BioinformaticsBioinformaticsPeer-reviewed journal article
vcfgl: A flexible genotype likelihood simulator for VCF/BCF files
Isin AltinkayaiD, Rasmus NielseniD, Thorfinn Sand KorneliusseniD
Abstract
MotivationAccurate quantification of genotype uncertainty is pivotal in ensuring the reliability of genetic inferences drawn from NGS data. Genotype uncertainty is typically modeled using Genotype Likelihoods (GLs), which can help propagate measures of statistical uncertainty in base calls to downstream analyses. However, the effects of errors and biases in the estimation of GLs, introduced by biases in the original base call quality scores or the discretization of quality scores, as well as the choice of the GL model, remain under-explored. ResultsWe present vcfgl, a versatile tool for simulating genotype likelihoods associated with simulated read data. It offers a framework for researchers to simulate and investigate the uncertainties and biases associated with the quantification of uncertainty, thereby facilitating a deeper understanding of their impacts on downstream analytical methods. Through simulations, we demonstrate the utility of vcfgl in benchmarking GL-based methods. The program can calculate GLs using various widely used genotype likelihood models and can simulate the errors in quality scores using a Beta distribution. It is compatible with modern simulators such as msprime and SLiM, and can output data in pileup, VCF/BCF and gVCF file formats. The vcfgl program is freely available as an efficient and user-friendly software written in C/C++. Availabilityvcfgl is freely available at https://github.com/isinaltinkaya/vcfgl. Contactisin.altinkaya@sund.ku.dk Supplementary informationSupplementary information is available online.
- assay: whole-genome sequencing
- research focus: benchmarking
- research focus: variant calling
- research focus: variant effect prediction
- approach: simulation
- Citations
- 4
- FWCI
- 1.20
- Field percentile
- top 26%
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