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

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.

Keywords: Complex DNA mixtures; Deconvolution; Probabilistic genotyping; Replicates; STRmix(™); Specificity.