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Evaluating DNA Mixtures with Contributors from Different Populations Using Probabilistic Genotyping

NCJ Number
Genes Volume: 14 Issue: 1 Dated: 2023
Maarten Kruijver ; Hannah Kelly ; Jo-Anne Bright ; John Buckleton
Date Published

The reported project evaluated DNA mixtures with contributors from different populations by using probabilistic genotyping.


It is common practice to evaluate DNA profiling evidence with likelihood ratios using allele frequency estimates from a relevant population. When multiple populations may be relevant, a choice has to be made. For two-person mixtures without dropout, it has been reported that conservative estimates can be obtained by using the Person of Interest’s population with a θ  value of 3%. More accurate estimates can be obtained by explicitly modelling different populations. One option is to present a minimum likelihood ratio across populations; another is to present a stratified likelihood ratio that incorporates a weighted average of likelihoods across multiple populations. For high template single source profiles, any difference between the methods is immaterial as far as conclusions are concerned. Th authors revisited this issue in the context of potentially low-level and mixed samples where the contributors may originate from different populations and study likelihood ratio behavior. They first present a method for evaluating DNA profiling evidence using probabilistic genotyping when the contributors may originate from different ethnic groups. In this method, likelihoods are weighted across a prior distribution that assigns sample donors to ethnic groups. The prior distribution can be constrained such that all sample donors are from the same ethnic group, or all permutations can be considered. A simulation study is used to determine the effect of either assumption on the likelihood ratio. The likelihood ratios are also compared to the minimum likelihood ratio across populations. The authors demonstrate that the common practice of taking a minimum likelihood ratio across populations is not always conservative when FST=0. Population stratification methods may also be non-conservative in some cases. When FST>0  is used in the likelihood ratio calculations, as is recommended, all compared approaches become conservative on average to varying degrees. (Published abstract provided)