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Open Access Methodology article

Evaluation and optimisation of indel detection workflows for ion torrent sequencing of the BRCA1 and BRCA2 genes

Zhen Xuan Yeo1, Joshua Chee Leong Wong1, Steven G Rozen2* and Ann Siew Gek Lee134*

Author Affiliations

1 Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore

2 Centre for Computational Biology, Duke-NUS Graduate Medical School, Singapore, Singapore

3 Office of Clinical & Academic Faculty Affairs, Duke-NUS Graduate Medical School, Singapore, Singapore

4 Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

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BMC Genomics 2014, 15:516  doi:10.1186/1471-2164-15-516

Published: 24 June 2014

Abstract

Background

The Ion Torrent PGM is a popular benchtop sequencer that shows promise in replacing conventional Sanger sequencing as the gold standard for mutation detection. Despite the PGM’s reported high accuracy in calling single nucleotide variations, it tends to generate many false positive calls in detecting insertions and deletions (indels), which may hinder its utility for clinical genetic testing.

Results

Recently, the proprietary analytical workflow for the Ion Torrent sequencer, Torrent Suite (TS), underwent a series of upgrades. We evaluated three major upgrades of TS by calling indels in the BRCA1 and BRCA2 genes. Our analysis revealed that false negative indels could be generated by TS under both default calling parameters and parameters adjusted for maximum sensitivity. However, indel calling with the same data using the open source variant callers, GATK and SAMtools showed that false negatives could be minimised with the use of appropriate bioinformatics analysis. Furthermore, we identified two variant calling measures, Quality-by-Depth (QD) and VARiation of the Width of gaps and inserts (VARW), which substantially reduced false positive indels, including non-homopolymer associated errors without compromising sensitivity. In our best case scenario that involved the TMAP aligner and SAMtools, we achieved 100% sensitivity, 99.99% specificity and 29% False Discovery Rate (FDR) in indel calling from all 23 samples, which is a good performance for mutation screening using PGM.

Conclusions

New versions of TS, BWA and GATK have shown improvements in indel calling sensitivity and specificity over their older counterpart. However, the variant caller of TS exhibits a lower sensitivity than GATK and SAMtools. Our findings demonstrate that although indel calling from PGM sequences may appear to be noisy at first glance, proper computational indel calling analysis is able to maximize both the sensitivity and specificity at the single base level, paving the way for the usage of this technology for future clinical genetic testing.

Keywords:
Mutation detection; Indels; Next generation sequencing; BRCA1; BRCA2; Ion Torrent; Variant calling; Workflow