gene Comprehensive Cancer Panel in whole-section tumors, intra-tumoral biopsies and matched normal samples obtained from frozen tissues and blood from four early-stage non-small cell lung cancer (NSCLC) patients. We used MuTect, Varscan2, IONT’s proprietary Ion Reporter, and a simple subtraction we called “Poor Man’s Caller.” Together these produced calls at 637 loci across all samples. Visual validation of 434 called variants was performed, and performance of the methods assessed individually and in combination. Of the subset of inspected putative variant calls (n=223) in genomic regions that were not intronic or intergenic, 68 variants (30%) were deemed valid after visual inspection. Among the individual methods, the Ion Reporter method offered perhaps the most reasonable tradeoffs. Ion Reporter captured 83% of all discovered variants; 50% of its variants were visually validated. Aggregating results from multiple packages offered varied improvements in performance. Conclusions Overall, Ion Reporter offered the most attractive performance among the individual callers. This study suggests combined strategies to maximize sensitivity and positive predictive value in variant calling using IONT deep sequencing.http://link.springer.com/article/10.1186/s12859-017-1991-3Next-generation sequencingIon torrentVariant calling strategiesIon ReporterVarscan2MuTect |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Aditya Deshpande Wenhua Lang Tina McDowell Smruthy Sivakumar Jiexin Zhang Jing Wang F. Anthony San Lucas Jerry Fowler Humam Kadara Paul Scheet |
spellingShingle |
Aditya Deshpande Wenhua Lang Tina McDowell Smruthy Sivakumar Jiexin Zhang Jing Wang F. Anthony San Lucas Jerry Fowler Humam Kadara Paul Scheet Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform BMC Bioinformatics Next-generation sequencing Ion torrent Variant calling strategies Ion Reporter Varscan2 MuTect |
author_facet |
Aditya Deshpande Wenhua Lang Tina McDowell Smruthy Sivakumar Jiexin Zhang Jing Wang F. Anthony San Lucas Jerry Fowler Humam Kadara Paul Scheet |
author_sort |
Aditya Deshpande |
title |
Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform |
title_short |
Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform |
title_full |
Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform |
title_fullStr |
Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform |
title_full_unstemmed |
Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform |
title_sort |
strategies for identification of somatic variants using the ion torrent deep targeted sequencing platform |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2018-01-01 |
description |
Abstract Background ‘Next-generation’ (NGS) sequencing has wide application in medical genetics, including the detection of somatic variation in cancer. The Ion Torrent-based (IONT) platform is among NGS technologies employed in clinical, research and diagnostic settings. However, identifying mutations from IONT deep sequencing with high confidence has remained a challenge. We compared various computational variant-calling methods to derive a variant identification pipeline that may improve the molecular diagnostic and research utility of IONT. Results Using IONT, we surveyed variants from the 409-gene Comprehensive Cancer Panel in whole-section tumors, intra-tumoral biopsies and matched normal samples obtained from frozen tissues and blood from four early-stage non-small cell lung cancer (NSCLC) patients. We used MuTect, Varscan2, IONT’s proprietary Ion Reporter, and a simple subtraction we called “Poor Man’s Caller.” Together these produced calls at 637 loci across all samples. Visual validation of 434 called variants was performed, and performance of the methods assessed individually and in combination. Of the subset of inspected putative variant calls (n=223) in genomic regions that were not intronic or intergenic, 68 variants (30%) were deemed valid after visual inspection. Among the individual methods, the Ion Reporter method offered perhaps the most reasonable tradeoffs. Ion Reporter captured 83% of all discovered variants; 50% of its variants were visually validated. Aggregating results from multiple packages offered varied improvements in performance. Conclusions Overall, Ion Reporter offered the most attractive performance among the individual callers. This study suggests combined strategies to maximize sensitivity and positive predictive value in variant calling using IONT deep sequencing. |
topic |
Next-generation sequencing Ion torrent Variant calling strategies Ion Reporter Varscan2 MuTect |
url |
http://link.springer.com/article/10.1186/s12859-017-1991-3 |
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