title: Complex DNA mixture analysis in a forensic context: evaluating the probative value using a likelihood ratio model.
abstract: The interpretation of mixed DNA profiles obtained from low template DNA samples has proven to be a particularly difficult task in forensic casework. Newly developed likelihood ratio (LR) models that account for PCR-related stochastic effects, such as allelic drop-out, drop-in and stutters, have enabled the analysis of complex cases that would otherwise have been reported as inconclusive. In such samples, there are uncertainties about the number of contributors, and the correct sets of propositions to consider. Using experimental samples, where the genotypes of the donors are known, we evaluated the feasibility and the relevance of the interpretation of high order mixtures, of three, four and five donors. The relative risks of analyzing high order mixtures of three, four, and five donors, were established by comparison of a 'gold standard' LR, to the LR that would be obtained in casework. The 'gold standard' LR is the ideal LR: since the genotypes and number of contributors are known, it follows that the parameters needed to compute the LR can be determined per contributor. The 'casework LR' was calculated as used in standard practice, where unknown donors are assumed; the parameters were estimated from the available data. Both LRs were calculated using the basic standard model, also termed the drop-out/drop-in model, implemented in the LRmix module of the R package Forensim. We show how our results furthered the understanding of the relevance of analyzing high order mixtures in a forensic context. Limitations are highlighted, and it is illustrated how our study serves as a guide to implement likelihood ratio interpretation of complex DNA profiles in forensic casework.
authors.affiliation: Department of Human Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands. Electronic address: h.haned@nfi.minvenj.nl.
authors.forename: Hinda
authors.initials: H
authors.lastname: Haned
authors.affiliation: Department of Human Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands. Electronic address: c.benschop@nfi.minvenj.nl.
authors.forename: Corina C G
authors.initials: CCG
authors.lastname: Benschop
authors.affiliation: National Institute of Public Health, Department of Forensic Biology, P.O. Box 4404 Nydalen, 0403 Oslo, Norway; National Institute of Public Health, Department of Forensic Medicine, P.O. Box 4950 Nydalen, 0424 Oslo, Norway. Electronic address: peterd.gill@gmail.com.
authors.forename: Peter D
authors.initials: PD
authors.lastname: Gill
authors.affiliation: Department of Human Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands. Electronic address: t.sijen@nfi.minvenj.nl.
authors.forename: Titia
authors.initials: T
authors.lastname: Sijen
mesh_terms: D045424:Complex Mixtures / Q000032:analysis* / Q000235:genetics; D004247:DNA / Q000032:analysis* / Q000097:blood / Q000235:genetics / Q000302:isolation & purification; D053803:Forensic Genetics / Q000379:methods*; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D011336:Probability
chemical_list: D045424:Complex Mixtures; D004247:DNA
keywords: Drop-in; Drop-out; High order mixtures; LRmix; Likelihood ratios; Robustness