Internal validation of STRmix™ for the interpretation of single source and mixed DNA profiles

The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity

Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decision-making toward computer-based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG). Decision-making by laboratories to implement probability-based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. The principles behind STRmix™ are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights. All PG methods generate a likelihood ratio (LR) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG, and in particular, STRmix™. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STRmix™, one of the available PG software.

A response to "Likelihood ratio as weight of evidence: A closer look" by Lund and Iyer

Recently, Lund and Iyer (L&I) raised an argument regarding the use of likelihood ratios in court. In our view, their argument is based on a lack of understanding of the paradigm. L&I argue that the decision maker should not accept the expert's likelihood ratio without further consideration. This is agreed by all parties. In normal practice, there is often considerable and proper exploration in court of the basis for any probabilistic statement. We conclude that L&I argue against a practice that does not exist and which no one advocates. Further we conclude that the most informative summary of evidential weight is the likelihood ratio. We state that this is the summary that should be presented to a court in every scientific assessment of evidential weight with supporting information about how it was constructed and on what it was based.

Separation/extraction, detection, and interpretation of DNA mixtures in forensic science (review)

Interpreting mixed DNA samples containing material from multiple contributors has long been considered a major challenge in forensic casework, especially when encountering low-template DNA (LT-DNA) or high-order mixtures that may involve missing alleles (dropout) and unrelated alleles (drop-in), among others. In the last decades, extraordinary progress has been made in the analysis of mixed DNA samples, which has led to increasing attention to this research field. The advent of new methods for the separation and extraction of DNA from mixtures, novel or jointly applied genetic markers for detection and reliable interpretation approaches for estimating the weight of evidence, as well as the powerful massively parallel sequencing (MPS) technology, has greatly extended the range of mixed samples that can be correctly analyzed. Here, we summarized the investigative approaches and progress in the field of forensic DNA mixture analysis, hoping to provide some assistance to forensic practitioners and to promote further development involving this issue.

Massively parallel sequencing-enabled mixture analysis of mitochondrial DNA samples

The mitochondrial genome has a number of characteristics that provide useful information to forensic investigations. Massively parallel sequencing (MPS) technologies offer improvements to the quantitative analysis of the mitochondrial genome, specifically the interpretation of mixed mitochondrial samples. Two-person mixtures with nuclear DNA ratios of 1:1, 5:1, 10:1, and 20:1 of individuals from different and similar phylogenetic backgrounds and three-person mixtures with nuclear DNA ratios of 1:1:1 and 5:1:1 were prepared using the Precision ID mtDNA Whole Genome Panel and Ion Chef, and sequenced on the Ion PGM or Ion S5 sequencer (Thermo Fisher Scientific, Waltham, MA, USA). These data were used to evaluate whether and to what degree MPS mixtures could be deconvolved. Analysis was effective in identifying the major contributor in each instance, while SNPs from the minor contributor's haplotype only were identified in the 1:1, 5:1, and 10:1 two-person mixtures. While the major contributor was identified from the 5:1:1 mixture, analysis of the three-person mixtures was more complex, and the mixed haplotypes could not be completely parsed. These results indicate that mixed mitochondrial DNA samples may be interpreted with the use of MPS technologies.