title: New York State TrueAllele ® casework validation study.
abstract: DNA evidence can pose interpretation challenges, particularly with low-level or mixed samples. It would be desirable to make full use of the quantitative data, consider every genotype possibility, and objectively produce accurate and reproducible DNA match results. Probabilistic genotype computing is designed to achieve these goals. This validation study assessed TrueAllele(®) probabilistic computer interpretation on 368 evidence items in 41 test cases and compared the results with human review of the same data. Whenever there was a human result, the computer's genotype was concordant. Further, the computer produced a match statistic on 81 mixture items (for 87 inferred matching genotypes) in the test cases, while human review reported a statistic on 25 of these items (30.9%). Using match statistics to quantify information, probabilistic genotyping was shown to be sensitive, specific, and reproducible. These results demonstrate that objective probabilistic genotyping of biological evidence can reliably preserve DNA identification information.
authors.affiliation: Cybergenetics Corp, 160 North Craig Street, Suite 210, Pittsburgh, PA, 15213.
authors.forename: Mark W
authors.initials: MW
authors.lastname: Perlin
authors.forename: Jamie L
authors.initials: JL
authors.lastname: Belrose
authors.forename: Barry W
authors.initials: BW
authors.lastname: Duceman
mesh_terms: D003198:Computer Simulation; D016172:DNA Fingerprinting; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D018895:Microsatellite Repeats; D011336:Probability; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: DNA evidence; developmental validation; forensic science; identification information; likelihood ratio; mixture interpretation; probabilistic genotype