F1000Research (Jul 2022)

vcferr: Development, validation, and application of a single nucleotide polymorphism genotyping error simulation framework [version 1; peer review: 1 approved, 2 approved with reservations]

  • Bruce Budowle,
  • Shakeel Jessa,
  • Jianye Ge,
  • Stephen D. Turner,
  • Matthew Scholz,
  • August E. Woerner,
  • Meng Huang,
  • V.P. Nagraj

Journal volume & issue
Vol. 11

Abstract

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Motivation: Genotyping error can impact downstream single nucleotide polymorphism (SNP)-based analyses. Simulating various modes and levels of error can help investigators better understand potential biases caused by miscalled genotypes. Methods: We have developed and validated vcferr, a tool to probabilistically simulate genotyping error and missingness in variant call format (VCF) files. We demonstrate how vcferr could be used to address a research question by introducing varying levels of error of different type into a sample in a simulated pedigree, and assessed how kinship analysis degrades as a function of the kind and type of error. Software availability: vcferr is available for installation via PyPi (https://pypi.org/project/vcferr/) or conda (https://anaconda.org/bioconda/vcferr). The software is released under the MIT license with source code available on GitHub (https://github.com/signaturescience/vcferr)

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