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Abstract

Minimizing false positives is a critical issue when variant calling as no method is without error. It is common practice to post-process a variant-call file (VCF) using hard filter criteria intended to discriminate true-positive (TP) from false-positive (FP) calls. These are applied on the simple principle that certain characteristics are disproportionately represented among the set of FP calls and that a user-chosen threshold can maximize the number detected. To provide guidance on this issue, this study empirically characterized all false SNP and indel calls made using real Illumina sequencing data from six disparate species and 166 variant-calling pipelines (the combination of 14 read aligners with up to 13 different variant callers, plus four ‘all-in-one’ pipelines). We did not seek to optimize filter thresholds but instead to draw attention to those filters of greatest efficacy and the pipelines to which they may most usefully be applied. In this respect, this study acts as a coda to our previous benchmarking evaluation of bacterial variant callers, and provides general recommendations for effective practice. The results suggest that, of the pipelines analysed in this study, the most straightforward way of minimizing false positives would simply be to use Snippy. We also find that a disproportionate number of false calls, irrespective of the variant-calling pipeline, are located in the vicinity of indels, and highlight this as an issue for future development.

Funding
This study was supported by the:
  • National Institute for Health Research Health Protection Research Unit (Award HPRU-2012-10041)
    • Principle Award Recipient: NotApplicable
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2021-08-04
2024-04-25
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