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<p>Variant benchmarking is critical in assessing the accuracy of genomic secondary pipelines. However, traditional benchmarking tools that require exact genotype matches inject biases from variant representation and are ill-suited for tandem repeat or structural variation. We describe Aardvark, a variant benchmarking tool that introduces the basepair score to directly compare haplotype sequences, reducing representation biases while allowing for partial credit scoring. The tool also includes the traditional genotype score and supports separate or joint benchmarking of small variants, tandem repeats, and structural variants (&lt;10 kb). Aardvark accepts standard inputs, runs <InlineEquation ID="IEq1"><EquationSource Format="TEX">\(\approx\)</EquationSource><EquationSource Format="MATHML"><math><mo>≈</mo></math></EquationSource></InlineEquation>18x faster than hap.py, and is open source (<a href="https://github.com/PacificBiosciences/aardvark">https://github.com/PacificBiosciences/aardvark</a> or <a href="https://doi.org/10.5281/zenodo.20271610">https://doi.org/10.5281/zenodo.20271610</a>).</p>

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Aardvark: sifting through differences in a mound of variants

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月18日

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  • James M. Holt,
  • Christopher T. Saunders,
  • Egor Dolzhenko,
  • Peter Krusche,
  • Nathan D. Olson,
  • Justin M. Zook,
  • Michael A. Eberle,
  • Zev Kronenberg

摘要

Variant benchmarking is critical in assessing the accuracy of genomic secondary pipelines. However, traditional benchmarking tools that require exact genotype matches inject biases from variant representation and are ill-suited for tandem repeat or structural variation. We describe Aardvark, a variant benchmarking tool that introduces the basepair score to directly compare haplotype sequences, reducing representation biases while allowing for partial credit scoring. The tool also includes the traditional genotype score and supports separate or joint benchmarking of small variants, tandem repeats, and structural variants (<10 kb). Aardvark accepts standard inputs, runs \(\approx\)≈18x faster than hap.py, and is open source (https://github.com/PacificBiosciences/aardvark or https://doi.org/10.5281/zenodo.20271610).