ArticleJournal of forensic sciences2013
New York State TrueAllele ® casework validation study.
Article in Journal of forensic sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 23 citations in OpenAlex.
- Article
- DNA Mixture Deconvolution: A Four-Strategy Framework from Physical Separation to Database Searching.Genes · 2026Review
- A new implementation of a semi-continuous method for DNA mixture interpretation.Forensic Science International. Reports · 2022Article
- Article
- Validating TrueAlleleJournal of forensic sciences · 2020Article
- Mixture deconvolution by massively parallel sequencing of microhaplotypes.International journal of legal medicine · 2019Article
- The future of forensic DNA analysis.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015Review
- Inclusion probability for DNA mixtures is a subjective one-sided match statistic unrelated to identification information.Journal of pathology informatics · 2015Article
- TrueAllele casework on Virginia DNA mixture evidence: computer and manual interpretation in 72 reported criminal cases.PloS one · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.