Validation of an internal method for the interpretation of mixed genetic profiles and validation of a probabilistic genotyping software within the Forensic Genetics Laboratory of the Forensic Scientific Police Service

This doctoral research focuses on the validation of an internal method for the analysis of mixed DNA profiles and the implementation of probabilistic genotyping software (PGS) within the Forensic Genetics Laboratory of the Forensic Science Police Service in Rome. The project responds to the growing need to extend the laboratory’s ISO/IEC 17025 accreditation—previously limited to single-source DNA profiles—to the analysis of mixed profiles, which are increasingly common in forensic casework due to advances in DNA recovery from trace, degraded, or low-template biological samples. The research was developed in two principal phases. The first concerned the validation of the complete analytical workflow for the interpretation of mixed genetic profiles involving two and three contributors. Ad hoc mixtures were prepared in the laboratory using buccal swabs from selected individuals, ensuring defined allelic compositions and mixture ratios. These samples were analysed using the GlobalFiler™ PCR Amplification Kit, capillary electrophoresis on the Applied Biosystems 3500 Genetic Analyzer, and GeneMapper® ID-X software, in accordance with internal procedures. The study verified whether analytical thresholds values validated for single profiles could be extended to mixed profiles. Results confirmed the suitability of previously validated thresholds for both low-template (LT-DNA) and conventional samples (cDNA). The second phase addressed the validation of probabilistic genotyping software to complement the classical, expert-based interpretation of mixed profiles with an objective, likelihood ratio (LR)–based statistical assessment. After a comparative evaluation between semi-continuous and continuous models—specifically LRmixStudio, STRmix™, and EuroForMix—the latter was identified as the most appropriate for the laboratory’s operational needs. EuroForMix was therefore subjected to a comprehensive internal validation process, following the SWGDAM (2015), to assess its performance, reproducibility, and limitations. Validation datasets included laboratory-generated mixtures, in silico samples derived from the PROVEDIt database, and real forensic cases, representing the full range of complexities encountered in practice. Validation tests examined reliability, precision, sensitivity, and specificity. Repeated analyses demonstrated high reproducibility of LR values, with minimal variability between runs. Sensitivity assessments confirmed the software’s robustness even in cases of partial profiles or stochastic effects for true contributors, while specificity testing verified that non-contributors consistently yielded LR values below 1, thus minimizing false inclusions. Additional studies on over- and underestimation of the number of contributors highlighted the software’s capacity to maintain stable likelihood ratios across different mixture hypotheses. The analytical models implemented in EuroForMix—based on gamma distributions for peak height data—proved effective in accounting for allele drop-out, stutter, and degradation phenomena. The findings demonstrate that EuroForMix provides a scientifically sound and transparent framework for interpreting complex DNA mixtures, supporting the forensic analyst in producing reproducible, probabilistically weighted conclusions. Nonetheless, the study emphasises that PGS tools must be regarded as complementary aids rather than substitutes for expert judgment. Their outputs require critical interpretation within the broader evidentiary and contextual framework of each case. Overall, this doctoral work strengthens the methodological and interpretative capacity of the Forensic Genetics Laboratory of the Italian Scientific Police, integrating validated probabilistic models into accredited workflows. The validated use of EuroForMix enhances the objectivity, reproducibility, and international comparability of forensic DNA interpretations, thereby contributing to greater scientific rigour and judicial reliability in the evaluation of complex biological evidence.