Internal Validation of STRmix (TM) for the Interpretation of Single Source and Mixed DNA Profiles

• NCJ Number: 252342
• Author(s): Tamyra R. Moretti, Rebecca S. Just, Susannah C. Kehl, Leah E. Willis, John S. Buckleton, Jo-Anne Bright, Duncan A. Taylor, Anthony J. Onorato
• Date Published: July 2017
• Length: 19 pages
• Agencies: NIJ-Sponsored
• Award: Population Genetic Issues for Forensic DNA Profiles

Annotation

This article reports on studies that assessed and internally validated the probabilistic genotyping software STRmix™ for casework usage at the Federal Bureau of Investigation Laboratory, using lab-specific parameters and more than 300 single-source and mixed contributor profiles.

Abstract

The interpretation of DNA evidence can involve analysis of challenging STR typing results. Genotypes inferred from low quality or quantity specimens, or mixed DNA samples originating from multiple contributors, can result in weak or inconclusive match probabilities when a binary interpretation method and necessary thresholds (such as a stochastic threshold) are employed. Probabilistic genotyping approaches, such as fully continuous methods that incorporate empirically determined biological parameter models, enable usage of more of the profile information and reduce subjectivity in interpretation. As a result, software-based probabilistic analyses tend to produce more consistent and more informative results regarding potential contributors to DNA evidence. In the current study, simulated forensic specimens, including constructed mixtures that included DNA from two to five donors across a broad range of template amounts and contributor proportions, were used to examine the sensitivity and specificity of the system via more than 60,000 tests that compared hundreds of known contributors and non-contributors to the specimens. Conditioned analyses, concurrent interpretation of amplification replicates, and application of an incorrect contributor number were also performed to further investigate software performance and probe the limitations of the system. In addition, the results from manual and probabilistic interpretation of both prepared and evidentiary mixtures were compared. The findings support that STRmix™ is sufficiently robust for implementation in forensic laboratories, offering numerous advantages over historical methods of DNA profile analysis and greater statistical power for the estimation of evidentiary weight, and can be used reliably in human identification testing. With few exceptions, likelihood ratio results reflected intuitively correct estimates of the weight of the genotype possibilities and known contributor genotypes. This comprehensive evaluation provides a model in accordance with SWGDAM recommendations for internal validation of a probabilistic genotyping system for DNA evidence interpretation. (Publisher abstract modified)