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. 2022 Jul 11:11:775.
doi: 10.12688/f1000research.122840.1. eCollection 2022.

vcferr: Development, validation, and application of a single nucleotide polymorphism genotyping error simulation framework

V P Nagraj  1 , Matthew Scholz  1 , Shakeel Jessa  1 , Jianye Ge  2 , August E Woerner  2 , Meng Huang  2 , Bruce Budowle  2 , Stephen D Turner  1
Affiliations

vcferr: Development, validation, and application of a single nucleotide polymorphism genotyping error simulation framework

V P Nagraj et al. F1000Res. .

Abstract

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).

Keywords: GWAS; benchmarking; bioinformatics; genealogy; kinship; python; simulation.

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Conflict of interest statement

No competing interests were disclosed.

Figures

Figure 1.
Figure 1.. Impact of genotyping error on inferred degree classification accuracy.
Each line corresponds to a type of error, with error rates from 0 to 0.2 stepped at 0.01 increments while holding all other types of error constant at 0. The solid black line at the bottom represents the accuracy at guessing, which is the floor for relationship degree classification.
See this image and copyright information in PMC

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