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A tool for simulating single source and mixed DNA profiles.

Maarten Kruijver¹, Jo-Anne Bright¹

¹ESR, Auckland, New Zealand.

Forensic Science International. Genetics

|July 17, 2022

Summary

This summary is machine-generated.

This study introduces simDNAmixtures, an R-package for in silico DNA profile simulation. It models complex factors like peak height variability, aiding probabilistic genotyping software validation.

Keywords:

DNA mixtures Probabilistic genotyping Simulation

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Area of Science:

Forensic Science
Computational Biology
Genetics

Background:

Probabilistic genotyping systems require robust validation.
Existing simulation tools often oversimplify complex biological factors like peak height variability.
There is a continuous need for advanced simulation methods to study these systems.

Purpose of the Study:

To introduce simDNAmixtures, a novel R-package for in silico simulation of DNA mixtures.
To provide a tool that incorporates realistic complexities such as peak height variability and relatedness.
To facilitate the validation and investigation of probabilistic genotyping software.

Main Methods:

Contributor genotypes simulated via allele frequency sampling.
Gene dropping used for related contributors within a pedigree structure.
Peak height variability modeled using lognormal or gamma distributions.
Configurable parameters include contributor number, DNA template amount, and degradation.

Main Results:

Simulated DNA profiles exhibit behavior broadly similar to laboratory-generated profiles.
The simDNAmixtures tool successfully models complex factors often omitted in simpler simulations.
While showing similarities, simulated profiles display less variation than experimental data.

Conclusions:

simDNAmixtures offers a valuable tool for in silico validation of probabilistic genotyping software.
The package addresses the need for more realistic DNA mixture simulations.
Experimental data remains essential, but simulation tools like simDNAmixtures enhance research capabilities.