Abstract
BackgroundThe 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.ResultsRecently, 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.ConclusionsNew 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-516) contains supplementary material, which is available to authorized users.
Highlights
The Ion Torrent PGM is a popular benchtop sequencer that shows promise in replacing conventional Sanger sequencing as the gold standard for mutation detection
We examined the distribution of the four measurements generated by indel calling workflows that used the TMAP-TS3.4 and BWA alignments combined with the GATK and SAMtools variant calling
Comparison of single nucleotide variations (SNV) calling in the 6 training samples using different variant calling workflows
Summary
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. The PGM performed well in accurately detecting single nucleotide variations (SNV) but the overall specificity remained low due to the high false positive rate for indel detection [2,5,6]. A low false positive rate is necessary if the clinical laboratory is screening for deleterious mutations using the PGM for tens or hundreds of patients
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