Multi-laboratory validation of DNAxs including the statistical library DNAStatistX. (November 2020)

• Record Type: Journal Article
• Authors: Benschop, Corina C.G.; Hoogenboom, Jerry; Bargeman, Fiep; Hovers, Pauline; Slagter, Martin; van der Linden, Jennifer; Parag, Raymond; Kruise, Dennis; Drobnic, Katja; Klucevsek, Gregor; Parson, Walther; Berger, Burkhard; Laurent, Francois Xavier; Faivre, Magalie; Ulus, Ayhan; Schneider, Peter; Bogus, Magdalena; Kneppers, Alexander L.J.; Sijen, Titia
• Is Part Of: Forensic science international. Volume 49(2020)
• Publication Date: 2020-11
• Subjects: DNA profile interpretation -- Likelihood ratio -- Continuous model -- Validation -- DNAxs -- DNAStatistX; Forensic genetics -- Periodicals; Génétique légale -- Périodiques; Forensic genetics; Electronic journals; Periodicals; 614.1
• DOI: 10.1016/j.fsigen.2020.102390
• Languages: English
• ISSNs: 1872-4973

Abstract

Highlights: Five laboratories evaluated the robustness of the use of the interpretation tools DNAxs and DNAStatistX. Results showed high concordance between laboratories. Few differences in LRs were obtained, but these had no impact on reporting. Adjusted software parameters minimized differences and increased robustness. DNAxs and DNAStatistX were found user-friendly and valid for use in multiple laboratories. Abstract: This study describes a multi-laboratory validation of DNAxs, a DNA eXpert System for the data management and probabilistic interpretation of DNA profiles [1 ], and its statistical library DNAStatistX to which, besides the organising laboratory, four laboratories participated. The software was modified to read multiple data formats and the study was performed prior to the release of the software to the forensic community. The first exercise explored all main functionalities of DNAxs with feedback on user-friendliness, installation and general performance. Next, every laboratory performed likelihood ratio (LR) calculations using their own dataset and a dataset provided by the organising laboratory. The organising laboratory performed LR calculations using all datasets. The datasets were generated with different STR typing kits or analysis systems and consisted of samples varying in DNA amounts, mixture ratios, number of contributors and drop-out level. Hypothesis sets had the correct, under- and over-assigned number of contributors and true and false donors as person of interest. When comparing the results between laboratories, the LRs were foremost within one unit on log10 scale. The few LR results that deviated more had differences for the parameters estimated by the optimizer within DNAStatistX. Some of these were indicated by failed iteration results, others by a failed model validation, since unrealistic hypotheses were included. When these results that do not meet the quality criteria were excluded, as is in accordance with interpretation guidelines, none of the analyses in the different laboratories yielded a different statement in the casework report. Nonetheless, changes in software parameters were sought that minimized differences in outcomes, which made the DNAStatistX module more robust. Overall, the software was found intuitive, user-friendly and valid for use in multiple laboratories.