STRmix™ put to the test: 300 000 non-contributor profiles compared to four-contributor DNA mixtures and the impact of replicates. (July 2019)

• Record Type: Journal Article
• Authors: Noël, Sarah; Noël, Josée; Granger, Dominic; Lefebvre, Jean-François; Séguin, Diane
• Is Part Of: Forensic science international. Volume 41(2019)
• Page Start: 24
• Page End: 31
• Publication Date: 2019-07
• Subjects: STRmix™ -- Probabilistic genotyping -- Specificity -- Complex DNA mixtures -- Deconvolution -- Replicates; Forensic genetics -- Periodicals; Génétique légale -- Périodiques; Forensic genetics; Electronic journals; Periodicals; 614.1
• DOI: 10.1016/j.fsigen.2019.03.017
• Languages: English
• ISSNs: 1872-4973

Abstract

Highlights: Complex known or apparent 4-person DNA mixtures with minor contributors were used. Mixtures were compared to 300, 000 non-contributors in STRmix ™ . 99.1% of the non-contributors had correct H2 support (LR < 1). Higher specificity (99.8%) was achieved when using replicate amplifications. Abstract: Probabilistic genotyping approaches are increasingly used for the interpretation of DNA mixtures. To explore the specificity of one of these systems (STRmix ™ ), we conducted an extensive study using 24 complex mixtures: all were known or apparent 4-person mixtures with at least one contributor representing less than 20% of total DNA, and all mixtures had at least one contributor with suboptimal DNA quantity. Those mixtures were either generated in-house or from casework. All the mixtures were compared to 300, 000 virtual non-contributors, resulting in a dataset of 7.2 million comparisons. The great majority of the non-contributor comparisons led to a LR lower than 1 for a specificity of 99.1%. The effect of using replicate amplifications to calculate the LR of non-contributors was also assessed as triplicates were used and led to an increased specificity of 99.8%. The very large extent of the analyzed data shows that STRmix ™ has an excellent ability to discriminate non-contributors from complex DNA mixtures.