Validating TrueAllele Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors.

Most DNA evidence is a mixture of two or more people. Cybergenetics TrueAllele system uses Bayesian computing to separate genotypes from mixture data and compare genotypes to calculate likelihood ratio (LR) match statistics. This validation study examined the reliability of TrueAllele computing on laboratory-generated DNA mixtures containing up to ten unknown contributors.

TrueAllele(®) Genotype Identification on DNA Mixtures Containing up to Five Unknown Contributors.

Computer methods have been developed for mathematically interpreting mixed and low-template DNA. The genotype modeling approach computationally separates out the contributors to a mixture, with uncertainty represented through probability. Comparison of inferred genotypes calculates a likelihood ratio (LR), which measures identification information.

TrueAllele casework on Virginia DNA mixture evidence: computer and manual interpretation in 72 reported criminal cases.

Mixtures are a commonly encountered form of biological evidence that contain DNA from two or more contributors. Laboratory analysis of mixtures produces data signals that usually cannot be separated into distinct contributor genotypes. Computer modeling can resolve the genotypes up to probability, reflecting the uncertainty inherent in the data.