A novel computational strategy to predict the value of the evidence in the SNP-based forensic mixtures

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This study introduces a methodology for inferring the weight of the evidence (WoE) in the single nucleotide polymorphism (SNP)-typed DNA mixtures of forensic interest. First, we redefined some algebraic formulae to approach the semi-continuous calculation of likelihoods and likelihood ratios (LRs). To address the allelic dropouts, a peak height ratio index (“h,” an index of heterozygous state plausibility) was incorporated into semi-continuous formulae to act as a proxy for the “split-drop” model of calculation. Second, the original ratio at which a person of interest (POI) has entered into the mixture was inferred by evaluating the DNA amounts conferred by unique genotypes to any possible permutation of any locus of the typing protocol (unique genotypes are genotypes that appear just once in the relevant permutation). We compared this expected ratio (MRex) to all the mixing ratios emerging at all other permutations of the mixture (MRobs) using several (1 - χ2) tests to evaluate the probability of each permutation to exist in the mixture according to quantitative criteria. At the level of each permutation state, we multiplied the (1 - χ2) value to the genotype frequencies and the h index. All the products of all the permutation states were finally summed to give a likelihood value that accounts for three independent properties of the mixtures. Owing to the (1 - χ2) index and the h index, this approach qualifies as a fully continuous methodology of LR calculation. We compared the MRs and LRs emerging from our methodology to those generated by the EuroForMix software ver. 3.0.3. When the true contributors were tested as POIs, our procedure generated highly discriminant LRs that, unlike EuroForMix, never overcame the corresponding single-source LRs. When false contributors were tested as POIs, we obtained a much lower LR value than that from EuroForMix. These two findings indicate that our computational method is more reliable and realistic than EuroForMix.
Lingua originaleEnglish
pagine (da-a)e0247344-e0247344
RivistaPLoS One
Stato di pubblicazionePubblicato - 2021


  • Alleles
  • DNA
  • DNA Fingerprinting
  • Forensic Genetics
  • Genetic Techniques
  • Genotype
  • Humans
  • Likelihood Functions
  • Microsatellite Repeats
  • Models, Genetic
  • Polymorphism, Single Nucleotide
  • Sequence Analysis, DNA
  • Software


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