In this paper, the authors introduce a simulation tool for the generation of single-source and mixed DNA profiles according to models used in probabilistic genotyping; they note that the tool is open source and built to be flexible with regards to different peak height models and population genetic models, which makes it possible to use the tool in various types of simulation studies.
Simulation studies play an important role in the study of probabilistic genotyping systems, as a low cost and fast alternative to in vitro studies. With ongoing calls for further study of the behavior of probabilistic genotyping systems, there is a continuous need for such studies. In most cases, researchers use simplified models, for example ignoring complexities such as peak height variability due to lack of availability of advanced tools. The authors seek to fill this void and describe a tool that can simulate DNA profiles in silico for the validation and investigation of probabilistic genotyping software. The authors simulated contributor genotypes by randomly sampling alleles from selected allele frequencies. Some or all contributors may be related to a pedigree and the genotypes of non-founders are obtained by random gene dropping. They note that the number of contributors per profile, and ranges for parameters such as DNA template amount and degradation parameters can be configured. Peak height variability is modelled using a lognormal distribution or a gamma distribution. Profile behavior of simulated profiles is shown to be broadly similar to laboratory generated profiles though the latter shows more variation. The authors also note that simulation studies do not remove the need for experimental data. Their tool has been made available as an R-package named simDNAmixtures. Publisher Abstract Provided
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