Open source software EuroForMix can be used to analyse complex SNP mixtures. (November 2017)

• Record Type: Journal Article
• Authors: Bleka, Øyvind; Eduardoff, Mayra; Santos, Carla; Phillips, Chris; Parson, Walther; Gill, Peter
• Is Part Of: Forensic science international. Volume 31(2017)
• Page Start: 105
• Page End: 110
• Publication Date: 2017-11
• Subjects: SNP -- EuroForMix -- Complex mixture -- Likelihood ratio -- Sequence read; Forensic genetics -- Periodicals; Génétique légale -- Périodiques; Forensic genetics; Electronic journals; Periodicals; 614.1
• DOI: 10.1016/j.fsigen.2017.08.001
• Languages: English
• ISSNs: 1872-4973

Abstract

Highlights: This paper describes the first demonstration of a quantitative likelihood ratio mixture calculation of a SNP panel. It is demonstrated that uncertainty about the number of contributors to a mixture has little effect of the likelihood ratio. The demonstration removes a barrier to widespread adoption of SNP crime-stain analysis. Abstract: A series of two- and three-person mixtures of varying dilutions were prepared and analysed with Life Technologies' HID-Ion AmpliSeq™ Identity Panel v2.2 using the Ion PGM™ massively parallel sequencing (MPS) system. From this panel we used 134 autosomal SNPs. Using the reference samples of three donors, we evaluated the strength of evidence with likelihood ratio (LR) calculations using the open-source quantitative EuroForMix program and compared the results with a previous study using a qualitative software (LRmix). SNP analysis is a special case of STRs, restricted to a maximum of two alleles per locus. We showed that simple two-person mixtures can be readily analysed with both LRmix and Euroformix, but the performance of three- or more person mixtures is generally inefficient with LRmix. Taking account of the "peak height" information, by substituting 'sequence read' coverage values from the MPS data for each SNP allele, greatly improves the discrimination between true and non-contributors. The higher the mixture proportion ( Mx ) of the person of interest is, the higher the LR. Simulation experiments (up to six contributors) showed that the strength of the evidence is dependent upon Mx, but relatively insensitive to the number of contributors. If a higher number of loci were multiplexed, the analysis of mixtures would be much improved, because the extra information would enable lower Mx values to be evaluated. In summary, incorporating the 'sequence read' (coverage) into the quantitative model shows a significant benefit over the qualitative approach. Calculations are quite fast (six seconds for three contributors).